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Posted to commits@tvm.apache.org by tq...@apache.org on 2022/05/04 08:48:36 UTC
[tvm-site] branch asf-site updated: deploying docs (apache/tvm@a0c61038b6fd25f0a1cf8673a76b9ff6d8fa5052)
This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/tvm-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 454b4247f deploying docs (apache/tvm@a0c61038b6fd25f0a1cf8673a76b9ff6d8fa5052)
454b4247f is described below
commit 454b4247f9ac5f32e31784a944be038774a6d8d7
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Wed May 4 08:48:31 2022 +0000
deploying docs (apache/tvm@a0c61038b6fd25f0a1cf8673a76b9ff6d8fa5052)
---
.../how_to/compile_models/from_mxnet.rst.txt | 2 +-
.../how_to/compile_models/from_oneflow.rst.txt | 7 +-
.../how_to/compile_models/from_paddle.rst.txt | 2 +-
.../how_to/compile_models/from_pytorch.rst.txt | 2 +-
.../how_to/compile_models/from_tensorflow.rst.txt | 2 +-
.../compile_models/sg_execution_times.rst.txt | 22 +-
.../deploy_models/deploy_model_on_android.rst.txt | 2 +-
.../deploy_object_detection_pytorch.rst.txt | 4 +-
.../deploy_models/deploy_prequantized.rst.txt | 6 +-
.../deploy_prequantized_tflite.rst.txt | 4 +-
.../how_to/deploy_models/deploy_quantized.rst.txt | 2 +-
.../deploy_models/deploy_ssd_gluoncv.rst.txt | 4 +-
.../deploy_models/sg_execution_times.rst.txt | 18 +-
.../extend_tvm/bring_your_own_datatypes.rst.txt | 2 +-
.../how_to/extend_tvm/sg_execution_times.rst.txt | 10 +-
.../how_to/extend_tvm/use_pass_instrument.rst.txt | 16 +-
.../optimize_operators/opt_conv_cuda.rst.txt | 2 +-
.../optimize_operators/opt_conv_tensorcore.rst.txt | 2 +-
.../how_to/optimize_operators/opt_gemm.rst.txt | 16 +-
.../optimize_operators/sg_execution_times.rst.txt | 8 +-
.../sg_execution_times.rst.txt | 16 +-
.../tune_conv2d_layer_cuda.rst.txt | 818 +++--
.../tune_network_cuda.rst.txt | 2 +-
.../tune_network_x86.rst.txt | 4 +-
.../tune_sparse_x86.rst.txt | 132 +-
.../tune_with_autotvm/sg_execution_times.rst.txt | 12 +-
.../tune_with_autotvm/tune_conv2d_cuda.rst.txt | 34 +-
.../work_with_microtvm/micro_autotune.rst.txt | 16 +-
.../work_with_microtvm/sg_execution_times.rst.txt | 12 +-
.../work_with_relay/sg_execution_times.rst.txt | 8 +-
.../work_with_schedules/sg_execution_times.rst.txt | 18 +-
.../how_to/work_with_schedules/tensorize.rst.txt | 2 +-
.../tutorials/autotvm/sg_execution_times.rst.txt | 6 +-
.../frontend/deploy_classification.rst.txt | 2 +-
.../tutorials/frontend/deploy_detection.rst.txt | 2 +-
.../tutorials/frontend/sg_execution_times.rst.txt | 6 +-
.../tutorials/optimize/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/sg_execution_times.rst.txt | 6 +-
.../tutorial/auto_scheduler_matmul_x86.rst.txt | 2 +-
docs/_sources/tutorial/autotvm_relay_x86.rst.txt | 65 +-
.../tutorial/cross_compilation_and_rpc.rst.txt | 2 +-
docs/_sources/tutorial/intro_topi.rst.txt | 2 +-
docs/_sources/tutorial/sg_execution_times.rst.txt | 26 +-
.../tutorial/tensor_expr_get_started.rst.txt | 45 +-
docs/commit_hash | 2 +-
docs/how_to/compile_models/from_mxnet.html | 2 +-
docs/how_to/compile_models/from_oneflow.html | 3757 +-------------------
docs/how_to/compile_models/from_paddle.html | 2 +-
docs/how_to/compile_models/from_pytorch.html | 6 +-
docs/how_to/compile_models/from_tensorflow.html | 2 +-
docs/how_to/compile_models/sg_execution_times.html | 22 +-
.../deploy_models/deploy_model_on_android.html | 2 +-
.../deploy_object_detection_pytorch.html | 18 +-
docs/how_to/deploy_models/deploy_prequantized.html | 9 +-
.../deploy_models/deploy_prequantized_tflite.html | 4 +-
docs/how_to/deploy_models/deploy_quantized.html | 2 +-
docs/how_to/deploy_models/deploy_ssd_gluoncv.html | 48 +-
docs/how_to/deploy_models/sg_execution_times.html | 18 +-
.../extend_tvm/bring_your_own_datatypes.html | 2 +-
docs/how_to/extend_tvm/sg_execution_times.html | 10 +-
docs/how_to/extend_tvm/use_pass_instrument.html | 16 +-
docs/how_to/optimize_operators/opt_conv_cuda.html | 2 +-
.../optimize_operators/opt_conv_tensorcore.html | 2 +-
docs/how_to/optimize_operators/opt_gemm.html | 16 +-
.../optimize_operators/sg_execution_times.html | 8 +-
.../sg_execution_times.html | 14 +-
.../tune_conv2d_layer_cuda.html | 818 +++--
.../tune_with_autoscheduler/tune_network_cuda.html | 2 +-
.../tune_with_autoscheduler/tune_network_x86.html | 4 +-
.../tune_with_autoscheduler/tune_sparse_x86.html | 132 +-
.../tune_with_autotvm/sg_execution_times.html | 12 +-
.../how_to/tune_with_autotvm/tune_conv2d_cuda.html | 34 +-
docs/how_to/work_with_microtvm/micro_autotune.html | 16 +-
.../work_with_microtvm/sg_execution_times.html | 12 +-
.../how_to/work_with_relay/sg_execution_times.html | 8 +-
.../work_with_schedules/sg_execution_times.html | 18 +-
docs/how_to/work_with_schedules/tensorize.html | 2 +-
docs/reference/api/python/auto_scheduler.html | 4 +-
.../api/typedoc/classes/bytestreamreader.html | 12 +-
.../api/typedoc/classes/cachedcallstack.html | 34 +-
docs/reference/api/typedoc/classes/dldatatype.html | 12 +-
docs/reference/api/typedoc/classes/dldevice.html | 10 +-
.../reference/api/typedoc/classes/environment.html | 12 +-
docs/reference/api/typedoc/classes/ffilibrary.html | 20 +-
.../api/typedoc/classes/graphexecutor.html | 16 +-
docs/reference/api/typedoc/classes/instance.html | 40 +-
docs/reference/api/typedoc/classes/memory.html | 34 +-
docs/reference/api/typedoc/classes/module.html | 10 +-
docs/reference/api/typedoc/classes/ndarray.html | 22 +-
.../api/typedoc/classes/packedfunccell.html | 6 +-
docs/reference/api/typedoc/classes/rpcserver.html | 14 +-
docs/reference/api/typedoc/classes/scalar.html | 6 +-
.../api/typedoc/classes/webgpucontext.html | 12 +-
docs/reference/api/typedoc/enums/argtypecode.html | 30 +-
.../api/typedoc/enums/aynccallbackcode.html | 4 +-
.../api/typedoc/enums/dldatatypecode.html | 8 +-
.../api/typedoc/enums/rpcserverstate.html | 12 +-
docs/reference/api/typedoc/enums/sizeof.html | 18 +-
docs/reference/api/typedoc/index.html | 112 +-
.../api/typedoc/interfaces/disposable.html | 2 +-
.../api/typedoc/interfaces/functioninfo.html | 6 +-
.../api/typedoc/interfaces/libraryprovider.html | 4 +-
docs/searchindex.js | 2 +-
.../vta/tutorials/autotvm/sg_execution_times.html | 6 +-
.../tutorials/frontend/deploy_classification.html | 2 +-
.../vta/tutorials/frontend/deploy_detection.html | 2 +-
.../vta/tutorials/frontend/sg_execution_times.html | 6 +-
.../vta/tutorials/optimize/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/sg_execution_times.html | 6 +-
docs/tutorial/auto_scheduler_matmul_x86.html | 2 +-
docs/tutorial/autotvm_relay_x86.html | 177 +-
docs/tutorial/cross_compilation_and_rpc.html | 2 +-
docs/tutorial/intro_topi.html | 2 +-
docs/tutorial/sg_execution_times.html | 26 +-
docs/tutorial/tensor_expr_get_started.html | 41 +-
115 files changed, 1831 insertions(+), 5308 deletions(-)
diff --git a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
index 896c12eca..cc8c6070f 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -98,7 +98,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip043cc264-4629-4bfd-9c1c-16a85ae75591 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip3c9c1e6c-31ef-4005-a713-1d77ab7fb756 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
diff --git a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
index 34fbc2d1b..05e642886 100644
--- a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
@@ -100,7 +100,7 @@ Load a pretrained OneFlow model and save model
.. code-block:: none
Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
-
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4%|3 | 1.58M/41.5M [00:38<13:00, 53.6kB/s]
4%|3 | 1.59M/41.5M [00:38<10:44, 64.9kB/s]
4%|3 | 1.60M/41.5M [00:38<11:40, 59.7kB/s]
4%|3 | 1.62M/41.5M [00:38<10:01, 69.5kB/s]
4%|3 | 1.62M/41.5M [00:38<11:04, 62.9kB/s]
4%|3 | 1.64M/41.5M [00:38<09:40, 72.0kB/s]
4%|3 | 1.66M/41.5M [00:39<09:29, 73.3kB/s]
4%|4 | 1.66M/41.5M [00:39<12:53, 54.0kB/s]
4%|4 | 1.69M/41.5M [00:39<09:43, 71.5kB/s]
4%|4 | 1.70M/41.5M [00:39<10:38, 65.3kB/s]
4%|4 | 1.70M/41.5M [00:40<11:29, 60.5kB/s]
4%|4 | 1.72M/41.5M [00:40<09:58, 69.6kB/s]
4%|4 | 1.73M/41.5M [00:40<09:05, 76.4kB/s]
4%|4 | 1.75M/41.5M [00:40<08:32, 81.3kB/s]
4%|4 | 1.77M/41.5M [00:41<12:55, 53.7kB/s]
4%|4 | 1.79M/41.5M [00:41<09:40, 71.7kB/s]
4%|4 | 1.80M/41.5M [00:41<11:06, 62.5kB/s]
4%|4 | 1.81M/41.5M [00:41<11:42, 59.2kB/s]
4%|4 | 1.83M/41.5M [00:42<10:19, 67.2kB/s]
4%|4 | 1.84M/41.5M [00:42<11:09, 62.1kB/s]
4%|4 | 1.85M/41.5M [00:42<09:50, 70.4kB/s]
4%|4 | 1.86M/41.5M [00:42<10:49, 64.0kB/s]
5%|4 | 1.88M/41.5M [00:42<09:34, 72.3kB/s]
5%|4 | 1.88M/41.5M [00:43<13:43, 50.4kB/s]
5%|4 | 1.90M/41.5M [00:43<11:22, 60.8kB/s]
5%|4 | 1.91M/41.5M [00:43<12:05, 57.2kB/s]
5%|4 | 1.91M/41.5M [00:43<12:42, 54.4kB/s]
5%|4 | 1.92M/41.5M
[00:43<13:12, 52.3kB/s]
5%|4 | 1.93M/41.5M [00:44<17:27, 39.6kB/s]
5%|4 | 1.95M/41.5M [00:44<13:08, 52.6kB/s]
5%|4 | 1.95M/41.5M [00:44<13:31, 51.1kB/s]
5%|4 | 1.96M/41.5M [00:44<17:31, 39.4kB/s]
5%|4 | 1.98M/41.5M [00:44<13:16, 52.0kB/s]
5%|4 | 1.98M/41.5M [00:45<13:36, 50.7kB/s]
5%|4 | 1.99M/41.5M [00:45<13:53, 49.7kB/s]
5%|4 | 2.00M/41.5M [00:45<14:06, 48.9kB/s]
5%|4 | 2.01M/41.5M [00:45<14:16, 48.3kB/s]
5%|4 | 2.02M/41.5M [00:45<14:23, 47.9kB/s]
5%|4 | 2.03M/41.5M [00:46<11:16, 61.2kB/s]
5%|4 | 2.04M/41.5M [00:46<15:38, 44.1kB/s]
5%|4 | 2.05M/41.5M [00:46<15:15, 45.2kB/s]
5%|4 | 2.06M/41.5M [00:46<15:07, 45.6kB/s]
5%|4 | 2.07M/41.5M [00:47<15:01, 45.9kB/s]
5%|5 | 2.08M/41.5M [00:47<14:56, 46.1kB/s]
5%|5 | 2.09M/41.5M [00:47<18:49, 36.6kB/s]
5%|5 | 2.09M/41.5M [00:47<21:45, 31.6kB/s]
5%|5 | 2.11M/41.5M [00:48<18:37, 37.0kB/s]
5%|5 | 2.12M/41.5M [00:48<17:40, 38.9kB/s]
5%|5 | 2.12M/41.5M [00:48<16:54, 40.7kB/s]
5%|5 | 2.13M/41.5M [00:48<16:18, 42.2kB/s]
5%|5 | 2.14M/41.5M [00:48<15:51, 43.4kB/s]
5%|5 | 2.15M/41.5M [00:49<15:31, 44.3kB/s]
5%|5 | 2.16M/41.5M [00:49<15:16, 45.0kB/s]
5%|5 | 2.16M/41.5M [00:49<19:22, 35.5kB/s]
5%|5 | 2.18M/41.5M [00:49<13:55, 49.4kB/s]
5%|5 | 2.19M/41.5M [00:50<14:05, 48.7kB/s]
5%|5 | 2.20M/41.5M [00:50<18:02, 38.1kB/s]
5%|5 | 2.21M/41.5M [00:50<16:35, 41.4kB/s]
5%|5 | 2.22M/41.5M [00:51<19:33, 35.1kB/s]
5%|5 | 2.23M/41.5M [00:51<17:34, 39.0kB/s]
5%|5 | 2.24M/41.5M [00:51<20:10, 34.0kB/s]
5%|5 | 2.25M/41.5M [00:51<18:50, 36.4kB/s]
5%|5 | 2.26M/41.5
M [00:52<21:30, 31.9kB/s]
5%|5 | 2.27M/41.5M [00:52<19:39, 34.9kB/s]
5%|5 | 2.27M/41.5M [00:52<18:15, 37.5kB/s]
5%|5 | 2.28M/41.5M [00:52<17:13, 39.8kB/s]
6%|5 | 2.29M/41.5M [00:53<16:28, 41.6kB/s]
6%|5 | 2.30M/41.5M [00:53<15:55, 43.0kB/s]
6%|5 | 2.30M/41.5M [00:53<19:50, 34.5kB/s]
6%|5 | 2.32M/41.5M [00:53<17:26, 39.2kB/s]
6%|5 | 2.33M/41.5M [00:54<31:06, 22.0kB/s]
6%|5 | 2.34M/41.5M [00:54<26:48, 25.5kB/s]
6%|5 | 2.34M/41.5M [00:55<39:19, 17.4kB/s]
6%|5 | 2.35M/41.5M [00:55<32:25, 21.1kB/s]
6%|5 | 2.36M/41.5M [00:56<31:29, 21.7kB/s]
6%|5 | 2.37M/41.5M [00:56<26:35, 25.7kB/s]
6%|5 | 2.38M/41.5M [00:56<27:21, 25.0kB/s]
6%|5 | 2.38M/41.5M [00:57<23:35, 29.0kB/s]
6%|5 | 2.39M/41.5M [00:57<20:54, 32.7kB/s]
6%|5 | 2.40M/41.5M [00:57<23:21, 29.2kB/s]
6%|5 | 2.41M/41.5M [00:57<20:44, 32.9kB/s]
6%|5 | 2.41M/41.5M [00:58<23:14, 29.4kB/s]
6%|5 | 2.42M/41.5M [00:58<20:38, 33.1kB/s]
6%|5 | 2.43M/41.5M [00:58<18:49, 36.3kB/s]
6%|5 | 2.45M/41.5M [00:58<13:29, 50.5kB/s]
6%|5 | 2.45M/41.5M [00:58<13:45, 49.6kB/s]
6%|5 | 2.46M/41.5M [00:58<13:58, 48.8kB/s]
6%|5 | 2.48M/41.5M [00:59<14:12, 48.0kB/s]
6%|6 | 2.49M/41.5M [00:59<11:34, 58.9kB/s]
6%|6 | 2.50M/41.5M [00:59<12:12, 55.8kB/s]
6%|6 | 2.51M/41.5M [00:59<12:44, 53.4kB/s]
6%|6 | 2.52M/41.5M [01:00<13:11, 51.6kB/s]
6%|6 | 2.52M/41.5M [01:00<18:19, 37.2kB/s]
6%|6 | 2.53M/41.5M [01:00<17:16, 39.4kB/s]
6%|6 | 2.54M/41.5M [01:00<16:30, 41.2kB/s]
6%|6 | 2.55M/41.5M [01:00<13:33, 50.2kB/s]
6%|6 | 2.56M/41.5M [01:01<13:47, 49.4kB/s]
6%|6 | 2.57M/41.
5M [01:01<12:37, 53.9kB/s]
6%|6 | 2.58M/41.5M [01:01<13:07, 51.8kB/s]
6%|6 | 2.59M/41.5M [01:01<13:30, 50.3kB/s]
6%|6 | 2.59M/41.5M [01:01<17:53, 38.0kB/s]
6%|6 | 2.61M/41.5M [01:02<16:24, 41.4kB/s]
6%|6 | 2.62M/41.5M [01:02<15:56, 42.6kB/s]
6%|6 | 2.62M/41.5M [01:02<15:34, 43.6kB/s]
6%|6 | 2.63M/41.5M [01:03<23:03, 29.4kB/s]
6%|6 | 2.64M/41.5M [01:03<20:40, 32.8kB/s]
6%|6 | 2.65M/41.5M [01:03<27:08, 25.0kB/s]
6%|6 | 2.66M/41.5M [01:04<21:27, 31.6kB/s]
6%|6 | 2.67M/41.5M [01:04<23:16, 29.1kB/s]
6%|6 | 2.68M/41.5M [01:04<24:43, 27.4kB/s]
6%|6 | 2.69M/41.5M [01:05<25:51, 26.2kB/s]
6%|6 | 2.70M/41.5M [01:05<30:43, 22.1kB/s]
7%|6 | 2.70M/41.5M [01:06<26:06, 26.0kB/s]
7%|6 | 2.71M/41.5M [01:06<23:44, 28.5kB/s]
7%|6 | 2.72M/41.5M [01:06<24:14, 28.0kB/s]
7%|6 | 2.73M/41.5M [01:06<22:22, 30.3kB/s]
7%|6 | 2.73M/41.5M [01:06<20:01, 33.8kB/s]
7%|6 | 2.74M/41.5M [01:07<18:22, 36.9kB/s]
7%|6 | 2.75M/41.5M [01:07<16:09, 41.9kB/s]
7%|6 | 2.76M/41.5M [01:07<15:38, 43.3kB/s]
7%|6 | 2.77M/41.5M [01:07<15:17, 44.3kB/s]
7%|6 | 2.78M/41.5M [01:07<12:21, 54.7kB/s]
7%|6 | 2.79M/41.5M [01:07<12:00, 56.3kB/s]
7%|6 | 2.80M/41.5M [01:08<12:38, 53.5kB/s]
7%|6 | 2.81M/41.5M [01:08<10:19, 65.5kB/s]
7%|6 | 2.82M/41.5M [01:08<12:05, 55.9kB/s]
7%|6 | 2.84M/41.5M [01:08<09:27, 71.4kB/s]
7%|6 | 2.85M/41.5M [01:08<08:38, 78.2kB/s]
7%|6 | 2.87M/41.5M [01:09<10:36, 63.6kB/s]
7%|6 | 2.88M/41.5M [01:09<09:29, 71.1kB/s]
7%|6 | 2.89M/41.5M [01:09<14:07, 47.8kB/s]
7%|7 | 2.91M/41.5M [01:10<13:19, 50.6kB/s]
7%|7 | 2.92M/41
.5M [01:10<13:40, 49.3kB/s]
7%|7 | 2.93M/41.5M [01:10<13:48, 48.8kB/s]
7%|7 | 2.94M/41.5M [01:10<13:55, 48.4kB/s]
7%|7 | 2.95M/41.5M [01:11<20:48, 32.4kB/s]
7%|7 | 2.96M/41.5M [01:11<15:19, 43.9kB/s]
7%|7 | 2.97M/41.5M [01:11<18:18, 36.8kB/s]
7%|7 | 2.98M/41.5M [01:11<17:21, 38.8kB/s]
7%|7 | 2.98M/41.5M [01:12<23:57, 28.1kB/s]
7%|7 | 2.99M/41.5M [01:12<21:22, 31.5kB/s]
7%|7 | 3.00M/41.5M [01:12<19:25, 34.6kB/s]
7%|7 | 3.01M/41.5M [01:12<17:59, 37.4kB/s]
7%|7 | 3.02M/41.5M [01:13<16:55, 39.7kB/s]
7%|7 | 3.02M/41.5M [01:13<16:10, 41.6kB/s]
7%|7 | 3.03M/41.5M [01:13<15:38, 43.0kB/s]
7%|7 | 3.04M/41.5M [01:14<23:45, 28.3kB/s]
7%|7 | 3.05M/41.5M [01:14<20:57, 32.1kB/s]
7%|7 | 3.05M/41.5M [01:14<18:58, 35.4kB/s]
7%|7 | 3.06M/41.5M [01:14<21:52, 30.7kB/s]
7%|7 | 3.07M/41.5M [01:14<19:37, 34.2kB/s]
7%|7 | 3.08M/41.5M [01:15<18:01, 37.2kB/s]
7%|7 | 3.09M/41.5M [01:15<21:12, 31.6kB/s]
7%|7 | 3.09M/41.5M [01:15<23:26, 28.6kB/s]
7%|7 | 3.10M/41.5M [01:16<26:10, 25.6kB/s]
7%|7 | 3.11M/41.5M [01:16<22:37, 29.6kB/s]
8%|7 | 3.12M/41.5M [01:16<23:16, 28.8kB/s]
8%|7 | 3.12M/41.5M [01:16<24:09, 27.7kB/s]
8%|7 | 3.13M/41.5M [01:17<21:54, 30.6kB/s]
8%|7 | 3.14M/41.5M [01:17<19:37, 34.2kB/s]
8%|7 | 3.15M/41.5M [01:17<18:01, 37.2kB/s]
8%|7 | 3.16M/41.5M [01:17<16:12, 41.4kB/s]
8%|7 | 3.16M/41.5M [01:17<15:37, 42.9kB/s]
8%|7 | 3.17M/41.5M [01:18<19:30, 34.3kB/s]
8%|7 | 3.18M/41.5M [01:18<17:56, 37.3kB/s]
8%|7 | 3.19M/41.5M [01:18<21:07, 31.7kB/s]
8%|7 | 3.20M/41.5M [01:19<23:21, 28.7kB/s]
8%|7 | 3.20M/4
1.5M [01:19<26:02, 25.7kB/s]
8%|7 | 3.21M/41.5M [01:19<22:30, 29.7kB/s]
8%|7 | 3.22M/41.5M [01:20<28:35, 23.4kB/s]
8%|7 | 3.23M/41.5M [01:20<29:31, 22.6kB/s]
8%|7 | 3.23M/41.5M [01:21<35:00, 19.1kB/s]
8%|7 | 3.24M/41.5M [01:21<33:03, 20.2kB/s]
8%|7 | 3.25M/41.5M [01:21<27:24, 24.4kB/s]
8%|7 | 3.26M/41.5M [01:22<27:44, 24.1kB/s]
8%|7 | 3.27M/41.5M [01:22<23:41, 28.2kB/s]
8%|7 | 3.27M/41.5M [01:22<20:51, 32.0kB/s]
8%|7 | 3.28M/41.5M [01:22<18:52, 35.4kB/s]
8%|7 | 3.30M/41.5M [01:22<13:26, 49.7kB/s]
8%|7 | 3.30M/41.5M [01:22<13:38, 48.9kB/s]
8%|7 | 3.31M/41.5M [01:23<13:47, 48.4kB/s]
8%|8 | 3.33M/41.5M [01:23<10:56, 61.0kB/s]
8%|8 | 3.34M/41.5M [01:23<15:03, 44.3kB/s]
8%|8 | 3.36M/41.5M [01:23<09:53, 67.4kB/s]
8%|8 | 3.37M/41.5M [01:23<10:43, 62.2kB/s]
8%|8 | 3.38M/41.5M [01:24<12:13, 54.5kB/s]
8%|8 | 3.39M/41.5M [01:24<09:36, 69.4kB/s]
8%|8 | 3.40M/41.5M [01:24<10:35, 62.9kB/s]
8%|8 | 3.41M/41.5M [01:24<14:45, 45.1kB/s]
8%|8 | 3.42M/41.5M [01:25<11:40, 56.9kB/s]
8%|8 | 3.43M/41.5M [01:25<15:23, 43.2kB/s]
8%|8 | 3.45M/41.5M [01:25<14:50, 44.8kB/s]
8%|8 | 3.45M/41.5M [01:25<14:41, 45.2kB/s]
8%|8 | 3.46M/41.5M [01:26<14:34, 45.6kB/s]
8%|8 | 3.47M/41.5M [01:26<14:28, 45.9kB/s]
8%|8 | 3.48M/41.5M [01:26<21:54, 30.3kB/s]
8%|8 | 3.48M/41.5M [01:26<19:47, 33.6kB/s]
8%|8 | 3.49M/41.5M [01:27<18:11, 36.5kB/s]
8%|8 | 3.50M/41.5M [01:27<18:52, 35.2kB/s]
8%|8 | 3.51M/41.5M [01:27<17:29, 37.9kB/s]
8%|8 | 3.52M/41.5M [01:27<16:31, 40.2kB/s]
8%|8 | 3.52M/41.5M [01:27<15:49, 41.9kB/s]
9%|8 | 3.53M/
41.5M [01:28<15:19, 43.3kB/s]
9%|8 | 3.54M/41.5M [01:28<14:58, 44.3kB/s]
9%|8 | 3.55M/41.5M [01:28<14:35, 45.4kB/s]
9%|8 | 3.57M/41.5M [01:28<13:09, 50.4kB/s]
9%|8 | 3.58M/41.5M [01:29<13:22, 49.5kB/s]
9%|8 | 3.59M/41.5M [01:29<13:33, 48.9kB/s]
9%|8 | 3.60M/41.5M [01:29<13:47, 48.0kB/s]
9%|8 | 3.61M/41.5M [01:29<13:51, 47.8kB/s]
9%|8 | 3.62M/41.5M [01:29<13:55, 47.5kB/s]
9%|8 | 3.62M/41.5M [01:30<17:36, 37.6kB/s]
9%|8 | 3.63M/41.5M [01:30<16:40, 39.7kB/s]
9%|8 | 3.64M/41.5M [01:30<15:57, 41.5kB/s]
9%|8 | 3.65M/41.5M [01:30<15:25, 42.9kB/s]
9%|8 | 3.66M/41.5M [01:30<15:02, 43.9kB/s]
9%|8 | 3.66M/41.5M [01:31<14:46, 44.8kB/s]
9%|8 | 3.67M/41.5M [01:31<14:34, 45.4kB/s]
9%|8 | 3.68M/41.5M [01:31<14:26, 45.8kB/s]
9%|8 | 3.69M/41.5M [01:31<18:31, 35.7kB/s
]
9%|8 | 3.70M/41.5M [01:31<13:14, 49.9kB/s]
9%|8 | 3.71M/41.5M [01:32<13:27, 49.1kB/s]
9%|8 | 3.72M/41.5M [01:32<13:36, 48.5kB/s]
9%|8 | 3.73M/41.5M [01:32<13:44, 48.0kB/s]
9%|9 | 3.74M/41.5M [01:32<13:52, 47.5kB/s]
9%|9 | 3.75M/41.5M [01:33<16:05, 41.0kB/s]
9%|9 | 3.77M/41.5M [01:33<16:16, 40.5kB/s]
9%|9 | 3.78M/41.5M [01:33<15:27, 42.6kB/s]
9%|9 | 3.79M/41.5M [01:34<15:10, 43.4kB/s]
9%|9 | 3.80M/41.5M [01:34<14:54, 44.2kB/s]
9%|9 | 3.80M/41.5M [01:34<14:42, 44.8kB/s]
9%|9 | 3.81M/41.5M [01:34<14:31, 45.3kB/s]
9%|9 | 3.82M/41.5M [01:34<14:23, 45.7kB/s]
9%|9 | 3.83M/41.5M [01:34<14:17, 46.0kB/s]
9%|9 | 3.84M/41.5M [01:35<14:13, 46.3kB/s]
9%|9 | 3.85M/41.5M [01:35<14:08, 46.5kB/s]
9%|9 | 3.87M/41.5M [01:35<11:20, 57.9kB/s]
9%|9 | 3.88M
/41.5M [01:36<12:18, 53.4kB/s]
9%|9 | 3.90M/41.5M [01:36<10:30, 62.5kB/s]
9%|9 | 3.91M/41.5M [01:36<11:11, 58.7kB/s]
9%|9 | 3.91M/41.5M [01:36<11:48, 55.6kB/s]
9%|9 | 3.92M/41.5M [01:36<15:38, 42.0kB/s]
9%|9 | 3.94M/41.5M [01:37<14:58, 43.8kB/s]
10%|9 | 3.95M/41.5M [01:37<17:53, 36.7kB/s]
10%|9 | 3.95M/41.5M [01:37<20:20, 32.3kB/s]
10%|9 | 3.96M/41.5M [01:38<19:33, 33.5kB/s]
10%|9 | 3.97M/41.5M [01:38<25:34, 25.6kB/s]
10%|9 | 3.98M/41.5M [01:39<34:46, 18.9kB/s]
10%|9 | 3.98M/41.5M [01:39<36:48, 17.8kB/s]
10%|9 | 3.99M/41.5M [01:40<34:15, 19.1kB/s]
10%|9 | 4.00M/41.5M [01:40<32:24, 20.2kB/s]
10%|9 | 4.01M/41.5M [01:40<31:05, 21.1kB/s]
10%|9 | 4.02M/41.5M [01:41<26:02, 25.1kB/s]
10%|9 | 4.02M/41.5M [01:41<26:36, 24.6kB/s]
10%|9 | 4.03M/41.5M [01:41<22:50, 28.7kB/
s]
10%|9 | 4.04M/41.5M [01:41<20:11, 32.4kB/s]
10%|9 | 4.05M/41.5M [01:42<18:19, 35.7kB/s]
10%|9 | 4.05M/41.5M [01:42<18:03, 36.2kB/s]
10%|9 | 4.06M/41.5M [01:42<16:49, 38.9kB/s]
10%|9 | 4.07M/41.5M [01:42<14:55, 43.8kB/s]
10%|9 | 4.08M/41.5M [01:42<14:37, 44.7kB/s]
10%|9 | 4.09M/41.5M [01:43<18:36, 35.1kB/s]
10%|9 | 4.09M/41.5M [01:43<15:32, 42.1kB/s]
10%|9 | 4.11M/41.5M [01:43<16:05, 40.6kB/s]
10%|9 | 4.12M/41.5M [01:43<15:33, 42.0kB/s]
10%|9 | 4.12M/41.5M [01:44<18:46, 34.8kB/s]
10%|9 | 4.13M/41.5M [01:44<17:27, 37.4kB/s]
10%|9 | 4.14M/41.5M [01:44<16:27, 39.6kB/s]
10%|9 | 4.15M/41.5M [01:44<15:44, 41.5kB/s]
10%|# | 4.16M/41.5M [01:44<11:47, 55.3kB/s]
10%|# | 4.17M/41.5M [01:45<12:18, 53.0kB/s]
10%|# | 4.19M/41.5M [01:45<12:57, 50.3kB/s]
10%|# | 4.20
M/41.5M [01:45<10:44, 60.7kB/s]
10%|# | 4.21M/41.5M [01:46<20:06, 32.4kB/s]
10%|# | 4.23M/41.5M [01:46<15:10, 42.9kB/s]
10%|# | 4.23M/41.5M [01:46<14:54, 43.7kB/s]
10%|# | 4.24M/41.5M [01:46<14:40, 44.4kB/s]
10%|# | 4.25M/41.5M [01:47<17:55, 36.3kB/s]
10%|# | 4.26M/41.5M [01:47<20:30, 31.7kB/s]
10%|# | 4.27M/41.5M [01:47<17:39, 36.8kB/s]
10%|# | 4.29M/41.5M [01:48<14:11, 45.8kB/s]
10%|# | 4.30M/41.5M [01:48<14:07, 46.0kB/s]
10%|# | 4.30M/41.5M [01:48<14:03, 46.2kB/s]
10%|# | 4.31M/41.5M [01:48<17:28, 37.2kB/s]
10%|# | 4.32M/41.5M [01:48<15:44, 41.2kB/s]
10%|# | 4.33M/41.5M [01:49<15:14, 42.6kB/s]
10%|# | 4.34M/41.5M [01:49<14:50, 43.7kB/s]
10%|# | 4.34M/41.5M [01:49<14:33, 44.6kB/s]
10%|# | 4.35M/41.5M [01:49<14:21, 45.2kB/s]
11%|# | 4.36M/41.5M [01:49<14:12, 45.7kB
/s]
11%|# | 4.37M/41.5M [01:50<22:16, 29.1kB/s]
11%|# | 4.38M/41.5M [01:50<15:14, 42.5kB/s]
11%|# | 4.39M/41.5M [01:50<14:53, 43.5kB/s]
11%|# | 4.40M/41.5M [01:50<14:37, 44.3kB/s]
11%|# | 4.41M/41.5M [01:50<14:24, 45.0kB/s]
11%|# | 4.41M/41.5M [01:51<14:14, 45.5kB/s]
11%|# | 4.42M/41.5M [01:51<18:03, 35.9kB/s]
11%|# | 4.44M/41.5M [01:52<19:15, 33.6kB/s]
11%|# | 4.45M/41.5M [01:52<17:55, 36.1kB/s]
11%|# | 4.45M/41.5M [01:52<16:52, 38.4kB/s]
11%|# | 4.46M/41.5M [01:52<19:45, 32.8kB/s]
11%|# | 4.47M/41.5M [01:52<18:06, 35.7kB/s]
11%|# | 4.48M/41.5M [01:53<16:53, 38.3kB/s]
11%|# | 4.49M/41.5M [01:53<12:24, 52.1kB/s]
11%|# | 4.50M/41.5M [01:53<12:44, 50.7kB/s]
11%|# | 4.51M/41.5M [01:53<13:00, 49.7kB/s]
11%|# | 4.52M/41.5M [01:53<10:25, 62.0kB/s]
11%|# | 4.5
3M/41.5M [01:53<11:11, 57.7kB/s]
11%|# | 4.55M/41.5M [01:54<12:14, 52.7kB/s]
11%|# | 4.56M/41.5M [01:54<10:17, 62.7kB/s]
11%|#1 | 4.57M/41.5M [01:54<13:50, 46.6kB/s]
11%|#1 | 4.59M/41.5M [01:54<09:29, 67.9kB/s]
11%|#1 | 4.60M/41.5M [01:55<10:16, 62.7kB/s]
11%|#1 | 4.61M/41.5M [01:55<10:59, 58.6kB/s]
11%|#1 | 4.62M/41.5M [01:55<11:37, 55.5kB/s]
11%|#1 | 4.62M/41.5M [01:55<12:08, 53.1kB/s]
11%|#1 | 4.63M/41.5M [01:55<12:33, 51.3kB/s]
11%|#1 | 4.64M/41.5M [01:56<16:35, 38.8kB/s]
11%|#1 | 4.66M/41.5M [01:56<15:20, 41.9kB/s]
11%|#1 | 4.66M/41.5M [01:56<14:57, 43.0kB/s]
11%|#1 | 4.67M/41.5M [01:56<14:38, 43.9kB/s]
11%|#1 | 4.68M/41.5M [01:57<18:02, 35.6kB/s]
11%|#1 | 4.69M/41.5M [01:57<20:39, 31.1kB/s]
11%|#1 | 4.70M/41.5M [01:57<22:34, 28.5kB/s]
11%|#1 | 4.71M/41.5M [01:58<18:36, 34.5k
B/s]
11%|#1 | 4.72M/41.5M [01:58<20:44, 31.0kB/s]
11%|#1 | 4.73M/41.5M [01:58<18:55, 33.9kB/s]
11%|#1 | 4.73M/41.5M [01:59<17:31, 36.7kB/s]
11%|#1 | 4.74M/41.5M [01:59<16:27, 39.0kB/s]
11%|#1 | 4.76M/41.5M [01:59<12:13, 52.5kB/s]
11%|#1 | 4.77M/41.5M [01:59<12:34, 51.1kB/s]
12%|#1 | 4.77M/41.5M [01:59<12:51, 49.9kB/s]
12%|#1 | 4.78M/41.5M [01:59<13:04, 49.1kB/s]
12%|#1 | 4.79M/41.5M [02:00<13:14, 48.5kB/s]
12%|#1 | 4.80M/41.5M [02:00<10:25, 61.5kB/s]
12%|#1 | 4.81M/41.5M [02:00<11:11, 57.3kB/s]
12%|#1 | 4.82M/41.5M [02:00<15:18, 41.9kB/s]
12%|#1 | 4.84M/41.5M [02:01<12:04, 53.1kB/s]
12%|#1 | 4.85M/41.5M [02:01<13:03, 49.0kB/s]
12%|#1 | 4.86M/41.5M [02:01<13:11, 48.5kB/s]
12%|#1 | 4.87M/41.5M [02:01<13:18, 48.1kB/s]
12%|#1 | 4.88M/41.5M [02:01<13:23, 47.8kB/s]
12%|#1 | 4.
88M/41.5M [02:02<13:27, 47.5kB/s]
12%|#1 | 4.89M/41.5M [02:02<13:30, 47.3kB/s]
12%|#1 | 4.90M/41.5M [02:02<13:32, 47.2kB/s]
12%|#1 | 4.91M/41.5M [02:02<17:30, 36.5kB/s]
12%|#1 | 4.93M/41.5M [02:03<15:21, 41.6kB/s]
12%|#1 | 4.94M/41.5M [02:03<17:51, 35.8kB/s]
12%|#1 | 4.95M/41.5M [02:03<17:39, 36.2kB/s]
12%|#1 | 4.95M/41.5M [02:03<16:39, 38.3kB/s]
12%|#1 | 4.96M/41.5M [02:04<19:24, 32.9kB/s]
12%|#1 | 4.97M/41.5M [02:04<21:32, 29.6kB/s]
12%|#1 | 4.98M/41.5M [02:05<26:56, 23.7kB/s]
12%|#2 | 4.99M/41.5M [02:05<21:02, 30.3kB/s]
12%|#2 | 5.00M/41.5M [02:05<19:15, 33.1kB/s]
12%|#2 | 5.01M/41.5M [02:06<21:17, 30.0kB/s]
12%|#2 | 5.02M/41.5M [02:06<19:13, 33.2kB/s]
12%|#2 | 5.02M/41.5M [02:06<21:26, 29.7kB/s]
12%|#2 | 5.04M/41.5M [02:07<30:25, 20.9kB/s]
12%|#2 | 5.05M/41.5M [02:07<26:23, 24.1
kB/s]
12%|#2 | 5.05M/41.5M [02:08<26:35, 24.0kB/s]
12%|#2 | 5.06M/41.5M [02:08<23:06, 27.5kB/s]
12%|#2 | 5.07M/41.5M [02:08<20:28, 31.1kB/s]
12%|#2 | 5.08M/41.5M [02:09<26:12, 24.3kB/s]
12%|#2 | 5.09M/41.5M [02:09<20:32, 31.0kB/s]
12%|#2 | 5.10M/41.5M [02:09<18:51, 33.7kB/s]
12%|#2 | 5.11M/41.5M [02:09<17:29, 36.3kB/s]
12%|#2 | 5.12M/41.5M [02:09<16:26, 38.7kB/s]
12%|#2 | 5.12M/41.5M [02:10<15:38, 40.6kB/s]
12%|#2 | 5.13M/41.5M [02:10<15:02, 42.2kB/s]
12%|#2 | 5.14M/41.5M [02:10<14:36, 43.5kB/s]
12%|#2 | 5.15M/41.5M [02:10<14:18, 44.4kB/s]
12%|#2 | 5.16M/41.5M [02:11<18:04, 35.1kB/s]
12%|#2 | 5.17M/41.5M [02:11<12:54, 49.2kB/s]
12%|#2 | 5.18M/41.5M [02:11<13:03, 48.6kB/s]
13%|#2 | 5.19M/41.5M [02:11<13:10, 48.1kB/s]
13%|#2 | 5.20M/41.5M [02:11<10:26, 60.7kB/s]
13%|#2 | 5
.21M/41.5M [02:11<11:09, 56.8kB/s]
13%|#2 | 5.22M/41.5M [02:12<11:45, 53.9kB/s]
13%|#2 | 5.23M/41.5M [02:12<15:46, 40.2kB/s]
13%|#2 | 5.24M/41.5M [02:12<11:55, 53.2kB/s]
13%|#2 | 5.25M/41.5M [02:12<15:27, 41.0kB/s]
13%|#2 | 5.27M/41.5M [02:13<14:40, 43.1kB/s]
13%|#2 | 5.27M/41.5M [02:13<14:24, 43.9kB/s]
13%|#2 | 5.28M/41.5M [02:13<17:27, 36.3kB/s]
13%|#2 | 5.29M/41.5M [02:13<16:26, 38.5kB/s]
13%|#2 | 5.30M/41.5M [02:14<15:38, 40.4kB/s]
13%|#2 | 5.30M/41.5M [02:14<22:31, 28.1kB/s]
13%|#2 | 5.32M/41.5M [02:14<15:32, 40.7kB/s]
13%|#2 | 5.33M/41.5M [02:15<18:17, 34.6kB/s]
13%|#2 | 5.34M/41.5M [02:15<17:03, 37.0kB/s]
13%|#2 | 5.34M/41.5M [02:15<19:42, 32.1kB/s]
13%|#2 | 5.35M/41.5M [02:15<17:58, 35.1kB/s]
13%|#2 | 5.36M/41.5M [02:16<16:42, 37.8kB/s]
13%|#2 | 5.37M/41.5M [02:16<15:46, 40.
0kB/s]
13%|#2 | 5.38M/41.5M [02:16<15:05, 41.8kB/s]
13%|#2 | 5.38M/41.5M [02:16<14:36, 43.2kB/s]
13%|#2 | 5.39M/41.5M [02:16<14:16, 44.2kB/s]
13%|#3 | 5.40M/41.5M [02:16<14:01, 45.0kB/s]
13%|#3 | 5.41M/41.5M [02:17<13:51, 45.5kB/s]
13%|#3 | 5.42M/41.5M [02:17<10:34, 59.6kB/s]
13%|#3 | 5.43M/41.5M [02:17<11:16, 55.9kB/s]
13%|#3 | 5.44M/41.5M [02:17<11:50, 53.2kB/s]
13%|#3 | 5.45M/41.5M [02:17<09:39, 65.3kB/s]
13%|#3 | 5.46M/41.5M [02:18<10:32, 59.8kB/s]
13%|#3 | 5.47M/41.5M [02:18<11:15, 55.9kB/s]
13%|#3 | 5.48M/41.5M [02:18<09:21, 67.2kB/s]
13%|#3 | 5.49M/41.5M [02:18<10:17, 61.1kB/s]
13%|#3 | 5.51M/41.5M [02:18<08:52, 70.9kB/s]
13%|#3 | 5.52M/41.5M [02:18<09:52, 63.7kB/s]
13%|#3 | 5.52M/41.5M [02:19<13:55, 45.1kB/s]
13%|#3 | 5.55M/41.5M [02:19<11:24, 55.1kB/s]
13%|#3 |
5.56M/41.5M [02:20<14:45, 42.5kB/s]
13%|#3 | 5.58M/41.5M [02:20<12:11, 51.5kB/s]
13%|#3 | 5.59M/41.5M [02:20<12:24, 50.5kB/s]
13%|#3 | 5.59M/41.5M [02:20<12:36, 49.7kB/s]
14%|#3 | 5.60M/41.5M [02:20<12:47, 49.0kB/s]
14%|#3 | 5.61M/41.5M [02:21<12:56, 48.5kB/s]
14%|#3 | 5.62M/41.5M [02:21<13:02, 48.0kB/s]
14%|#3 | 5.63M/41.5M [02:21<10:19, 60.7kB/s]
14%|#3 | 5.64M/41.5M [02:21<14:10, 44.2kB/s]
14%|#3 | 5.66M/41.5M [02:22<14:31, 43.1kB/s]
14%|#3 | 5.66M/41.5M [02:22<16:28, 38.0kB/s]
14%|#3 | 5.67M/41.5M [02:22<15:43, 39.8kB/s]
14%|#3 | 5.68M/41.5M [02:22<15:06, 41.4kB/s]
14%|#3 | 5.69M/41.5M [02:22<14:38, 42.7kB/s]
14%|#3 | 5.70M/41.5M [02:23<14:17, 43.8kB/s]
14%|#3 | 5.70M/41.5M [02:23<14:00, 44.6kB/s]
14%|#3 | 5.71M/41.5M [02:23<13:49, 45.2kB/s]
14%|#3 | 5.72M/41.5M [02:23<13:40, 45
.7kB/s]
14%|#3 | 5.73M/41.5M [02:23<13:34, 46.0kB/s]
14%|#3 | 5.74M/41.5M [02:24<16:30, 37.9kB/s]
14%|#3 | 5.76M/41.5M [02:24<15:15, 40.9kB/s]
14%|#3 | 5.78M/41.5M [02:24<10:17, 60.6kB/s]
14%|#3 | 5.79M/41.5M [02:25<13:13, 47.2kB/s]
14%|#3 | 5.80M/41.5M [02:25<13:14, 47.1kB/s]
14%|#3 | 5.80M/41.5M [02:25<13:15, 47.1kB/s]
14%|#4 | 5.81M/41.5M [02:25<13:15, 47.0kB/s]
14%|#4 | 5.82M/41.5M [02:25<13:16, 47.0kB/s]
14%|#4 | 5.83M/41.5M [02:26<13:16, 46.9kB/s]
14%|#4 | 5.84M/41.5M [02:26<13:16, 46.9kB/s]
14%|#4 | 5.84M/41.5M [02:26<13:16, 46.9kB/s]
14%|#4 | 5.85M/41.5M [02:26<17:07, 36.4kB/s]
14%|#4 | 5.87M/41.5M [02:27<15:22, 40.5kB/s]
14%|#4 | 5.88M/41.5M [02:27<18:06, 34.4kB/s]
14%|#4 | 5.88M/41.5M [02:27<17:41, 35.2kB/s]
14%|#4 | 5.89M/41.5M [02:28<19:12, 32.4kB/s]
14%|#4 |
5.90M/41.5M [02:28<18:26, 33.7kB/s]
14%|#4 | 5.91M/41.5M [02:28<16:58, 36.6kB/s]
14%|#4 | 5.91M/41.5M [02:28<15:54, 39.1kB/s]
14%|#4 | 5.92M/41.5M [02:28<15:07, 41.1kB/s]
14%|#4 | 5.93M/41.5M [02:29<22:24, 27.7kB/s]
14%|#4 | 5.94M/41.5M [02:29<18:43, 33.2kB/s]
14%|#4 | 5.95M/41.5M [02:29<18:04, 34.4kB/s]
14%|#4 | 5.95M/41.5M [02:29<16:37, 37.3kB/s]
14%|#4 | 5.96M/41.5M [02:29<14:38, 42.4kB/s]
14%|#4 | 5.97M/41.5M [02:30<14:14, 43.6kB/s]
14%|#4 | 5.98M/41.5M [02:30<13:56, 44.5kB/s]
14%|#4 | 5.98M/41.5M [02:30<21:39, 28.6kB/s]
14%|#4 | 6.00M/41.5M [02:31<15:26, 40.2kB/s]
14%|#4 | 6.01M/41.5M [02:31<14:53, 41.6kB/s]
14%|#4 | 6.02M/41.5M [02:31<14:27, 42.9kB/s]
15%|#4 | 6.02M/41.5M [02:31<14:06, 43.9kB/s]
15%|#4 | 6.03M/41.5M [02:31<13:51, 44.7kB/s]
15%|#4 | 6.04M/41.5M [02:31<13:40, 4
5.3kB/s]
15%|#4 | 6.05M/41.5M [02:32<13:32, 45.7kB/s]
15%|#4 | 6.05M/41.5M [02:32<17:20, 35.7kB/s]
15%|#4 | 6.07M/41.5M [02:32<12:26, 49.7kB/s]
15%|#4 | 6.08M/41.5M [02:32<12:37, 49.0kB/s]
15%|#4 | 6.09M/41.5M [02:32<12:46, 48.4kB/s]
15%|#4 | 6.10M/41.5M [02:33<10:08, 60.9kB/s]
15%|#4 | 6.11M/41.5M [02:33<13:55, 44.4kB/s]
15%|#4 | 6.12M/41.5M [02:33<17:02, 36.3kB/s]
15%|#4 | 6.13M/41.5M [02:33<12:41, 48.7kB/s]
15%|#4 | 6.14M/41.5M [02:34<15:49, 39.1kB/s]
15%|#4 | 6.16M/41.5M [02:34<15:23, 40.1kB/s]
15%|#4 | 6.16M/41.5M [02:34<14:53, 41.4kB/s]
15%|#4 | 6.17M/41.5M [02:35<17:38, 35.0kB/s]
15%|#4 | 6.18M/41.5M [02:35<16:29, 37.4kB/s]
15%|#4 | 6.19M/41.5M [02:35<15:36, 39.5kB/s]
15%|#4 | 6.20M/41.5M [02:35<18:33, 33.2kB/s]
15%|#4 | 6.20M/41.5M [02:36<20:46, 29.7kB/s]
15%|#4
| 6.22M/41.5M [02:36<17:21, 35.5kB/s]
15%|#5 | 6.23M/41.5M [02:36<13:09, 46.8kB/s]
15%|#5 | 6.24M/41.5M [02:37<13:09, 46.8kB/s]
15%|#5 | 6.25M/41.5M [02:37<13:09, 46.8kB/s]
15%|#5 | 6.26M/41.5M [02:37<13:08, 46.8kB/s]
15%|#5 | 6.27M/41.5M [02:37<16:37, 37.0kB/s]
15%|#5 | 6.28M/41.5M [02:37<12:16, 50.1kB/s]
15%|#5 | 6.29M/41.5M [02:38<15:34, 39.5kB/s]
15%|#5 | 6.30M/41.5M [02:38<18:15, 33.7kB/s]
15%|#5 | 6.31M/41.5M [02:38<16:06, 38.2kB/s]
15%|#5 | 6.32M/41.5M [02:39<15:24, 39.9kB/s]
15%|#5 | 6.33M/41.5M [02:39<14:50, 41.4kB/s]
15%|#5 | 6.34M/41.5M [02:39<14:23, 42.7kB/s]
15%|#5 | 6.34M/41.5M [02:39<14:02, 43.8kB/s]
15%|#5 | 6.35M/41.5M [02:39<13:46, 44.6kB/s]
15%|#5 | 6.36M/41.5M [02:40<17:19, 35.4kB/s]
15%|#5 | 6.38M/41.5M [02:40<13:09, 46.6kB/s]
15%|#5 | 6.38M/41.5M [02:40<13:08,
46.7kB/s]
15%|#5 | 6.39M/41.5M [02:40<13:07, 46.7kB/s]
15%|#5 | 6.40M/41.5M [02:40<13:07, 46.8kB/s]
15%|#5 | 6.41M/41.5M [02:41<13:06, 46.8kB/s]
15%|#5 | 6.41M/41.5M [02:41<14:04, 43.6kB/s]
15%|#5 | 6.43M/41.5M [02:41<12:52, 47.6kB/s]
16%|#5 | 6.44M/41.5M [02:41<12:55, 47.4kB/s]
16%|#5 | 6.45M/41.5M [02:41<12:57, 47.3kB/s]
16%|#5 | 6.46M/41.5M [02:42<10:14, 59.8kB/s]
16%|#5 | 6.47M/41.5M [02:42<10:53, 56.2kB/s]
16%|#5 | 6.48M/41.5M [02:42<11:25, 53.6kB/s]
16%|#5 | 6.48M/41.5M [02:42<10:42, 57.1kB/s]
16%|#5 | 6.50M/41.5M [02:42<09:50, 62.1kB/s]
16%|#5 | 6.51M/41.5M [02:42<10:35, 57.7kB/s]
16%|#5 | 6.52M/41.5M [02:43<08:57, 68.2kB/s]
16%|#5 | 6.53M/41.5M [02:43<08:54, 68.6kB/s]
16%|#5 | 6.54M/41.5M [02:43<10:56, 55.8kB/s]
16%|#5 | 6.55M/41.5M [02:43<10:55, 55.9kB/s]
16%|#5
| 6.57M/41.5M [02:43<09:17, 65.7kB/s]
16%|#5 | 6.58M/41.5M [02:44<10:03, 60.6kB/s]
16%|#5 | 6.59M/41.5M [02:44<10:26, 58.5kB/s]
16%|#5 | 6.60M/41.5M [02:44<08:52, 68.7kB/s]
16%|#5 | 6.62M/41.5M [02:44<08:01, 76.0kB/s]
16%|#5 | 6.62M/41.5M [02:44<09:02, 67.4kB/s]
16%|#6 | 6.64M/41.5M [02:45<08:05, 75.2kB/s]
16%|#6 | 6.66M/41.5M [02:45<07:33, 80.6kB/s]
16%|#6 | 6.67M/41.5M [02:45<09:34, 63.6kB/s]
16%|#6 | 6.69M/41.5M [02:45<08:22, 72.6kB/s]
16%|#6 | 6.70M/41.5M [02:45<07:46, 78.2kB/s]
16%|#6 | 6.72M/41.5M [02:46<07:22, 82.4kB/s]
16%|#6 | 6.73M/41.5M [02:46<09:05, 66.8kB/s]
16%|#6 | 6.75M/41.5M [02:46<08:17, 73.2kB/s]
16%|#6 | 6.77M/41.5M [02:46<07:44, 78.4kB/s]
16%|#6 | 6.78M/41.5M [02:46<07:21, 82.5kB/s]
16%|#6 | 6.80M/41.5M [02:47<07:05, 85.6kB/s]
16%|#6 | 6.81M/41.5M [02:47<13:03,
46.4kB/s]
16%|#6 | 6.84M/41.5M [02:48<09:47, 61.8kB/s]
17%|#6 | 6.87M/41.5M [02:48<11:09, 54.2kB/s]
17%|#6 | 6.88M/41.5M [02:49<13:07, 46.1kB/s]
17%|#6 | 6.89M/41.5M [02:49<13:05, 46.2kB/s]
17%|#6 | 6.90M/41.5M [02:49<15:16, 39.6kB/s]
17%|#6 | 6.91M/41.5M [02:49<14:48, 40.8kB/s]
17%|#6 | 6.91M/41.5M [02:50<17:13, 35.1kB/s]
17%|#6 | 6.93M/41.5M [02:50<18:02, 33.5kB/s]
17%|#6 | 6.94M/41.5M [02:51<28:04, 21.5kB/s]
17%|#6 | 6.95M/41.5M [02:51<24:28, 24.7kB/s]
17%|#6 | 6.95M/41.5M [02:52<24:47, 24.3kB/s]
17%|#6 | 6.96M/41.5M [02:52<28:27, 21.2kB/s]
17%|#6 | 6.97M/41.5M [02:53<27:42, 21.8kB/s]
17%|#6 | 6.98M/41.5M [02:53<27:09, 22.2kB/s]
17%|#6 | 6.98M/41.5M [02:53<26:44, 22.6kB/s]
17%|#6 | 6.99M/41.5M [02:53<22:42, 26.6kB/s]
17%|#6 | 7.00M/41.5M [02:54<27:21, 22.0kB/s]
17%|#6
| 7.01M/41.5M [02:54<26:52, 22.4kB/s]
17%|#6 | 7.02M/41.5M [02:55<22:42, 26.5kB/s]
17%|#6 | 7.02M/41.5M [02:55<19:46, 30.5kB/s]
17%|#6 | 7.03M/41.5M [02:55<25:22, 23.7kB/s]
17%|#6 | 7.04M/41.5M [02:56<25:28, 23.6kB/s]
17%|#6 | 7.05M/41.5M [02:56<21:41, 27.7kB/s]
17%|#7 | 7.05M/41.5M [02:56<27:18, 22.0kB/s]
17%|#7 | 7.07M/41.5M [02:57<23:08, 26.0kB/s]
17%|#7 | 7.08M/41.5M [02:57<26:56, 22.3kB/s]
17%|#7 | 7.09M/41.5M [02:58<26:36, 22.6kB/s]
17%|#7 | 7.09M/41.5M [02:58<22:51, 26.3kB/s]
17%|#7 | 7.10M/41.5M [02:58<23:38, 25.4kB/s]
17%|#7 | 7.11M/41.5M [02:58<22:02, 27.3kB/s]
17%|#7 | 7.12M/41.5M [02:59<33:25, 18.0kB/s]
17%|#7 | 7.13M/41.5M [03:00<23:35, 25.5kB/s]
17%|#7 | 7.14M/41.5M [03:00<21:29, 27.9kB/s]
17%|#7 | 7.15M/41.5M [03:00<21:58, 27.3kB/s]
17%|#7 | 7.16M/41.5M [03:01<26:24
, 22.7kB/s]
17%|#7 | 7.17M/41.5M [03:01<18:52, 31.8kB/s]
17%|#7 | 7.18M/41.5M [03:01<22:12, 27.0kB/s]
17%|#7 | 7.20M/41.5M [03:02<20:58, 28.6kB/s]
17%|#7 | 7.20M/41.5M [03:02<19:09, 31.3kB/s]
17%|#7 | 7.21M/41.5M [03:02<17:36, 34.0kB/s]
17%|#7 | 7.22M/41.5M [03:02<16:21, 36.6kB/s]
17%|#7 | 7.23M/41.5M [03:03<15:23, 38.9kB/s]
17%|#7 | 7.23M/41.5M [03:03<14:40, 40.8kB/s]
17%|#7 | 7.24M/41.5M [03:03<17:45, 33.7kB/s]
17%|#7 | 7.25M/41.5M [03:03<19:59, 29.9kB/s]
17%|#7 | 7.26M/41.5M [03:04<17:52, 33.5kB/s]
18%|#7 | 7.27M/41.5M [03:04<23:53, 25.0kB/s]
18%|#7 | 7.27M/41.5M [03:04<20:35, 29.0kB/s]
18%|#7 | 7.28M/41.5M [03:05<26:45, 22.3kB/s]
18%|#7 | 7.29M/41.5M [03:05<23:58, 24.9kB/s]
18%|#7 | 7.30M/41.5M [03:05<24:25, 24.5kB/s]
18%|#7 | 7.30M/41.5M [03:06<20:55, 28.5kB/s]
18%|#7
| 7.31M/41.5M [03:06<22:17, 26.8kB/s]
18%|#7 | 7.32M/41.5M [03:06<19:25, 30.7kB/s]
18%|#7 | 7.34M/41.5M [03:07<19:16, 31.0kB/s]
18%|#7 | 7.35M/41.5M [03:07<14:08, 42.2kB/s]
18%|#7 | 7.36M/41.5M [03:07<13:49, 43.1kB/s]
18%|#7 | 7.37M/41.5M [03:07<16:36, 35.9kB/s]
18%|#7 | 7.38M/41.5M [03:08<16:22, 36.4kB/s]
18%|#7 | 7.38M/41.5M [03:08<22:11, 26.9kB/s]
18%|#7 | 7.40M/41.5M [03:09<20:50, 28.6kB/s]
18%|#7 | 7.41M/41.5M [03:09<21:54, 27.2kB/s]
18%|#7 | 7.41M/41.5M [03:10<30:09, 19.7kB/s]
18%|#7 | 7.42M/41.5M [03:10<25:32, 23.3kB/s]
18%|#7 | 7.43M/41.5M [03:10<25:29, 23.3kB/s]
18%|#7 | 7.44M/41.5M [03:10<21:53, 27.2kB/s]
18%|#7 | 7.45M/41.5M [03:11<22:53, 26.0kB/s]
18%|#7 | 7.45M/41.5M [03:11<19:56, 29.8kB/s]
18%|#7 | 7.46M/41.5M [03:11<17:48, 33.4kB/s]
18%|#8 | 7.47M/41.5M [03:12<20:0
2, 29.7kB/s]
18%|#8 | 7.48M/41.5M [03:12<13:45, 43.2kB/s]
18%|#8 | 7.49M/41.5M [03:12<13:29, 44.0kB/s]
18%|#8 | 7.50M/41.5M [03:12<13:16, 44.7kB/s]
18%|#8 | 7.51M/41.5M [03:12<13:06, 45.3kB/s]
18%|#8 | 7.52M/41.5M [03:12<12:59, 45.7kB/s]
18%|#8 | 7.52M/41.5M [03:13<12:53, 46.0kB/s]
18%|#8 | 7.53M/41.5M [03:13<12:49, 46.3kB/s]
18%|#8 | 7.55M/41.5M [03:13<09:52, 60.0kB/s]
18%|#8 | 7.55M/41.5M [03:13<10:33, 56.2kB/s]
18%|#8 | 7.56M/41.5M [03:13<11:05, 53.4kB/s]
18%|#8 | 7.58M/41.5M [03:14<11:45, 50.4kB/s]
18%|#8 | 7.60M/41.5M [03:14<08:09, 72.6kB/s]
18%|#8 | 7.61M/41.5M [03:14<08:58, 65.9kB/s]
18%|#8 | 7.62M/41.5M [03:14<09:44, 60.8kB/s]
18%|#8 | 7.63M/41.5M [03:14<10:49, 54.7kB/s]
18%|#8 | 7.66M/41.5M [03:15<09:44, 60.7kB/s]
18%|#8 | 7.67M/41.5M [03:15<08:43, 67.8kB/s]
19%|#8
| 7.68M/41.5M [03:15<11:36, 50.9kB/s]
19%|#8 | 7.69M/41.5M [03:16<11:48, 50.0kB/s]
19%|#8 | 7.70M/41.5M [03:16<14:47, 39.9kB/s]
19%|#8 | 7.71M/41.5M [03:16<13:55, 42.4kB/s]
19%|#8 | 7.72M/41.5M [03:17<19:06, 30.9kB/s]
19%|#8 | 7.73M/41.5M [03:17<17:33, 33.6kB/s]
19%|#8 | 7.73M/41.5M [03:17<16:18, 36.2kB/s]
19%|#8 | 7.74M/41.5M [03:17<15:18, 38.5kB/s]
19%|#8 | 7.75M/41.5M [03:18<18:01, 32.7kB/s]
19%|#8 | 7.77M/41.5M [03:18<18:23, 32.1kB/s]
19%|#8 | 7.77M/41.5M [03:19<19:59, 29.5kB/s]
19%|#8 | 7.78M/41.5M [03:19<21:18, 27.7kB/s]
19%|#8 | 7.79M/41.5M [03:19<18:58, 31.0kB/s]
19%|#8 | 7.80M/41.5M [03:20<24:07, 24.4kB/s]
19%|#8 | 7.80M/41.5M [03:20<24:24, 24.1kB/s]
19%|#8 | 7.81M/41.5M [03:20<25:30, 23.1kB/s]
19%|#8 | 7.82M/41.5M [03:20<21:43, 27.1kB/s]
19%|#8 | 7.83M/41.5M [03:21<26:
24, 22.3kB/s]
19%|#8 | 7.84M/41.5M [03:21<26:00, 22.6kB/s]
19%|#8 | 7.84M/41.5M [03:22<22:00, 26.7kB/s]
19%|#8 | 7.85M/41.5M [03:22<22:55, 25.6kB/s]
19%|#8 | 7.86M/41.5M [03:22<23:33, 24.9kB/s]
19%|#8 | 7.87M/41.5M [03:22<20:15, 29.0kB/s]
19%|#8 | 7.88M/41.5M [03:23<21:41, 27.1kB/s]
19%|#8 | 7.88M/41.5M [03:23<22:42, 25.9kB/s]
19%|#9 | 7.89M/41.5M [03:23<24:17, 24.2kB/s]
19%|#9 | 7.90M/41.5M [03:24<32:02, 18.3kB/s]
19%|#9 | 7.91M/41.5M [03:25<30:35, 19.2kB/s]
19%|#9 | 7.91M/41.5M [03:25<28:55, 20.3kB/s]
19%|#9 | 7.92M/41.5M [03:25<31:30, 18.6kB/s]
19%|#9 | 7.93M/41.5M [03:26<25:48, 22.7kB/s]
19%|#9 | 7.94M/41.5M [03:26<21:48, 26.9kB/s]
19%|#9 | 7.95M/41.5M [03:26<22:46, 25.7kB/s]
19%|#9 | 7.95M/41.5M [03:26<19:41, 29.8kB/s]
19%|#9 | 7.96M/41.5M [03:26<17:31, 33.4kB/s]
19%|#9
| 7.97M/41.5M [03:27<16:01, 36.6kB/s]
19%|#9 | 7.98M/41.5M [03:27<14:57, 39.2kB/s]
19%|#9 | 7.98M/41.5M [03:27<14:13, 41.2kB/s]
19%|#9 | 8.00M/41.5M [03:27<10:32, 55.5kB/s]
19%|#9 | 8.01M/41.5M [03:27<11:01, 53.1kB/s]
19%|#9 | 8.02M/41.5M [03:28<11:23, 51.3kB/s]
19%|#9 | 8.03M/41.5M [03:28<11:51, 49.3kB/s]
19%|#9 | 8.05M/41.5M [03:28<12:05, 48.3kB/s]
19%|#9 | 8.05M/41.5M [03:28<12:46, 45.7kB/s]
19%|#9 | 8.06M/41.5M [03:29<12:42, 46.0kB/s]
19%|#9 | 8.07M/41.5M [03:29<12:38, 46.2kB/s]
19%|#9 | 8.08M/41.5M [03:29<15:53, 36.8kB/s]
19%|#9 | 8.09M/41.5M [03:29<15:51, 36.8kB/s]
20%|#9 | 8.09M/41.5M [03:30<14:54, 39.2kB/s]
20%|#9 | 8.10M/41.5M [03:30<14:11, 41.1kB/s]
20%|#9 | 8.11M/41.5M [03:30<17:18, 33.7kB/s]
20%|#9 | 8.12M/41.5M [03:30<15:05, 38.6kB/s]
20%|#9 | 8.13M/41.5M [03:31<14
:26, 40.4kB/s]
20%|#9 | 8.14M/41.5M [03:31<17:08, 34.0kB/s]
20%|#9 | 8.16M/41.5M [03:31<13:06, 44.4kB/s]
20%|#9 | 8.16M/41.5M [03:31<12:57, 44.9kB/s]
20%|#9 | 8.17M/41.5M [03:32<12:49, 45.4kB/s]
20%|#9 | 8.18M/41.5M [03:32<15:59, 36.4kB/s]
20%|#9 | 8.19M/41.5M [03:32<15:00, 38.8kB/s]
20%|#9 | 8.20M/41.5M [03:33<21:14, 27.4kB/s]
20%|#9 | 8.20M/41.5M [03:33<18:42, 31.1kB/s]
20%|#9 | 8.21M/41.5M [03:33<16:52, 34.5kB/s]
20%|#9 | 8.22M/41.5M [03:33<15:33, 37.4kB/s]
20%|#9 | 8.23M/41.5M [03:33<14:37, 39.7kB/s]
20%|#9 | 8.23M/41.5M [03:33<13:58, 41.6kB/s]
20%|#9 | 8.24M/41.5M [03:34<13:30, 43.0kB/s]
20%|#9 | 8.25M/41.5M [03:34<13:10, 44.1kB/s]
20%|#9 | 8.26M/41.5M [03:34<20:20, 28.5kB/s]
20%|#9 | 8.27M/41.5M [03:35<19:31, 29.7kB/s]
20%|#9 | 8.29M/41.5M [03:36<21:36, 26.9kB/s]
20%|##
| 8.30M/41.5M [03:36<16:01, 36.2kB/s]
20%|## | 8.31M/41.5M [03:36<17:48, 32.6kB/s]
20%|## | 8.32M/41.5M [03:36<16:34, 35.0kB/s]
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0:44, 53.7kB/s]
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21%|##
| 8.68M/41.5M [03:44<11:00, 52.1kB/s]
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21%|## | 8.71M/41.5M [03:45<16:48, 34.1kB/s]
21%|##1 | 8.72M/41.5M [03:45<16:34, 34.6kB/s]
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21%|##1 | 8.73M/41.5M [03:46<14:29, 39.5kB/s]
21%|##1 | 8.74M/41.5M [03:46<19:45, 29.0kB/s]
21%|##1 | 8.75M/41.5M [03:46<18:39, 30.7kB/s]
21%|##1 | 8.77M/41.5M [03:46<12:58, 44.1kB/s]
21%|##1 | 8.77M/41.5M [03:47<12:47, 44.7kB/s]
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21%|##1 | 8.80M/41.5M [03:47<17:10, 33.3kB/s]
21%|##1 | 8.80M/41.5M [03:48<19:13, 29.7kB/s]
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21%|##1 | 8.83M/41.5M [03:49<
18:04, 31.6kB/s]
21%|##1 | 8.84M/41.5M [03:49<17:17, 33.0kB/s]
21%|##1 | 8.84M/41.5M [03:49<19:11, 29.7kB/s]
21%|##1 | 8.85M/41.5M [03:49<16:26, 34.7kB/s]
21%|##1 | 8.86M/41.5M [03:50<22:08, 25.8kB/s]
21%|##1 | 8.88M/41.5M [03:50<17:39, 32.3kB/s]
21%|##1 | 8.88M/41.5M [03:50<16:19, 34.9kB/s]
21%|##1 | 8.89M/41.5M [03:50<15:15, 37.4kB/s]
21%|##1 | 8.90M/41.5M [03:51<17:41, 32.2kB/s]
21%|##1 | 8.91M/41.5M [03:51<16:09, 35.3kB/s]
21%|##1 | 8.91M/41.5M [03:51<15:00, 37.9kB/s]
22%|##1 | 8.92M/41.5M [03:51<14:11, 40.1kB/s]
22%|##1 | 8.93M/41.5M [03:52<17:07, 33.2kB/s]
22%|##1 | 8.94M/41.5M [03:52<15:39, 36.3kB/s]
22%|##1 | 8.95M/41.5M [03:52<14:36, 38.9kB/s]
22%|##1 | 8.95M/41.5M [03:52<13:52, 41.0kB/s]
22%|##1 | 8.96M/41.5M [03:52<13:21, 42.6kB/s]
22%|##1 | 8.97M/41.5M [03:53<12:58, 43.8kB/s]
22%|##
1 | 8.98M/41.5M [03:53<16:21, 34.8kB/s]
22%|##1 | 8.98M/41.5M [03:53<15:07, 37.6kB/s]
22%|##1 | 9.00M/41.5M [03:54<16:31, 34.3kB/s]
22%|##1 | 9.02M/41.5M [03:54<12:21, 45.9kB/s]
22%|##1 | 9.02M/41.5M [03:54<12:18, 46.1kB/s]
22%|##1 | 9.03M/41.5M [03:54<12:15, 46.3kB/s]
22%|##1 | 9.04M/41.5M [03:54<12:13, 46.4kB/s]
22%|##1 | 9.05M/41.5M [03:55<18:39, 30.4kB/s]
22%|##1 | 9.06M/41.5M [03:55<13:11, 43.0kB/s]
22%|##1 | 9.07M/41.5M [03:55<12:55, 43.8kB/s]
22%|##1 | 9.08M/41.5M [03:56<22:19, 25.4kB/s]
22%|##1 | 9.09M/41.5M [03:56<15:08, 37.4kB/s]
22%|##1 | 9.10M/41.5M [03:57<19:59, 28.3kB/s]
22%|##1 | 9.12M/41.5M [03:57<14:27, 39.1kB/s]
22%|##1 | 9.12M/41.5M [03:57<13:55, 40.6kB/s]
22%|##2 | 9.13M/41.5M [03:57<13:28, 42.0kB/s]
22%|##2 | 9.14M/41.5M [03:57<13:06, 43.1kB/s]
22%|##2 | 9.15M/41.5M [03:57
<12:50, 44.0kB/s]
22%|##2 | 9.16M/41.5M [03:58<12:36, 44.8kB/s]
22%|##2 | 9.16M/41.5M [03:58<12:27, 45.4kB/s]
22%|##2 | 9.17M/41.5M [03:58<12:20, 45.8kB/s]
22%|##2 | 9.19M/41.5M [03:58<09:29, 59.5kB/s]
22%|##2 | 9.20M/41.5M [03:58<10:06, 55.8kB/s]
22%|##2 | 9.21M/41.5M [03:59<08:25, 67.0kB/s]
22%|##2 | 9.22M/41.5M [03:59<09:14, 61.0kB/s]
22%|##2 | 9.23M/41.5M [03:59<07:58, 70.7kB/s]
22%|##2 | 9.25M/41.5M [03:59<07:16, 77.5kB/s]
22%|##2 | 9.26M/41.5M [03:59<08:13, 68.4kB/s]
22%|##2 | 9.28M/41.5M [03:59<06:15, 90.0kB/s]
22%|##2 | 9.30M/41.5M [04:00<06:10, 91.1kB/s]
22%|##2 | 9.31M/41.5M [04:00<06:07, 91.9kB/s]
22%|##2 | 9.33M/41.5M [04:00<06:05, 92.3kB/s]
23%|##2 | 9.34M/41.5M [04:00<06:03, 92.8kB/s]
23%|##2 | 9.36M/41.5M [04:00<07:50, 71.6kB/s]
23%|##2 | 9.39M/41.5M [04:01<05:35, 100kB/s]
23%|#
#2 | 9.41M/41.5M [04:01<07:11, 78.0kB/s]
23%|##2 | 9.42M/41.5M [04:01<06:51, 81.6kB/s]
23%|##2 | 9.44M/41.5M [04:01<06:37, 84.6kB/s]
23%|##2 | 9.45M/41.5M [04:01<06:26, 87.0kB/s]
23%|##2 | 9.47M/41.5M [04:02<09:43, 57.6kB/s]
23%|##2 | 9.50M/41.5M [04:02<07:02, 79.5kB/s]
23%|##2 | 9.52M/41.5M [04:03<07:50, 71.2kB/s]
23%|##2 | 9.53M/41.5M [04:03<08:53, 62.8kB/s]
23%|##3 | 9.55M/41.5M [04:03<07:30, 74.4kB/s]
23%|##3 | 9.57M/41.5M [04:03<07:41, 72.6kB/s]
23%|##3 | 9.58M/41.5M [04:03<07:37, 73.1kB/s]
23%|##3 | 9.59M/41.5M [04:04<08:23, 66.4kB/s]
23%|##3 | 9.59M/41.5M [04:04<11:28, 48.6kB/s]
23%|##3 | 9.62M/41.5M [04:04<08:00, 69.5kB/s]
23%|##3 | 9.62M/41.5M [04:04<08:21, 66.6kB/s]
23%|##3 | 9.64M/41.5M [04:04<07:51, 70.8kB/s]
23%|##3 | 9.66M/41.5M [04:05<07:13, 77.0kB/s]
23%|##3 | 9.66M/41.5M [04:0
5<07:44, 71.9kB/s]
23%|##3 | 9.68M/41.5M [04:05<07:26, 74.6kB/s]
23%|##3 | 9.70M/41.5M [04:05<07:26, 74.7kB/s]
23%|##3 | 9.70M/41.5M [04:05<07:19, 75.8kB/s]
23%|##3 | 9.72M/41.5M [04:06<07:10, 77.3kB/s]
23%|##3 | 9.73M/41.5M [04:06<09:46, 56.8kB/s]
23%|##3 | 9.75M/41.5M [04:06<06:33, 84.7kB/s]
24%|##3 | 9.77M/41.5M [04:06<07:08, 77.6kB/s]
24%|##3 | 9.78M/41.5M [04:06<06:46, 81.9kB/s]
24%|##3 | 9.80M/41.5M [04:07<06:30, 85.1kB/s]
24%|##3 | 9.81M/41.5M [04:07<12:43, 43.5kB/s]
24%|##3 | 9.84M/41.5M [04:07<07:38, 72.4kB/s]
24%|##3 | 9.86M/41.5M [04:08<07:47, 70.9kB/s]
24%|##3 | 9.88M/41.5M [04:08<09:45, 56.6kB/s]
24%|##3 | 9.90M/41.5M [04:08<07:39, 72.1kB/s]
24%|##3 | 9.91M/41.5M [04:09<09:18, 59.2kB/s]
24%|##3 | 9.93M/41.5M [04:09<07:45, 71.1kB/s]
24%|##3 | 9.95M/41.5M [04:09<08:51, 62.2kB/s]
24%|
##4 | 9.96M/41.5M [04:10<10:04, 54.7kB/s]
24%|##4 | 9.97M/41.5M [04:10<09:53, 55.7kB/s]
24%|##4 | 9.98M/41.5M [04:10<12:31, 44.0kB/s]
24%|##4 | 9.98M/41.5M [04:10<14:53, 37.0kB/s]
24%|##4 | 10.0M/41.5M [04:11<13:41, 40.2kB/s]
24%|##4 | 10.0M/41.5M [04:12<21:12, 25.9kB/s]
24%|##4 | 10.0M/41.5M [04:12<14:31, 37.8kB/s]
24%|##4 | 10.0M/41.5M [04:12<14:00, 39.3kB/s]
24%|##4 | 10.0M/41.5M [04:12<13:31, 40.6kB/s]
24%|##4 | 10.1M/41.5M [04:12<13:06, 41.9kB/s]
24%|##4 | 10.1M/41.5M [04:13<15:39, 35.1kB/s]
24%|##4 | 10.1M/41.5M [04:13<17:41, 31.0kB/s]
24%|##4 | 10.1M/41.5M [04:13<15:07, 36.3kB/s]
24%|##4 | 10.1M/41.5M [04:14<14:19, 38.3kB/s]
24%|##4 | 10.1M/41.5M [04:14<13:40, 40.1kB/s]
24%|##4 | 10.1M/41.5M [04:14<16:13, 33.8kB/s]
24%|##4 | 10.1M/41.5M [04:14<14:59, 36.6kB/s]
24%|##4 | 10.1M/41.5M [04:
14<14:03, 39.0kB/s]
24%|##4 | 10.1M/41.5M [04:15<13:22, 41.0kB/s]
24%|##4 | 10.1M/41.5M [04:15<12:53, 42.5kB/s]
24%|##4 | 10.1M/41.5M [04:15<15:57, 34.3kB/s]
24%|##4 | 10.2M/41.5M [04:16<14:00, 39.1kB/s]
25%|##4 | 10.2M/41.5M [04:16<10:46, 50.7kB/s]
25%|##4 | 10.2M/41.5M [04:16<10:58, 49.8kB/s]
25%|##4 | 10.2M/41.5M [04:16<11:08, 49.1kB/s]
25%|##4 | 10.2M/41.5M [04:16<11:16, 48.5kB/s]
25%|##4 | 10.2M/41.5M [04:16<11:22, 48.1kB/s]
25%|##4 | 10.2M/41.5M [04:17<11:27, 47.7kB/s]
25%|##4 | 10.2M/41.5M [04:17<11:30, 47.5kB/s]
25%|##4 | 10.2M/41.5M [04:17<14:53, 36.7kB/s]
25%|##4 | 10.2M/41.5M [04:17<13:57, 39.1kB/s]
25%|##4 | 10.3M/41.5M [04:17<10:15, 53.2kB/s]
25%|##4 | 10.3M/41.5M [04:18<10:35, 51.5kB/s]
25%|##4 | 10.3M/41.5M [04:18<08:37, 63.2kB/s]
25%|##4 | 10.3M/41.5M [04:18<09:18, 58.6kB/s]
25%
|##4 | 10.3M/41.5M [04:18<09:52, 55.2kB/s]
25%|##4 | 10.3M/41.5M [04:18<10:35, 51.4kB/s]
25%|##4 | 10.3M/41.5M [04:19<08:49, 61.8kB/s]
25%|##4 | 10.3M/41.5M [04:19<09:24, 57.9kB/s]
25%|##4 | 10.3M/41.5M [04:19<09:54, 54.9kB/s]
25%|##4 | 10.4M/41.5M [04:19<08:16, 65.7kB/s]
25%|##4 | 10.4M/41.5M [04:19<09:00, 60.4kB/s]
25%|##5 | 10.4M/41.5M [04:20<09:37, 56.5kB/s]
25%|##5 | 10.4M/41.5M [04:20<13:05, 41.5kB/s]
25%|##5 | 10.4M/41.5M [04:20<08:16, 65.7kB/s]
25%|##5 | 10.4M/41.5M [04:20<11:14, 48.3kB/s]
25%|##5 | 10.4M/41.5M [04:21<11:57, 45.4kB/s]
25%|##5 | 10.4M/41.5M [04:21<13:57, 38.9kB/s]
25%|##5 | 10.4M/41.5M [04:21<13:32, 40.1kB/s]
25%|##5 | 10.5M/41.5M [04:22<13:08, 41.3kB/s]
25%|##5 | 10.5M/41.5M [04:22<15:31, 34.9kB/s]
25%|##5 | 10.5M/41.5M [04:22<14:29, 37.4kB/s]
25%|##5 | 10.5M/41.5M [04
:22<13:42, 39.5kB/s]
25%|##5 | 10.5M/41.5M [04:22<13:06, 41.3kB/s]
25%|##5 | 10.5M/41.5M [04:23<12:39, 42.8kB/s]
25%|##5 | 10.5M/41.5M [04:23<12:20, 43.9kB/s]
25%|##5 | 10.5M/41.5M [04:23<09:22, 57.8kB/s]
25%|##5 | 10.5M/41.5M [04:23<09:54, 54.7kB/s]
25%|##5 | 10.5M/41.5M [04:23<10:19, 52.4kB/s]
25%|##5 | 10.5M/41.5M [04:23<08:23, 64.5kB/s]
25%|##5 | 10.6M/41.5M [04:24<09:07, 59.3kB/s]
25%|##5 | 10.6M/41.5M [04:24<07:46, 69.5kB/s]
26%|##5 | 10.6M/41.5M [04:24<07:02, 76.7kB/s]
26%|##5 | 10.6M/41.5M [04:24<05:38, 95.7kB/s]
26%|##5 | 10.6M/41.5M [04:24<05:40, 95.1kB/s]
26%|##5 | 10.6M/41.5M [04:24<04:57, 109kB/s]
26%|##5 | 10.7M/41.5M [04:25<05:10, 104kB/s]
26%|##5 | 10.7M/41.5M [04:25<04:42, 114kB/s]
26%|##5 | 10.7M/41.5M [04:25<03:55, 137kB/s]
26%|##5 | 10.7M/41.5M [04:25<05:03, 106kB/s]
26%|##
5 | 10.8M/41.5M [04:26<04:43, 114kB/s]
26%|##5 | 10.8M/41.5M [04:26<04:56, 109kB/s]
26%|##6 | 10.8M/41.5M [04:26<05:07, 105kB/s]
26%|##6 | 10.8M/41.5M [04:26<05:16, 102kB/s]
26%|##6 | 10.8M/41.5M [04:26<05:23, 99.3kB/s]
26%|##6 | 10.8M/41.5M [04:26<05:28, 97.7kB/s]
26%|##6 | 10.9M/41.5M [04:27<05:32, 96.5kB/s]
26%|##6 | 10.9M/41.5M [04:27<05:35, 95.7kB/s]
26%|##6 | 10.9M/41.5M [04:27<05:37, 95.1kB/s]
26%|##6 | 10.9M/41.5M [04:27<05:38, 94.7kB/s]
26%|##6 | 10.9M/41.5M [04:27<05:39, 94.4kB/s]
26%|##6 | 10.9M/41.5M [04:27<05:40, 94.2kB/s]
26%|##6 | 11.0M/41.5M [04:28<07:22, 72.4kB/s]
26%|##6 | 11.0M/41.5M [04:28<08:05, 66.0kB/s]
26%|##6 | 11.0M/41.5M [04:28<08:44, 61.0kB/s]
26%|##6 | 11.0M/41.5M [04:28<07:37, 69.9kB/s]
26%|##6 | 11.0M/41.5M [04:29<08:24, 63.4kB/s]
27%|##6 | 11.0M/41.5M [04:29<09:
04, 58.7kB/s]
27%|##6 | 11.0M/41.5M [04:29<07:44, 68.8kB/s]
27%|##6 | 11.0M/41.5M [04:29<08:31, 62.4kB/s]
27%|##6 | 11.0M/41.5M [04:29<09:12, 57.8kB/s]
27%|##6 | 11.0M/41.5M [04:30<10:04, 52.8kB/s]
27%|##6 | 11.1M/41.5M [04:30<07:08, 74.4kB/s]
27%|##6 | 11.1M/41.5M [04:30<07:54, 67.2kB/s]
27%|##6 | 11.1M/41.5M [04:30<08:36, 61.7kB/s]
27%|##6 | 11.1M/41.5M [04:30<09:36, 55.2kB/s]
27%|##6 | 11.1M/41.5M [04:31<07:32, 70.3kB/s]
27%|##6 | 11.1M/41.5M [04:31<07:35, 69.9kB/s]
27%|##6 | 11.1M/41.5M [04:31<07:31, 70.5kB/s]
27%|##6 | 11.2M/41.5M [04:31<07:34, 70.0kB/s]
27%|##6 | 11.2M/41.5M [04:31<06:56, 76.4kB/s]
27%|##6 | 11.2M/41.5M [04:31<06:59, 75.8kB/s]
27%|##6 | 11.2M/41.5M [04:32<06:30, 81.3kB/s]
27%|##7 | 11.2M/41.5M [04:32<06:54, 76.6kB/s]
27%|##7 | 11.2M/41.5M [04:32<05:49, 90.7kB/s]
27%|##7
| 11.2M/41.5M [04:32<05:46, 91.7kB/s]
27%|##7 | 11.3M/41.5M [04:32<05:43, 92.3kB/s]
27%|##7 | 11.3M/41.5M [04:32<05:41, 92.8kB/s]
27%|##7 | 11.3M/41.5M [04:33<07:00, 75.3kB/s]
27%|##7 | 11.3M/41.5M [04:34<12:59, 40.6kB/s]
27%|##7 | 11.4M/41.5M [04:34<06:59, 75.3kB/s]
27%|##7 | 11.4M/41.5M [04:34<07:23, 71.2kB/s]
27%|##7 | 11.4M/41.5M [04:35<08:49, 59.6kB/s]
27%|##7 | 11.4M/41.5M [04:35<06:36, 79.5kB/s]
28%|##7 | 11.4M/41.5M [04:35<09:04, 58.0kB/s]
28%|##7 | 11.4M/41.5M [04:35<08:11, 64.2kB/s]
28%|##7 | 11.5M/41.5M [04:36<08:59, 58.4kB/s]
28%|##7 | 11.5M/41.5M [04:36<09:20, 56.2kB/s]
28%|##7 | 11.5M/41.5M [04:36<13:51, 37.8kB/s]
28%|##7 | 11.5M/41.5M [04:37<10:59, 47.7kB/s]
28%|##7 | 11.5M/41.5M [04:37<13:14, 39.6kB/s]
28%|##7 | 11.5M/41.5M [04:37<12:47, 41.0kB/s]
28%|##7 | 11.5M/41.5M [04:37<12
:24, 42.2kB/s]
28%|##7 | 11.5M/41.5M [04:37<12:05, 43.3kB/s]
28%|##7 | 11.5M/41.5M [04:38<11:51, 44.2kB/s]
28%|##7 | 11.5M/41.5M [04:38<11:40, 44.9kB/s]
28%|##7 | 11.5M/41.5M [04:38<08:58, 58.3kB/s]
28%|##7 | 11.6M/41.5M [04:38<09:30, 55.0kB/s]
28%|##7 | 11.6M/41.5M [04:38<07:54, 66.1kB/s]
28%|##7 | 11.6M/41.5M [04:38<08:38, 60.5kB/s]
28%|##7 | 11.6M/41.5M [04:39<07:26, 70.3kB/s]
28%|##7 | 11.6M/41.5M [04:39<06:45, 77.2kB/s]
28%|##8 | 11.6M/41.5M [04:39<06:21, 82.1kB/s]
28%|##8 | 11.6M/41.5M [04:39<06:05, 85.6kB/s]
28%|##8 | 11.7M/41.5M [04:39<05:55, 88.0kB/s]
28%|##8 | 11.7M/41.5M [04:40<05:48, 89.7kB/s]
28%|##8 | 11.7M/41.5M [04:40<07:26, 70.0kB/s]
28%|##8 | 11.7M/41.5M [04:40<06:51, 75.9kB/s]
28%|##8 | 11.7M/41.5M [04:40<06:27, 80.5kB/s]
28%|##8 | 11.7M/41.5M [04:41<08:16, 62.9kB/s]
28%|##8
| 11.8M/41.5M [04:41<07:02, 73.8kB/s]
28%|##8 | 11.8M/41.5M [04:41<09:55, 52.3kB/s]
28%|##8 | 11.8M/41.5M [04:42<08:03, 64.4kB/s]
28%|##8 | 11.8M/41.5M [04:42<08:32, 60.8kB/s]
28%|##8 | 11.8M/41.5M [04:42<09:00, 57.6kB/s]
28%|##8 | 11.8M/41.5M [04:42<07:48, 66.4kB/s]
29%|##8 | 11.8M/41.5M [04:42<08:26, 61.3kB/s]
29%|##8 | 11.8M/41.5M [04:42<09:01, 57.4kB/s]
29%|##8 | 11.9M/41.5M [04:43<09:48, 52.8kB/s]
29%|##8 | 11.9M/41.5M [04:43<10:14, 50.5kB/s]
29%|##8 | 11.9M/41.5M [04:43<10:30, 49.2kB/s]
29%|##8 | 11.9M/41.5M [04:44<10:36, 48.7kB/s]
29%|##8 | 11.9M/41.5M [04:44<10:42, 48.3kB/s]
29%|##8 | 11.9M/41.5M [04:44<10:46, 48.0kB/s]
29%|##8 | 11.9M/41.5M [04:44<10:50, 47.7kB/s]
29%|##8 | 11.9M/41.5M [04:44<08:36, 60.0kB/s]
29%|##8 | 11.9M/41.5M [04:45<11:42, 44.1kB/s]
29%|##8 | 12.0M/41.5M [04:45<0
9:14, 55.8kB/s]
29%|##8 | 12.0M/41.5M [04:45<09:38, 53.5kB/s]
29%|##8 | 12.0M/41.5M [04:45<09:56, 51.9kB/s]
29%|##8 | 12.0M/41.5M [04:45<10:12, 50.5kB/s]
29%|##8 | 12.0M/41.5M [04:46<10:25, 49.5kB/s]
29%|##8 | 12.0M/41.5M [04:46<08:17, 62.2kB/s]
29%|##8 | 12.0M/41.5M [04:46<08:55, 57.7kB/s]
29%|##8 | 12.0M/41.5M [04:46<09:46, 52.7kB/s]
29%|##9 | 12.0M/41.5M [04:46<08:12, 62.7kB/s]
29%|##9 | 12.0M/41.5M [04:47<08:46, 58.6kB/s]
29%|##9 | 12.1M/41.5M [04:47<11:47, 43.7kB/s]
29%|##9 | 12.1M/41.5M [04:47<11:35, 44.4kB/s]
29%|##9 | 12.1M/41.5M [04:47<11:25, 45.0kB/s]
29%|##9 | 12.1M/41.5M [04:48<14:15, 36.0kB/s]
29%|##9 | 12.1M/41.5M [04:48<13:20, 38.5kB/s]
29%|##9 | 12.1M/41.5M [04:48<12:39, 40.6kB/s]
29%|##9 | 12.1M/41.5M [04:49<18:30, 27.7kB/s]
29%|##9 | 12.1M/41.5M [04:49<12:36, 40.7kB/s]
29%|##9
| 12.1M/41.5M [04:49<12:12, 42.1kB/s]
29%|##9 | 12.1M/41.5M [04:49<11:52, 43.2kB/s]
29%|##9 | 12.1M/41.5M [04:49<14:36, 35.1kB/s]
29%|##9 | 12.1M/41.5M [04:50<13:34, 37.8kB/s]
29%|##9 | 12.2M/41.5M [04:50<12:49, 40.0kB/s]
29%|##9 | 12.2M/41.5M [04:50<15:26, 33.2kB/s]
29%|##9 | 12.2M/41.5M [04:50<13:23, 38.2kB/s]
29%|##9 | 12.2M/41.5M [04:51<12:47, 40.0kB/s]
29%|##9 | 12.2M/41.5M [04:51<12:18, 41.6kB/s]
29%|##9 | 12.2M/41.5M [04:51<11:55, 42.9kB/s]
29%|##9 | 12.2M/41.5M [04:51<11:38, 43.9kB/s]
29%|##9 | 12.2M/41.5M [04:51<08:54, 57.4kB/s]
29%|##9 | 12.2M/41.5M [04:51<09:22, 54.5kB/s]
30%|##9 | 12.2M/41.5M [04:52<09:46, 52.3kB/s]
30%|##9 | 12.2M/41.5M [04:52<10:04, 50.7kB/s]
30%|##9 | 12.3M/41.5M [04:52<08:04, 63.3kB/s]
30%|##9 | 12.3M/41.5M [04:52<08:44, 58.5kB/s]
30%|##9 | 12.3M/41.5M [04:52<
07:24, 68.9kB/s]
30%|##9 | 12.3M/41.5M [04:53<06:41, 76.3kB/s]
30%|##9 | 12.3M/41.5M [04:53<06:15, 81.4kB/s]
30%|##9 | 12.3M/41.5M [04:53<07:09, 71.2kB/s]
30%|##9 | 12.3M/41.5M [04:53<06:32, 77.9kB/s]
30%|##9 | 12.4M/41.5M [04:53<06:09, 82.6kB/s]
30%|##9 | 12.4M/41.5M [04:54<07:42, 66.0kB/s]
30%|##9 | 12.4M/41.5M [04:54<05:17, 96.1kB/s]
30%|##9 | 12.4M/41.5M [04:54<05:19, 95.5kB/s]
30%|##9 | 12.4M/41.5M [04:54<05:20, 95.0kB/s]
30%|### | 12.5M/41.5M [04:54<05:22, 94.6kB/s]
30%|### | 12.5M/41.5M [04:55<06:54, 73.4kB/s]
30%|### | 12.5M/41.5M [04:55<05:39, 89.5kB/s]
30%|### | 12.5M/41.5M [04:55<07:01, 72.0kB/s]
30%|### | 12.5M/41.5M [04:55<05:47, 87.5kB/s]
30%|### | 12.5M/41.5M [04:56<05:41, 88.8kB/s]
30%|### | 12.6M/41.5M [04:56<05:36, 90.1kB/s]
30%|### | 12.6M/41.5M [04:56<08:31, 59.3kB/s]
30%|##
# | 12.6M/41.5M [04:56<08:53, 56.8kB/s]
30%|### | 12.6M/41.5M [04:57<07:10, 70.4kB/s]
30%|### | 12.6M/41.5M [04:57<07:11, 70.2kB/s]
30%|### | 12.6M/41.5M [04:57<09:57, 50.6kB/s]
30%|### | 12.6M/41.5M [04:57<08:33, 58.9kB/s]
31%|### | 12.7M/41.5M [04:58<08:57, 56.3kB/s]
31%|### | 12.7M/41.5M [04:58<09:33, 52.7kB/s]
31%|### | 12.7M/41.5M [04:58<09:47, 51.4kB/s]
31%|### | 12.7M/41.5M [04:58<12:19, 40.8kB/s]
31%|### | 12.7M/41.5M [04:59<11:57, 42.1kB/s]
31%|### | 12.7M/41.5M [04:59<11:38, 43.2kB/s]
31%|### | 12.7M/41.5M [04:59<11:23, 44.1kB/s]
31%|### | 12.7M/41.5M [05:00<29:00, 17.3kB/s]
31%|### | 12.7M/41.5M [05:00<23:50, 21.1kB/s]
31%|### | 12.7M/41.5M [05:01<15:35, 32.2kB/s]
31%|### | 12.8M/41.5M [05:01<17:20, 29.0kB/s]
31%|### | 12.8M/41.5M [05:01<15:16, 32.9kB/s]
31%|### | 12.8M/41.5M [05:02
<19:48, 25.4kB/s]
31%|### | 12.8M/41.5M [05:02<13:31, 37.1kB/s]
31%|### | 12.8M/41.5M [05:02<12:51, 39.0kB/s]
31%|### | 12.8M/41.5M [05:02<12:18, 40.7kB/s]
31%|### | 12.8M/41.5M [05:03<17:33, 28.6kB/s]
31%|### | 12.8M/41.5M [05:03<12:17, 40.8kB/s]
31%|### | 12.8M/41.5M [05:03<11:54, 42.1kB/s]
31%|### | 12.8M/41.5M [05:03<11:35, 43.2kB/s]
31%|### | 12.8M/41.5M [05:03<11:21, 44.1kB/s]
31%|### | 12.9M/41.5M [05:04<11:10, 44.8kB/s]
31%|### | 12.9M/41.5M [05:04<11:01, 45.4kB/s]
31%|###1 | 12.9M/41.5M [05:04<10:55, 45.8kB/s]
31%|###1 | 12.9M/41.5M [05:04<13:56, 35.9kB/s]
31%|###1 | 12.9M/41.5M [05:04<10:02, 49.8kB/s]
31%|###1 | 12.9M/41.5M [05:05<10:11, 49.0kB/s]
31%|###1 | 12.9M/41.5M [05:05<10:18, 48.4kB/s]
31%|###1 | 12.9M/41.5M [05:05<10:24, 48.0kB/s]
31%|###1 | 12.9M/41.5M [05:05<13:26, 37.2kB/s]
31%|#
##1 | 12.9M/41.5M [05:05<12:38, 39.5kB/s]
31%|###1 | 12.9M/41.5M [05:06<12:03, 41.4kB/s]
31%|###1 | 12.9M/41.5M [05:06<11:38, 42.8kB/s]
31%|###1 | 13.0M/41.5M [05:06<09:21, 53.3kB/s]
31%|###1 | 13.0M/41.5M [05:06<09:39, 51.6kB/s]
31%|###1 | 13.0M/41.5M [05:06<09:14, 53.9kB/s]
31%|###1 | 13.0M/41.5M [05:07<09:37, 51.8kB/s]
31%|###1 | 13.0M/41.5M [05:07<08:17, 60.0kB/s]
31%|###1 | 13.0M/41.5M [05:07<08:14, 60.3kB/s]
31%|###1 | 13.0M/41.5M [05:07<07:03, 70.5kB/s]
31%|###1 | 13.0M/41.5M [05:07<06:24, 77.5kB/s]
31%|###1 | 13.0M/41.5M [05:07<07:16, 68.3kB/s]
31%|###1 | 13.1M/41.5M [05:08<06:32, 75.9kB/s]
32%|###1 | 13.1M/41.5M [05:08<06:06, 81.3kB/s]
32%|###1 | 13.1M/41.5M [05:08<05:00, 99.1kB/s]
32%|###1 | 13.1M/41.5M [05:08<06:36, 75.0kB/s]
32%|###1 | 13.1M/41.5M [05:08<05:25, 91.2kB/s]
32%|###1 | 13.2M/41.5M [05:0
9<04:45, 104kB/s]
32%|###1 | 13.2M/41.5M [05:09<05:13, 94.8kB/s]
32%|###1 | 13.2M/41.5M [05:09<05:14, 94.5kB/s]
32%|###1 | 13.2M/41.5M [05:09<05:14, 94.3kB/s]
32%|###1 | 13.2M/41.5M [05:10<06:43, 73.4kB/s]
32%|###1 | 13.2M/41.5M [05:10<07:26, 66.3kB/s]
32%|###1 | 13.2M/41.5M [05:10<09:45, 50.6kB/s]
32%|###1 | 13.3M/41.5M [05:10<07:29, 65.8kB/s]
32%|###2 | 13.3M/41.5M [05:11<08:00, 61.6kB/s]
32%|###2 | 13.3M/41.5M [05:11<08:29, 58.1kB/s]
32%|###2 | 13.3M/41.5M [05:11<08:55, 55.2kB/s]
32%|###2 | 13.3M/41.5M [05:11<07:31, 65.5kB/s]
32%|###2 | 13.3M/41.5M [05:12<09:01, 54.5kB/s]
32%|###2 | 13.4M/41.5M [05:12<06:16, 78.3kB/s]
32%|###2 | 13.4M/41.5M [05:13<13:52, 35.4kB/s]
32%|###2 | 13.4M/41.5M [05:13<09:49, 50.0kB/s]
32%|###2 | 13.4M/41.5M [05:13<09:04, 54.1kB/s]
32%|###2 | 13.4M/41.5M [05:14<12:10, 40.3kB/s]
32%|
###2 | 13.4M/41.5M [05:14<12:01, 40.8kB/s]
32%|###2 | 13.5M/41.5M [05:15<15:16, 32.1kB/s]
32%|###2 | 13.5M/41.5M [05:16<16:18, 30.0kB/s]
32%|###2 | 13.5M/41.5M [05:16<15:04, 32.5kB/s]
33%|###2 | 13.5M/41.5M [05:16<15:23, 31.8kB/s]
33%|###2 | 13.5M/41.5M [05:16<15:14, 32.1kB/s]
33%|###2 | 13.5M/41.5M [05:16<15:34, 31.4kB/s]
33%|###2 | 13.5M/41.5M [05:17<15:20, 31.9kB/s]
33%|###2 | 13.5M/41.5M [05:17<13:59, 34.9kB/s]
33%|###2 | 13.5M/41.5M [05:17<15:55, 30.7kB/s]
33%|###2 | 13.5M/41.5M [05:17<13:07, 37.2kB/s]
33%|###2 | 13.5M/41.5M [05:18<18:22, 26.6kB/s]
33%|###2 | 13.6M/41.5M [05:18<14:46, 33.1kB/s]
33%|###2 | 13.6M/41.5M [05:18<13:42, 35.6kB/s]
33%|###2 | 13.6M/41.5M [05:19<12:50, 38.0kB/s]
33%|###2 | 13.6M/41.5M [05:19<12:11, 40.0kB/s]
33%|###2 | 13.6M/41.5M [05:19<11:42, 41.7kB/s]
33%|###2 | 13.6M/41.5M [05:
19<11:19, 43.0kB/s]
33%|###2 | 13.6M/41.5M [05:19<11:03, 44.1kB/s]
33%|###2 | 13.6M/41.5M [05:20<23:08, 21.1kB/s]
33%|###2 | 13.6M/41.5M [05:20<16:51, 28.9kB/s]
33%|###2 | 13.6M/41.5M [05:21<20:45, 23.5kB/s]
33%|###2 | 13.7M/41.5M [05:22<16:43, 29.1kB/s]
33%|###2 | 13.7M/41.5M [05:22<14:33, 33.4kB/s]
33%|###2 | 13.7M/41.5M [05:22<13:44, 35.4kB/s]
33%|###2 | 13.7M/41.5M [05:22<12:59, 37.4kB/s]
33%|###3 | 13.7M/41.5M [05:23<09:59, 48.6kB/s]
33%|###3 | 13.7M/41.5M [05:23<10:04, 48.2kB/s]
33%|###3 | 13.7M/41.5M [05:23<10:08, 47.9kB/s]
33%|###3 | 13.7M/41.5M [05:23<10:13, 47.5kB/s]
33%|###3 | 13.8M/41.5M [05:23<08:22, 57.9kB/s]
33%|###3 | 13.8M/41.5M [05:24<08:46, 55.2kB/s]
33%|###3 | 13.8M/41.5M [05:24<09:07, 53.1kB/s]
33%|###3 | 13.8M/41.5M [05:24<09:25, 51.3kB/s]
33%|###3 | 13.8M/41.5M [05:24<09:39, 50.1kB/s]
33%
|###3 | 13.8M/41.5M [05:24<09:50, 49.2kB/s]
33%|###3 | 13.8M/41.5M [05:25<15:43, 30.8kB/s]
33%|###3 | 13.8M/41.5M [05:25<13:19, 36.3kB/s]
33%|###3 | 13.8M/41.5M [05:25<12:36, 38.4kB/s]
33%|###3 | 13.8M/41.5M [05:26<14:39, 33.0kB/s]
33%|###3 | 13.8M/41.5M [05:26<13:29, 35.8kB/s]
33%|###3 | 13.8M/41.5M [05:26<12:36, 38.3kB/s]
33%|###3 | 13.9M/41.5M [05:26<11:57, 40.4kB/s]
33%|###3 | 13.9M/41.5M [05:27<17:24, 27.7kB/s]
33%|###3 | 13.9M/41.5M [05:27<11:53, 40.6kB/s]
33%|###3 | 13.9M/41.5M [05:27<16:30, 29.2kB/s]
33%|###3 | 13.9M/41.5M [05:28<11:50, 40.7kB/s]
34%|###3 | 13.9M/41.5M [05:28<11:29, 42.0kB/s]
34%|###3 | 13.9M/41.5M [05:28<11:11, 43.1kB/s]
34%|###3 | 13.9M/41.5M [05:28<13:36, 35.4kB/s]
34%|###3 | 13.9M/41.5M [05:29<12:42, 37.9kB/s]
34%|###3 | 13.9M/41.5M [05:29<14:53, 32.3kB/s]
34%|###3 | 13.9M/41.5M [05
:29<16:29, 29.2kB/s]
34%|###3 | 14.0M/41.5M [05:29<14:41, 32.7kB/s]
34%|###3 | 14.0M/41.5M [05:30<13:23, 35.9kB/s]
34%|###3 | 14.0M/41.5M [05:30<12:28, 38.6kB/s]
34%|###3 | 14.0M/41.5M [05:30<11:49, 40.7kB/s]
34%|###3 | 14.0M/41.5M [05:30<14:24, 33.4kB/s]
34%|###3 | 14.0M/41.5M [05:30<13:09, 36.5kB/s]
34%|###3 | 14.0M/41.5M [05:31<15:21, 31.3kB/s]
34%|###3 | 14.0M/41.5M [05:31<13:49, 34.7kB/s]
34%|###3 | 14.0M/41.5M [05:32<21:56, 21.9kB/s]
34%|###3 | 14.0M/41.5M [05:32<21:30, 22.3kB/s]
34%|###3 | 14.0M/41.5M [05:32<18:07, 26.5kB/s]
34%|###3 | 14.0M/41.5M [05:32<15:45, 30.4kB/s]
34%|###3 | 14.0M/41.5M [05:33<17:09, 27.9kB/s]
34%|###3 | 14.1M/41.5M [05:33<21:13, 22.6kB/s]
34%|###3 | 14.1M/41.5M [05:34<16:08, 29.7kB/s]
34%|###3 | 14.1M/41.5M [05:34<14:40, 32.7kB/s]
34%|###3 | 14.1M/41.5M [05:34<16:10, 29.6kB/s]
34
%|###3 | 14.1M/41.5M [05:34<17:19, 27.6kB/s]
34%|###4 | 14.1M/41.5M [05:35<14:12, 33.7kB/s]
34%|###4 | 14.1M/41.5M [05:35<13:15, 36.1kB/s]
34%|###4 | 14.1M/41.5M [05:35<12:28, 38.3kB/s]
34%|###4 | 14.1M/41.5M [05:35<11:52, 40.3kB/s]
34%|###4 | 14.1M/41.5M [05:35<08:56, 53.4kB/s]
34%|###4 | 14.2M/41.5M [05:36<09:14, 51.7kB/s]
34%|###4 | 14.2M/41.5M [05:36<12:02, 39.7kB/s]
34%|###4 | 14.2M/41.5M [05:36<09:08, 52.3kB/s]
34%|###4 | 14.2M/41.5M [05:36<09:22, 50.9kB/s]
34%|###4 | 14.2M/41.5M [05:37<09:34, 49.8kB/s]
34%|###4 | 14.2M/41.5M [05:37<07:42, 61.8kB/s]
34%|###4 | 14.2M/41.5M [05:37<08:16, 57.6kB/s]
34%|###4 | 14.2M/41.5M [05:37<08:44, 54.6kB/s]
34%|###4 | 14.2M/41.5M [05:37<07:13, 65.9kB/s]
34%|###4 | 14.2M/41.5M [05:37<07:53, 60.3kB/s]
34%|###4 | 14.3M/41.5M [05:38<06:46, 70.2kB/s]
34%|###4 | 14.3M/41.5M [0
5:38<07:30, 63.3kB/s]
34%|###4 | 14.3M/41.5M [05:38<08:08, 58.4kB/s]
34%|###4 | 14.3M/41.5M [05:38<08:40, 54.8kB/s]
34%|###4 | 14.3M/41.5M [05:38<07:08, 66.5kB/s]
34%|###4 | 14.3M/41.5M [05:38<07:50, 60.6kB/s]
35%|###4 | 14.3M/41.5M [05:39<06:43, 70.5kB/s]
35%|###4 | 14.3M/41.5M [05:39<07:28, 63.4kB/s]
35%|###4 | 14.4M/41.5M [05:39<08:30, 55.8kB/s]
35%|###4 | 14.4M/41.5M [05:39<07:16, 65.2kB/s]
35%|###4 | 14.4M/41.5M [05:40<08:13, 57.6kB/s]
35%|###4 | 14.4M/41.5M [05:40<07:11, 65.8kB/s]
35%|###4 | 14.4M/41.5M [05:40<07:44, 61.2kB/s]
35%|###4 | 14.4M/41.5M [05:40<08:14, 57.4kB/s]
35%|###4 | 14.4M/41.5M [05:40<08:40, 54.6kB/s]
35%|###4 | 14.4M/41.5M [05:41<07:13, 65.5kB/s]
35%|###4 | 14.4M/41.5M [05:41<07:51, 60.2kB/s]
35%|###4 | 14.5M/41.5M [05:41<07:34, 62.4kB/s]
35%|###4 | 14.5M/41.5M [05:41<07:13, 65.3kB/s]
3
5%|###4 | 14.5M/41.5M [05:41<07:06, 66.5kB/s]
35%|###4 | 14.5M/41.5M [05:41<06:57, 67.9kB/s]
35%|###4 | 14.5M/41.5M [05:42<08:04, 58.4kB/s]
35%|###5 | 14.5M/41.5M [05:42<06:00, 78.3kB/s]
35%|###5 | 14.5M/41.5M [05:42<06:10, 76.3kB/s]
35%|###5 | 14.6M/41.5M [05:42<06:18, 74.6kB/s]
35%|###5 | 14.6M/41.5M [05:42<05:52, 80.0kB/s]
35%|###5 | 14.6M/41.5M [05:43<05:36, 83.9kB/s]
35%|###5 | 14.6M/41.5M [05:43<05:53, 79.8kB/s]
35%|###5 | 14.6M/41.5M [05:43<06:05, 77.1kB/s]
35%|###5 | 14.6M/41.5M [05:43<06:54, 68.0kB/s]
35%|###5 | 14.6M/41.5M [05:43<06:11, 75.7kB/s]
35%|###5 | 14.6M/41.5M [05:44<05:46, 81.1kB/s]
35%|###5 | 14.7M/41.5M [05:44<05:31, 84.9kB/s]
35%|###5 | 14.7M/41.5M [05:44<05:21, 87.4kB/s]
35%|###5 | 14.7M/41.5M [05:44<05:14, 89.3kB/s]
35%|###5 | 14.7M/41.5M [05:44<05:37, 83.2kB/s]
35%|###5 | 14.7M/41.5M [
05:44<04:58, 94.1kB/s]
36%|###5 | 14.7M/41.5M [05:45<08:01, 58.2kB/s]
36%|###5 | 14.8M/41.5M [05:45<07:28, 62.5kB/s]
36%|###5 | 14.8M/41.5M [05:45<06:48, 68.6kB/s]
36%|###5 | 14.8M/41.5M [05:46<07:46, 60.0kB/s]
36%|###5 | 14.8M/41.5M [05:46<07:39, 60.9kB/s]
36%|###5 | 14.8M/41.5M [05:46<08:08, 57.3kB/s]
36%|###5 | 14.8M/41.5M [05:46<08:33, 54.5kB/s]
36%|###5 | 14.8M/41.5M [05:46<08:54, 52.3kB/s]
36%|###5 | 14.8M/41.5M [05:47<09:55, 46.9kB/s]
36%|###5 | 14.9M/41.5M [05:47<10:26, 44.6kB/s]
36%|###5 | 14.9M/41.5M [05:47<09:47, 47.5kB/s]
36%|###5 | 14.9M/41.5M [05:48<11:47, 39.5kB/s]
36%|###5 | 14.9M/41.5M [05:48<11:22, 40.9kB/s]
36%|###5 | 14.9M/41.5M [05:48<13:24, 34.7kB/s]
36%|###5 | 14.9M/41.5M [05:49<10:51, 42.8kB/s]
36%|###5 | 14.9M/41.5M [05:49<11:52, 39.1kB/s]
36%|###5 | 14.9M/41.5M [05:49<12:28, 37.2kB/s]
36%|###5 | 14.9M/41.5M [05:49<13:13, 35.1kB/s]
36%|###6 | 14.9M/41.5M [05:50<12:19, 37.6kB/s]
36%|###6 | 14.9M/41.5M [05:50<14:23, 32.2kB/s]
36%|###6 | 15.0M/41.5M [05:50<10:12, 45.4kB/s]
36%|###6 | 15.0M/41.5M [05:50<10:08, 45.7kB/s]
36%|###6 | 15.0M/41.5M [05:50<10:04, 46.0kB/s]
36%|###6 | 15.0M/41.5M [05:51<10:00, 46.3kB/s]
36%|###6 | 15.0M/41.5M [05:51<09:58, 46.4kB/s]
36%|###6 | 15.0M/41.5M [05:51<09:56, 46.6kB/s]
36%|###6 | 15.0M/41.5M [05:51<09:55, 46.6kB/s]
36%|###6 | 15.0M/41.5M [05:51<09:54, 46.7kB/s]
36%|###6 | 15.0M/41.5M [05:51<09:53, 46.7kB/s]
36%|###6 | 15.0M/41.5M [05:52<09:53, 46.8kB/s]
36%|###6 | 15.0M/41.5M [05:52<07:37, 60.7kB/s]
36%|###6 | 15.1M/41.5M [05:52<08:09, 56.6kB/s]
36%|###6 | 15.1M/41.5M [05:52<08:36, 53.7kB/s]
36%|###6 | 15.1M/41.5M [05:52<08:56, 51.6kB/s]
36%|###6 | 15.1M/41.5M
[05:53<07:41, 60.0kB/s]
36%|###6 | 15.1M/41.5M [05:53<08:11, 56.3kB/s]
36%|###6 | 15.1M/41.5M [05:53<08:01, 57.5kB/s]
36%|###6 | 15.1M/41.5M [05:53<07:12, 64.0kB/s]
36%|###6 | 15.1M/41.5M [05:53<07:16, 63.3kB/s]
36%|###6 | 15.1M/41.5M [05:53<07:54, 58.3kB/s]
37%|###6 | 15.1M/41.5M [05:54<07:08, 64.5kB/s]
37%|###6 | 15.2M/41.5M [05:54<07:13, 63.7kB/s]
37%|###6 | 15.2M/41.5M [05:54<06:18, 72.9kB/s]
37%|###6 | 15.2M/41.5M [05:54<07:04, 65.0kB/s]
37%|###6 | 15.2M/41.5M [05:54<06:14, 73.7kB/s]
37%|###6 | 15.2M/41.5M [05:54<05:45, 79.7kB/s]
37%|###6 | 15.2M/41.5M [05:55<05:27, 84.0kB/s]
37%|###6 | 15.2M/41.5M [05:55<05:16, 86.9kB/s]
37%|###6 | 15.3M/41.5M [05:55<05:09, 88.9kB/s]
37%|###6 | 15.3M/41.5M [05:55<05:03, 90.4kB/s]
37%|###6 | 15.3M/41.5M [05:55<04:20, 105kB/s]
37%|###6 | 15.3M/41.5M [05:56<05:08, 89.1kB/s]
37%|###6 | 15.3M/41.5M [05:56<04:08, 110kB/s]
37%|###7 | 15.4M/41.5M [05:57<09:21, 48.8kB/s]
37%|###7 | 15.4M/41.5M [05:57<05:46, 79.0kB/s]
37%|###7 | 15.4M/41.5M [05:57<06:37, 68.8kB/s]
37%|###7 | 15.4M/41.5M [05:57<06:12, 73.4kB/s]
37%|###7 | 15.4M/41.5M [05:58<08:18, 54.8kB/s]
37%|###7 | 15.4M/41.5M [05:58<08:31, 53.4kB/s]
37%|###7 | 15.5M/41.5M [05:58<08:53, 51.2kB/s]
37%|###7 | 15.5M/41.5M [05:59<10:45, 42.2kB/s]
37%|###7 | 15.5M/41.5M [05:59<10:32, 43.1kB/s]
37%|###7 | 15.5M/41.5M [05:59<10:21, 43.9kB/s]
37%|###7 | 15.5M/41.5M [06:00<19:36, 23.2kB/s]
37%|###7 | 15.5M/41.5M [06:00<19:33, 23.2kB/s]
37%|###7 | 15.5M/41.5M [06:01<19:29, 23.3kB/s]
37%|###7 | 15.5M/41.5M [06:01<16:46, 27.1kB/s]
37%|###7 | 15.5M/41.5M [06:01<17:30, 25.9kB/s]
37%|###7 | 15.5M/41.5M [06:01<15:14, 29.8kB/s]
37%|###7 | 15.5M/41.5M
[06:01<13:36, 33.3kB/s]
37%|###7 | 15.5M/41.5M [06:02<12:27, 36.4kB/s]
37%|###7 | 15.6M/41.5M [06:02<14:29, 31.3kB/s]
38%|###7 | 15.6M/41.5M [06:02<10:03, 45.0kB/s]
38%|###7 | 15.6M/41.5M [06:02<09:57, 45.5kB/s]
38%|###7 | 15.6M/41.5M [06:03<07:50, 57.7kB/s]
38%|###7 | 15.6M/41.5M [06:03<08:14, 54.8kB/s]
38%|###7 | 15.6M/41.5M [06:03<08:35, 52.6kB/s]
38%|###7 | 15.6M/41.5M [06:03<09:01, 50.1kB/s]
38%|###7 | 15.6M/41.5M [06:04<09:14, 48.9kB/s]
38%|###7 | 15.6M/41.5M [06:04<09:19, 48.4kB/s]
38%|###7 | 15.7M/41.5M [06:04<07:38, 59.1kB/s]
38%|###7 | 15.7M/41.5M [06:04<10:05, 44.7kB/s]
38%|###7 | 15.7M/41.5M [06:04<08:05, 55.7kB/s]
38%|###7 | 15.7M/41.5M [06:05<08:25, 53.5kB/s]
38%|###7 | 15.7M/41.5M [06:05<08:41, 51.8kB/s]
38%|###7 | 15.7M/41.5M [06:05<10:58, 41.0kB/s]
38%|###7 | 15.7M/41.5M [06:06<10:28, 43.0kB/s]
38%|###7 | 15.8M/41.5M [06:06<08:31, 52.7kB/s]
38%|###7 | 15.8M/41.5M [06:06<10:37, 42.3kB/s]
38%|###7 | 15.8M/41.5M [06:06<10:23, 43.3kB/s]
38%|###8 | 15.8M/41.5M [06:07<14:46, 30.4kB/s]
38%|###8 | 15.8M/41.5M [06:07<10:43, 41.9kB/s]
38%|###8 | 15.8M/41.5M [06:07<11:01, 40.7kB/s]
38%|###8 | 15.8M/41.5M [06:07<10:40, 42.0kB/s]
38%|###8 | 15.8M/41.5M [06:08<10:23, 43.2kB/s]
38%|###8 | 15.8M/41.5M [06:08<10:10, 44.1kB/s]
38%|###8 | 15.8M/41.5M [06:08<09:59, 44.9kB/s]
38%|###8 | 15.8M/41.5M [06:08<11:53, 37.7kB/s]
38%|###8 | 15.8M/41.5M [06:08<11:12, 40.0kB/s]
38%|###8 | 15.9M/41.5M [06:09<10:43, 41.8kB/s]
38%|###8 | 15.9M/41.5M [06:09<13:11, 33.9kB/s]
38%|###8 | 15.9M/41.5M [06:09<09:20, 47.9kB/s]
38%|###8 | 15.9M/41.5M [06:10<11:44, 38.1kB/s]
38%|###8 | 15.9M/41.5M [06:10<11:10, 40.1kB/s]
38%|###8 | 15.9M/41.5
M [06:10<10:28, 42.7kB/s]
38%|###8 | 15.9M/41.5M [06:10<10:15, 43.6kB/s]
38%|###8 | 15.9M/41.5M [06:10<10:04, 44.4kB/s]
38%|###8 | 15.9M/41.5M [06:11<09:55, 45.0kB/s]
38%|###8 | 15.9M/41.5M [06:11<09:49, 45.5kB/s]
38%|###8 | 15.9M/41.5M [06:11<12:24, 36.0kB/s]
38%|###8 | 16.0M/41.5M [06:11<09:00, 49.5kB/s]
38%|###8 | 16.0M/41.5M [06:11<09:07, 48.9kB/s]
39%|###8 | 16.0M/41.5M [06:12<09:13, 48.3kB/s]
39%|###8 | 16.0M/41.5M [06:12<11:50, 37.6kB/s]
39%|###8 | 16.0M/41.5M [06:12<07:12, 61.8kB/s]
39%|###8 | 16.0M/41.5M [06:12<07:40, 58.1kB/s]
39%|###8 | 16.0M/41.5M [06:12<08:04, 55.1kB/s]
39%|###8 | 16.0M/41.5M [06:13<08:25, 52.8kB/s]
39%|###8 | 16.0M/41.5M [06:13<08:41, 51.2kB/s]
39%|###8 | 16.1M/41.5M [06:13<07:00, 63.4kB/s]
39%|###8 | 16.1M/41.5M [06:13<09:47, 45.4kB/s]
39%|###8 | 16.1M/41.5M [06:14<09:42, 45.7kB/s]
39%|###8 | 16.1M/41.5M [06:14<07:38, 58.1kB/s]
39%|###8 | 16.1M/41.5M [06:14<08:03, 55.1kB/s]
39%|###8 | 16.1M/41.5M [06:14<06:44, 65.8kB/s]
39%|###8 | 16.1M/41.5M [06:14<09:25, 47.1kB/s]
39%|###8 | 16.1M/41.5M [06:15<07:36, 58.3kB/s]
39%|###8 | 16.1M/41.5M [06:15<10:02, 44.1kB/s]
39%|###8 | 16.2M/41.5M [06:15<08:00, 55.3kB/s]
39%|###8 | 16.2M/41.5M [06:15<08:18, 53.2kB/s]
39%|###8 | 16.2M/41.5M [06:15<08:34, 51.6kB/s]
39%|###8 | 16.2M/41.5M [06:16<08:47, 50.3kB/s]
39%|###9 | 16.2M/41.5M [06:16<09:03, 48.8kB/s]
39%|###9 | 16.2M/41.5M [06:16<09:08, 48.4kB/s]
39%|###9 | 16.2M/41.5M [06:16<09:12, 48.0kB/s]
39%|###9 | 16.2M/41.5M [06:17<09:17, 47.5kB/s]
39%|###9 | 16.2M/41.5M [06:17<09:45, 45.2kB/s]
39%|###9 | 16.2M/41.5M [06:17<09:12, 47.9kB/s]
39%|###9 | 16.3M/41.5M [06:17<09:15, 47.7kB/s]
39%|###9 | 16.3M/41.
5M [06:18<11:37, 37.9kB/s]
39%|###9 | 16.3M/41.5M [06:18<11:02, 39.9kB/s]
39%|###9 | 16.3M/41.5M [06:18<10:35, 41.6kB/s]
39%|###9 | 16.3M/41.5M [06:18<10:15, 42.9kB/s]
39%|###9 | 16.3M/41.5M [06:18<10:00, 44.0kB/s]
39%|###9 | 16.3M/41.5M [06:19<15:16, 28.8kB/s]
39%|###9 | 16.3M/41.5M [06:19<14:43, 29.9kB/s]
39%|###9 | 16.3M/41.5M [06:20<16:14, 27.1kB/s]
39%|###9 | 16.3M/41.5M [06:20<14:27, 30.4kB/s]
39%|###9 | 16.3M/41.5M [06:20<15:37, 28.1kB/s]
39%|###9 | 16.4M/41.5M [06:21<13:52, 31.7kB/s]
39%|###9 | 16.4M/41.5M [06:21<15:15, 28.8kB/s]
39%|###9 | 16.4M/41.5M [06:21<13:33, 32.4kB/s]
39%|###9 | 16.4M/41.5M [06:21<15:04, 29.1kB/s]
39%|###9 | 16.4M/41.5M [06:22<16:08, 27.2kB/s]
40%|###9 | 16.4M/41.5M [06:22<14:07, 31.0kB/s]
40%|###9 | 16.4M/41.5M [06:22<16:13, 27.0kB/s]
40%|###9 | 16.4M/41.5M [06:23<14:10, 30.9kB/s]
40%|###9 | 16.4M/41.5M [06:23<12:44, 34.4kB/s]
40%|###9 | 16.4M/41.5M [06:23<14:30, 30.2kB/s]
40%|###9 | 16.4M/41.5M [06:23<15:45, 27.8kB/s]
40%|###9 | 16.4M/41.5M [06:24<12:47, 34.2kB/s]
40%|###9 | 16.5M/41.5M [06:24<11:56, 36.7kB/s]
40%|###9 | 16.5M/41.5M [06:24<11:15, 38.9kB/s]
40%|###9 | 16.5M/41.5M [06:24<10:43, 40.8kB/s]
40%|###9 | 16.5M/41.5M [06:25<12:56, 33.8kB/s]
40%|###9 | 16.5M/41.5M [06:25<07:34, 57.6kB/s]
40%|###9 | 16.5M/41.5M [06:25<07:56, 55.0kB/s]
40%|###9 | 16.5M/41.5M [06:25<08:15, 52.9kB/s]
40%|###9 | 16.5M/41.5M [06:25<08:30, 51.3kB/s]
40%|###9 | 16.5M/41.5M [06:26<06:55, 63.0kB/s]
40%|###9 | 16.5M/41.5M [06:26<07:27, 58.4kB/s]
40%|###9 | 16.6M/41.5M [06:26<07:54, 55.1kB/s]
40%|###9 | 16.6M/41.5M [06:26<08:15, 52.7kB/s]
40%|###9 | 16.6M/41.5M [06:26<08:32, 51.0kB/s]
40%|###9 | 16.6M/41
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40%|###9 | 16.6M/41.5M [06:27<08:54, 48.9kB/s]
40%|#### | 16.6M/41.5M [06:27<06:59, 62.3kB/s]
40%|#### | 16.6M/41.5M [06:27<07:32, 57.7kB/s]
40%|#### | 16.6M/41.5M [06:27<12:45, 34.1kB/s]
40%|#### | 16.6M/41.5M [06:28<09:18, 46.6kB/s]
40%|#### | 16.6M/41.5M [06:28<11:27, 37.9kB/s]
40%|#### | 16.6M/41.5M [06:28<10:54, 39.8kB/s]
40%|#### | 16.7M/41.5M [06:29<15:20, 28.3kB/s]
40%|#### | 16.7M/41.5M [06:29<21:39, 20.0kB/s]
40%|#### | 16.7M/41.5M [06:30<23:21, 18.6kB/s]
40%|#### | 16.7M/41.5M [06:30<21:58, 19.7kB/s]
40%|#### | 16.7M/41.5M [06:31<26:19, 16.5kB/s]
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40%|#### | 16.7M/41.5M [06:31<20:28, 21.2kB/s]
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40%|#### | 16.7M/41.5M [06:32<13:04, 33.1kB/s]
40%|#### | 16.7M/41.5M [06:33<12:07, 35.7kB/s]
40%|#### | 16.8M/41.5M [06:33<11:57, 36.2kB/s]
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40%|#### | 16.8M/41.5M [06:33<10:14, 42.2kB/s]
40%|#### | 16.8M/41.5M [06:33<09:56, 43.4kB/s]
40%|#### | 16.8M/41.5M [06:34<11:45, 36.7kB/s]
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41%|#### | 16.8M/41.5M [06:34<09:03, 47.6kB/s]
41%|#### | 16.8M/41.5M [06:34<11:29, 37.5kB/s]
41%|#### | 16.8M/41.5M [06:35<13:21, 32.3kB/s]
41%|#### | 16.9M/41.5M [06:35<07:50, 54.9kB/s]
41%|#### | 16.9M/41.5M [06:35<08:06, 53.0kB/s]
41%|#### | 16.9M/41.5M [06:36<10:25, 41.3kB/s]
41%|#### | 16.9M/41.5M [06:36<09:55, 43.3kB/s]
41%|#### | 16.9M/41.5M [06:36<09:45, 44.0kB/s]
41%|#### | 16.9M/41.5M [06:36<09:37, 44.7kB/s]
41%|#### | 16.9M/4
1.5M [06:36<07:34, 56.7kB/s]
41%|#### | 16.9M/41.5M [06:37<07:55, 54.1kB/s]
41%|#### | 16.9M/41.5M [06:37<08:13, 52.2kB/s]
41%|#### | 16.9M/41.5M [06:37<06:43, 63.7kB/s]
41%|#### | 17.0M/41.5M [06:37<09:51, 43.5kB/s]
41%|#### | 17.0M/41.5M [06:38<06:57, 61.6kB/s]
41%|#### | 17.0M/41.5M [06:38<09:53, 43.3kB/s]
41%|#### | 17.0M/41.5M [06:39<09:59, 42.8kB/s]
41%|####1 | 17.0M/41.5M [06:39<08:40, 49.3kB/s]
41%|####1 | 17.0M/41.5M [06:39<08:45, 48.8kB/s]
41%|####1 | 17.0M/41.5M [06:39<08:49, 48.4kB/s]
41%|####1 | 17.0M/41.5M [06:40<17:21, 24.6kB/s]
41%|####1 | 17.1M/41.5M [06:40<10:07, 42.1kB/s]
41%|####1 | 17.1M/41.5M [06:41<11:39, 36.6kB/s]
41%|####1 | 17.1M/41.5M [06:41<11:06, 38.4kB/s]
41%|####1 | 17.1M/41.5M [06:41<10:38, 40.1kB/s]
41%|####1 | 17.1M/41.5M [06:41<08:11, 52.0kB/s]
41%|####1 | 17.1M/41.5M [06:42<12:25, 34.3kB/s]
41%|####1 | 17.1M/41.5M [06:42<09:21, 45.5kB/s]
41%|####1 | 17.1M/41.5M [06:42<09:17, 45.8kB/s]
41%|####1 | 17.1M/41.5M [06:42<09:14, 46.0kB/s]
41%|####1 | 17.2M/41.5M [06:42<11:30, 36.9kB/s]
41%|####1 | 17.2M/41.5M [06:43<07:05, 59.9kB/s]
41%|####1 | 17.2M/41.5M [06:43<11:04, 38.3kB/s]
41%|####1 | 17.2M/41.5M [06:43<10:37, 39.9kB/s]
41%|####1 | 17.2M/41.5M [06:44<10:00, 42.4kB/s]
42%|####1 | 17.2M/41.5M [06:44<09:48, 43.3kB/s]
42%|####1 | 17.2M/41.5M [06:44<09:37, 44.1kB/s]
42%|####1 | 17.2M/41.5M [06:44<09:28, 44.7kB/s]
42%|####1 | 17.2M/41.5M [06:44<09:21, 45.3kB/s]
42%|####1 | 17.3M/41.5M [06:45<09:40, 43.8kB/s]
42%|####1 | 17.3M/41.5M [06:45<07:18, 57.9kB/s]
42%|####1 | 17.3M/41.5M [06:45<07:41, 55.0kB/s]
42%|####1 | 17.3M/41.5M [06:45<07:59, 52.9kB/s]
42%|####1 | 17.3M/41.5M [06:45<08:14, 51.3kB/s]
42%|####1 | 17.3M/
41.5M [06:46<08:26, 50.0kB/s]
42%|####1 | 17.3M/41.5M [06:46<08:35, 49.1kB/s]
42%|####1 | 17.3M/41.5M [06:46<06:48, 62.1kB/s]
42%|####1 | 17.3M/41.5M [06:46<07:19, 57.6kB/s]
42%|####1 | 17.4M/41.5M [06:46<08:00, 52.7kB/s]
42%|####1 | 17.4M/41.5M [06:47<06:42, 62.8kB/s]
42%|####1 | 17.4M/41.5M [06:47<09:03, 46.5kB/s]
42%|####1 | 17.4M/41.5M [06:47<06:11, 68.0kB/s]
42%|####1 | 17.4M/41.5M [06:47<06:42, 62.8kB/s]
42%|####1 | 17.4M/41.5M [06:48<07:10, 58.6kB/s]
42%|####1 | 17.4M/41.5M [06:48<07:34, 55.5kB/s]
42%|####2 | 17.4M/41.5M [06:48<14:55, 28.2kB/s]
42%|####2 | 17.4M/41.5M [06:49<10:19, 40.7kB/s]
42%|####2 | 17.5M/41.5M [06:49<08:09, 51.5kB/s]
42%|####2 | 17.5M/41.5M [06:49<08:19, 50.5kB/s]
42%|####2 | 17.5M/41.5M [06:49<06:52, 61.0kB/s]
42%|####2 | 17.5M/41.5M [06:49<07:18, 57.4kB/s]
42%|####2 | 17.5M/41.5M [06:50<09:47, 42.8kB/s
]
42%|####2 | 17.5M/41.5M [06:50<06:23, 65.5kB/s]
42%|####2 | 17.5M/41.5M [06:50<06:52, 60.9kB/s]
42%|####2 | 17.5M/41.5M [06:51<09:10, 45.6kB/s]
42%|####2 | 17.6M/41.5M [06:51<09:05, 46.0kB/s]
42%|####2 | 17.6M/41.5M [06:51<09:02, 46.2kB/s]
42%|####2 | 17.6M/41.5M [06:52<09:00, 46.4kB/s]
42%|####2 | 17.6M/41.5M [06:52<08:58, 46.5kB/s]
42%|####2 | 17.6M/41.5M [06:52<08:57, 46.6kB/s]
42%|####2 | 17.6M/41.5M [06:52<08:56, 46.6kB/s]
42%|####2 | 17.6M/41.5M [06:52<08:55, 46.7kB/s]
43%|####2 | 17.6M/41.5M [06:52<07:04, 58.9kB/s]
43%|####2 | 17.6M/41.5M [06:53<07:29, 55.6kB/s]
43%|####2 | 17.7M/41.5M [06:53<10:00, 41.6kB/s]
43%|####2 | 17.7M/41.5M [06:53<12:01, 34.6kB/s]
43%|####2 | 17.7M/41.5M [06:53<08:47, 47.3kB/s]
43%|####2 | 17.7M/41.5M [06:54<08:48, 47.2kB/s]
43%|####2 | 17.7M/41.5M [06:54<08:49, 47.1kB/s]
43%|####2 | 17.7M
/41.5M [06:54<08:50, 47.0kB/s]
43%|####2 | 17.7M/41.5M [06:55<10:30, 39.5kB/s]
43%|####2 | 17.7M/41.5M [06:55<12:01, 34.5kB/s]
43%|####2 | 17.8M/41.5M [06:55<09:09, 45.3kB/s]
43%|####2 | 17.8M/41.5M [06:55<09:05, 45.6kB/s]
43%|####2 | 17.8M/41.5M [06:56<09:02, 45.9kB/s]
43%|####2 | 17.8M/41.5M [06:56<08:59, 46.1kB/s]
43%|####2 | 17.8M/41.5M [06:56<08:56, 46.3kB/s]
43%|####2 | 17.8M/41.5M [06:56<11:19, 36.6kB/s]
43%|####2 | 17.8M/41.5M [06:56<10:37, 39.0kB/s]
43%|####2 | 17.8M/41.5M [06:57<07:51, 52.7kB/s]
43%|####2 | 17.8M/41.5M [06:57<08:05, 51.1kB/s]
43%|####2 | 17.8M/41.5M [06:57<12:48, 32.3kB/s]
43%|####3 | 17.8M/41.5M [06:58<11:07, 37.1kB/s]
43%|####3 | 17.9M/41.5M [06:58<10:15, 40.3kB/s]
43%|####3 | 17.9M/41.5M [06:58<09:56, 41.5kB/s]
43%|####3 | 17.9M/41.5M [06:58<09:40, 42.7kB/s]
43%|####3 | 17.9M/41.5M [06:59<11:39, 35.4kB/
s]
43%|####3 | 17.9M/41.5M [06:59<10:54, 37.8kB/s]
43%|####3 | 17.9M/41.5M [06:59<13:19, 31.0kB/s]
43%|####3 | 17.9M/41.5M [06:59<11:26, 36.0kB/s]
43%|####3 | 17.9M/41.5M [07:00<10:40, 38.6kB/s]
43%|####3 | 17.9M/41.5M [07:00<11:40, 35.3kB/s]
43%|####3 | 17.9M/41.5M [07:00<10:49, 38.0kB/s]
43%|####3 | 17.9M/41.5M [07:00<12:48, 32.1kB/s]
43%|####3 | 18.0M/41.5M [07:01<09:45, 42.2kB/s]
43%|####3 | 18.0M/41.5M [07:01<09:30, 43.2kB/s]
43%|####3 | 18.0M/41.5M [07:01<10:02, 40.9kB/s]
43%|####3 | 18.0M/41.5M [07:02<15:40, 26.2kB/s]
43%|####3 | 18.0M/41.5M [07:03<17:12, 23.8kB/s]
43%|####3 | 18.0M/41.5M [07:03<10:47, 38.0kB/s]
43%|####3 | 18.0M/41.5M [07:04<14:56, 27.4kB/s]
43%|####3 | 18.0M/41.5M [07:04<12:53, 31.8kB/s]
44%|####3 | 18.1M/41.5M [07:04<12:06, 33.8kB/s]
44%|####3 | 18.1M/41.5M [07:04<11:22, 36.0kB/s]
44%|####3 | 18.1
M/41.5M [07:05<10:45, 38.0kB/s]
44%|####3 | 18.1M/41.5M [07:05<10:14, 39.9kB/s]
44%|####3 | 18.1M/41.5M [07:05<09:50, 41.5kB/s]
44%|####3 | 18.1M/41.5M [07:05<09:34, 42.7kB/s]
44%|####3 | 18.1M/41.5M [07:06<11:06, 36.8kB/s]
44%|####3 | 18.1M/41.5M [07:06<07:07, 57.3kB/s]
44%|####3 | 18.1M/41.5M [07:06<07:25, 55.0kB/s]
44%|####3 | 18.1M/41.5M [07:06<09:59, 40.8kB/s]
44%|####3 | 18.2M/41.5M [07:06<07:27, 54.6kB/s]
44%|####3 | 18.2M/41.5M [07:07<07:43, 52.8kB/s]
44%|####3 | 18.2M/41.5M [07:07<09:58, 40.9kB/s]
44%|####3 | 18.2M/41.5M [07:07<13:59, 29.1kB/s]
44%|####3 | 18.2M/41.5M [07:08<09:58, 40.8kB/s]
44%|####3 | 18.2M/41.5M [07:08<11:40, 34.9kB/s]
44%|####3 | 18.2M/41.5M [07:08<13:04, 31.1kB/s]
44%|####3 | 18.2M/41.5M [07:09<09:27, 43.0kB/s]
44%|####3 | 18.2M/41.5M [07:09<09:16, 43.8kB/s]
44%|####3 | 18.2M/41.5M [07:09<09:07, 44.5kB
/s]
44%|####4 | 18.3M/41.5M [07:09<09:00, 45.1kB/s]
44%|####4 | 18.3M/41.5M [07:09<11:14, 36.1kB/s]
44%|####4 | 18.3M/41.5M [07:10<12:00, 33.8kB/s]
44%|####4 | 18.3M/41.5M [07:10<09:02, 44.8kB/s]
44%|####4 | 18.3M/41.5M [07:10<08:57, 45.2kB/s]
44%|####4 | 18.3M/41.5M [07:11<10:54, 37.1kB/s]
44%|####4 | 18.3M/41.5M [07:11<12:30, 32.4kB/s]
44%|####4 | 18.3M/41.5M [07:11<13:46, 29.4kB/s]
44%|####4 | 18.3M/41.5M [07:12<15:16, 26.5kB/s]
44%|####4 | 18.4M/41.5M [07:12<13:42, 29.5kB/s]
44%|####4 | 18.4M/41.5M [07:12<12:44, 31.7kB/s]
44%|####4 | 18.4M/41.5M [07:13<13:36, 29.7kB/s]
44%|####4 | 18.4M/41.5M [07:13<12:14, 33.0kB/s]
44%|####4 | 18.4M/41.5M [07:13<11:33, 35.0kB/s]
44%|####4 | 18.4M/41.5M [07:14<15:18, 26.4kB/s]
44%|####4 | 18.4M/41.5M [07:14<10:21, 39.0kB/s]
44%|####4 | 18.4M/41.5M [07:14<14:06, 28.6kB/s]
44%|####4 | 18.
4M/41.5M [07:15<10:37, 37.9kB/s]
44%|####4 | 18.4M/41.5M [07:15<10:09, 39.7kB/s]
44%|####4 | 18.4M/41.5M [07:15<09:46, 41.2kB/s]
44%|####4 | 18.5M/41.5M [07:15<09:27, 42.5kB/s]
44%|####4 | 18.5M/41.5M [07:15<09:14, 43.6kB/s]
45%|####4 | 18.5M/41.5M [07:15<09:02, 44.5kB/s]
45%|####4 | 18.5M/41.5M [07:16<08:54, 45.1kB/s]
45%|####4 | 18.5M/41.5M [07:16<08:48, 45.6kB/s]
45%|####4 | 18.5M/41.5M [07:16<08:44, 46.0kB/s]
45%|####4 | 18.5M/41.5M [07:16<09:29, 42.4kB/s]
45%|####4 | 18.5M/41.5M [07:17<10:24, 38.6kB/s]
45%|####4 | 18.5M/41.5M [07:17<07:59, 50.2kB/s]
45%|####4 | 18.5M/41.5M [07:17<08:06, 49.4kB/s]
45%|####4 | 18.5M/41.5M [07:17<08:13, 48.8kB/s]
45%|####4 | 18.6M/41.5M [07:17<08:18, 48.3kB/s]
45%|####4 | 18.6M/41.5M [07:18<08:21, 47.9kB/s]
45%|####4 | 18.6M/41.5M [07:18<08:24, 47.6kB/s]
45%|####4 | 18.6M/41.5M [07:18<08:26, 47.4k
B/s]
45%|####4 | 18.6M/41.5M [07:18<08:28, 47.2kB/s]
45%|####4 | 18.6M/41.5M [07:19<16:21, 24.5kB/s]
45%|####4 | 18.6M/41.5M [07:19<13:41, 29.2kB/s]
45%|####4 | 18.6M/41.5M [07:19<09:23, 42.6kB/s]
45%|####4 | 18.6M/41.5M [07:19<07:35, 52.6kB/s]
45%|####4 | 18.6M/41.5M [07:20<09:40, 41.3kB/s]
45%|####4 | 18.7M/41.5M [07:20<07:20, 54.3kB/s]
45%|####4 | 18.7M/41.5M [07:20<07:35, 52.5kB/s]
45%|####5 | 18.7M/41.5M [07:20<07:48, 51.1kB/s]
45%|####5 | 18.7M/41.5M [07:20<07:58, 49.9kB/s]
45%|####5 | 18.7M/41.5M [07:20<08:07, 49.1kB/s]
45%|####5 | 18.7M/41.5M [07:21<08:13, 48.5kB/s]
45%|####5 | 18.7M/41.5M [07:21<10:41, 37.2kB/s]
45%|####5 | 18.7M/41.5M [07:21<10:03, 39.6kB/s]
45%|####5 | 18.7M/41.5M [07:22<09:48, 40.5kB/s]
45%|####5 | 18.7M/41.5M [07:22<10:32, 37.7kB/s]
45%|####5 | 18.8M/41.5M [07:22<10:05, 39.4kB/s]
45%|####5 | 18
.8M/41.5M [07:23<11:43, 33.9kB/s]
45%|####5 | 18.8M/41.5M [07:23<10:53, 36.4kB/s]
45%|####5 | 18.8M/41.5M [07:23<12:30, 31.8kB/s]
45%|####5 | 18.8M/41.5M [07:23<11:23, 34.9kB/s]
45%|####5 | 18.8M/41.5M [07:23<08:14, 48.2kB/s]
45%|####5 | 18.8M/41.5M [07:24<10:18, 38.5kB/s]
45%|####5 | 18.8M/41.5M [07:24<11:59, 33.1kB/s]
45%|####5 | 18.8M/41.5M [07:24<11:02, 35.9kB/s]
45%|####5 | 18.8M/41.5M [07:24<10:19, 38.4kB/s]
45%|####5 | 18.8M/41.5M [07:25<09:47, 40.4kB/s]
45%|####5 | 18.8M/41.5M [07:25<09:24, 42.1kB/s]
45%|####5 | 18.9M/41.5M [07:25<09:07, 43.4kB/s]
45%|####5 | 18.9M/41.5M [07:25<08:55, 44.3kB/s]
45%|####5 | 18.9M/41.5M [07:26<11:16, 35.1kB/s]
46%|####5 | 18.9M/41.5M [07:26<09:24, 42.0kB/s]
46%|####5 | 18.9M/41.5M [07:26<11:50, 33.3kB/s]
46%|####5 | 18.9M/41.5M [07:27<12:10, 32.4kB/s]
46%|####5 | 18.9M/41.5M [07:27<11:18, 34.9
kB/s]
46%|####5 | 18.9M/41.5M [07:27<10:35, 37.2kB/s]
46%|####5 | 18.9M/41.5M [07:28<14:25, 27.3kB/s]
46%|####5 | 18.9M/41.5M [07:28<12:47, 30.8kB/s]
46%|####5 | 18.9M/41.5M [07:28<13:54, 28.3kB/s]
46%|####5 | 19.0M/41.5M [07:28<13:03, 30.2kB/s]
46%|####5 | 19.0M/41.5M [07:29<11:42, 33.6kB/s]
46%|####5 | 19.0M/41.5M [07:29<12:27, 31.6kB/s]
46%|####5 | 19.0M/41.5M [07:29<13:44, 28.6kB/s]
46%|####5 | 19.0M/41.5M [07:30<11:51, 33.2kB/s]
46%|####5 | 19.0M/41.5M [07:30<11:00, 35.7kB/s]
46%|####5 | 19.0M/41.5M [07:30<12:29, 31.4kB/s]
46%|####5 | 19.0M/41.5M [07:30<10:44, 36.6kB/s]
46%|####5 | 19.0M/41.5M [07:31<10:10, 38.5kB/s]
46%|####5 | 19.0M/41.5M [07:31<09:43, 40.3kB/s]
46%|####5 | 19.0M/41.5M [07:31<11:34, 33.9kB/s]
46%|####5 | 19.1M/41.5M [07:31<08:23, 46.7kB/s]
46%|####5 | 19.1M/41.5M [07:32<08:23, 46.7kB/s]
46%|####5 | 1
9.1M/41.5M [07:32<10:28, 37.4kB/s]
46%|####6 | 19.1M/41.5M [07:32<09:55, 39.5kB/s]
46%|####6 | 19.1M/41.5M [07:33<14:03, 27.8kB/s]
46%|####6 | 19.1M/41.5M [07:33<11:32, 33.9kB/s]
46%|####6 | 19.1M/41.5M [07:33<10:46, 36.3kB/s]
46%|####6 | 19.1M/41.5M [07:33<12:16, 31.8kB/s]
46%|####6 | 19.1M/41.5M [07:34<08:51, 44.1kB/s]
46%|####6 | 19.1M/41.5M [07:34<08:44, 44.7kB/s]
46%|####6 | 19.2M/41.5M [07:34<08:37, 45.2kB/s]
46%|####6 | 19.2M/41.5M [07:34<10:43, 36.4kB/s]
46%|####6 | 19.2M/41.5M [07:35<10:04, 38.7kB/s]
46%|####6 | 19.2M/41.5M [07:35<14:14, 27.4kB/s]
46%|####6 | 19.2M/41.5M [07:35<11:36, 33.6kB/s]
46%|####6 | 19.2M/41.5M [07:36<10:48, 36.0kB/s]
46%|####6 | 19.2M/41.5M [07:36<10:09, 38.3kB/s]
46%|####6 | 19.2M/41.5M [07:36<09:39, 40.3kB/s]
46%|####6 | 19.2M/41.5M [07:36<09:17, 41.9kB/s]
46%|####6 | 19.2M/41.5M [07:36<09:00, 43.
2kB/s]
46%|####6 | 19.2M/41.5M [07:37<11:11, 34.8kB/s]
46%|####6 | 19.2M/41.5M [07:37<10:20, 37.6kB/s]
46%|####6 | 19.3M/41.5M [07:37<09:44, 39.9kB/s]
46%|####6 | 19.3M/41.5M [07:37<09:18, 41.7kB/s]
46%|####6 | 19.3M/41.5M [07:37<09:00, 43.1kB/s]
46%|####6 | 19.3M/41.5M [07:37<08:47, 44.2kB/s]
46%|####6 | 19.3M/41.5M [07:38<13:34, 28.6kB/s]
47%|####6 | 19.3M/41.5M [07:38<09:02, 42.8kB/s]
47%|####6 | 19.3M/41.5M [07:39<08:52, 43.6kB/s]
47%|####6 | 19.3M/41.5M [07:39<09:11, 42.1kB/s]
47%|####6 | 19.3M/41.5M [07:39<08:57, 43.2kB/s]
47%|####6 | 19.3M/41.5M [07:39<10:25, 37.1kB/s]
47%|####6 | 19.4M/41.5M [07:39<09:49, 39.4kB/s]
47%|####6 | 19.4M/41.5M [07:40<09:23, 41.2kB/s]
47%|####6 | 19.4M/41.5M [07:40<08:20, 46.3kB/s]
47%|####6 | 19.4M/41.5M [07:40<08:18, 46.5kB/s]
47%|####6 | 19.4M/41.5M [07:40<08:18, 46.5kB/s]
47%|####6 |
19.4M/41.5M [07:40<09:01, 42.8kB/s]
47%|####6 | 19.4M/41.5M [07:40<08:02, 48.0kB/s]
47%|####6 | 19.4M/41.5M [07:41<08:05, 47.7kB/s]
47%|####6 | 19.4M/41.5M [07:41<08:08, 47.4kB/s]
47%|####6 | 19.4M/41.5M [07:41<08:09, 47.3kB/s]
47%|####6 | 19.4M/41.5M [07:41<08:07, 47.5kB/s]
47%|####6 | 19.4M/41.5M [07:41<06:18, 61.0kB/s]
47%|####6 | 19.5M/41.5M [07:42<08:46, 43.9kB/s]
47%|####6 | 19.5M/41.5M [07:42<08:59, 42.8kB/s]
47%|####6 | 19.5M/41.5M [07:42<08:48, 43.7kB/s]
47%|####6 | 19.5M/41.5M [07:42<08:39, 44.4kB/s]
47%|####6 | 19.5M/41.5M [07:43<08:32, 45.0kB/s]
47%|####6 | 19.5M/41.5M [07:43<08:26, 45.5kB/s]
47%|####7 | 19.5M/41.5M [07:43<12:56, 29.7kB/s]
47%|####7 | 19.5M/41.5M [07:43<09:00, 42.6kB/s]
47%|####7 | 19.5M/41.5M [07:44<08:48, 43.5kB/s]
47%|####7 | 19.5M/41.5M [07:44<08:39, 44.3kB/s]
47%|####7 | 19.5M/41.5M [07:44<08:31, 45
.0kB/s]
47%|####7 | 19.6M/41.5M [07:44<08:25, 45.5kB/s]
47%|####7 | 19.6M/41.5M [07:44<08:21, 45.9kB/s]
47%|####7 | 19.6M/41.5M [07:44<08:17, 46.2kB/s]
47%|####7 | 19.6M/41.5M [07:45<08:40, 44.2kB/s]
47%|####7 | 19.6M/41.5M [07:45<08:05, 47.3kB/s]
47%|####7 | 19.6M/41.5M [07:45<08:06, 47.2kB/s]
47%|####7 | 19.6M/41.5M [07:45<08:07, 47.0kB/s]
47%|####7 | 19.6M/41.5M [07:46<08:07, 47.1kB/s]
47%|####7 | 19.6M/41.5M [07:46<08:07, 47.0kB/s]
47%|####7 | 19.6M/41.5M [07:46<07:13, 52.9kB/s]
47%|####7 | 19.6M/41.5M [07:46<08:24, 45.4kB/s]
47%|####7 | 19.6M/41.5M [07:46<10:43, 35.6kB/s]
47%|####7 | 19.7M/41.5M [07:47<07:41, 49.6kB/s]
47%|####7 | 19.7M/41.5M [07:47<09:48, 38.9kB/s]
47%|####7 | 19.7M/41.5M [07:47<09:21, 40.7kB/s]
47%|####7 | 19.7M/41.5M [07:47<09:01, 42.2kB/s]
47%|####7 | 19.7M/41.5M [07:48<11:02, 34.5kB/s]
48%|####7 |
19.7M/41.5M [07:48<12:01, 31.6kB/s]
48%|####7 | 19.7M/41.5M [07:49<10:30, 36.2kB/s]
48%|####7 | 19.7M/41.5M [07:49<09:59, 38.1kB/s]
48%|####7 | 19.7M/41.5M [07:49<09:32, 39.9kB/s]
48%|####7 | 19.8M/41.5M [07:49<09:10, 41.4kB/s]
48%|####7 | 19.8M/41.5M [07:49<08:53, 42.7kB/s]
48%|####7 | 19.8M/41.5M [07:50<10:53, 34.8kB/s]
48%|####7 | 19.8M/41.5M [07:50<09:40, 39.2kB/s]
48%|####7 | 19.8M/41.5M [07:50<07:30, 50.5kB/s]
48%|####7 | 19.8M/41.5M [07:50<09:22, 40.4kB/s]
48%|####7 | 19.8M/41.5M [07:51<09:04, 41.8kB/s]
48%|####7 | 19.8M/41.5M [07:51<08:49, 42.9kB/s]
48%|####7 | 19.8M/41.5M [07:51<06:48, 55.5kB/s]
48%|####7 | 19.8M/41.5M [07:51<07:06, 53.3kB/s]
48%|####7 | 19.9M/41.5M [07:51<07:20, 51.5kB/s]
48%|####7 | 19.9M/41.5M [07:52<05:58, 63.3kB/s]
48%|####7 | 19.9M/41.5M [07:52<06:26, 58.6kB/s]
48%|####7 | 19.9M/41.5M [07:52<06:50, 5
5.2kB/s]
48%|####7 | 19.9M/41.5M [07:52<09:14, 40.8kB/s]
48%|####7 | 19.9M/41.5M [07:52<05:47, 65.2kB/s]
48%|####8 | 19.9M/41.5M [07:53<06:32, 57.6kB/s]
48%|####8 | 19.9M/41.5M [07:53<06:49, 55.2kB/s]
48%|####8 | 20.0M/41.5M [07:53<05:49, 64.6kB/s]
48%|####8 | 20.0M/41.5M [07:53<05:12, 72.2kB/s]
48%|####8 | 20.0M/41.5M [07:53<05:45, 65.3kB/s]
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48%|####8 | 20.0M/41.5M [07:54<05:41, 65.9kB/s]
48%|####8 | 20.0M/41.5M [07:54<06:08, 61.1kB/s]
48%|####8 | 20.0M/41.5M [07:54<05:22, 69.7kB/s]
48%|####8 | 20.0M/41.5M [07:54<05:54, 63.5kB/s]
48%|####8 | 20.0M/41.5M [07:55<08:10, 45.8kB/s]
48%|####8 | 20.1M/41.5M [07:55<05:28, 68.5kB/s]
48%|####8 | 20.1M/41.5M [07:55<05:56, 63.0kB/s]
48%|####8 | 20.1M/41.5M [07:55<05:15, 71.2kB/s]
48%|####8 | 20.1M/41.5M [07:56<05:47, 64.5kB/s]
48%|####8
| 20.1M/41.5M [07:56<05:08, 72.7kB/s]
49%|####8 | 20.1M/41.5M [07:56<04:44, 78.8kB/s]
49%|####8 | 20.1M/41.5M [07:56<05:22, 69.5kB/s]
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49%|####8 | 20.2M/41.5M [07:56<05:55, 62.9kB/s]
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49%|####8 | 20.3M/41.5M [07:58<06:02, 61.3kB/s]
49%|####8 | 20.3M/41.5M [07:58<05:20, 69.3kB/s]
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49.1kB/s]
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| 20.5M/41.5M [08:04<10:16, 35.7kB/s]
49%|####9 | 20.5M/41.5M [08:05<14:39, 25.0kB/s]
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50%|####9 | 20.6M/41.5M [08:07<09:47, 37.3kB/s]
50%|####9 | 20.6M/41.5M [08:07<09:19, 39.2kB/s]
50%|####9 | 20.6M/41.5M [08:07<12:49, 28.5kB/s]
50%|####9 | 20.6M/41.5M [08:07<09:06, 40.1kB/s]
50%|####9 | 20.6M/41.5M [08:08<08:48, 41.5kB/s]
50%|####9 | 20.6M/41.5M [08:08<08:32, 42.7kB/s]
50%|####9 | 20.6M/41.5M [08:09<16:45, 21.7kB/s]
50%|####9 | 20.6M/41.5M [08:09<11:02, 33.0kB/s]
50%|####9 | 20.7M/41.5M [08:09<10:16, 35.4kB/s]
50%|####9 | 20.7M/41.5M [08:10<13:31, 26.9kB/s]
50%|####9 | 20.7M/41.5M [08:10<10:06,
36.0kB/s]
50%|####9 | 20.7M/41.5M [08:10<09:33, 38.0kB/s]
50%|####9 | 20.7M/41.5M [08:10<09:06, 39.9kB/s]
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50%|####9 | 20.7M/41.5M [08:10<08:28, 42.8kB/s]
50%|####9 | 20.7M/41.5M [08:11<08:16, 43.9kB/s]
50%|####9 | 20.7M/41.5M [08:11<08:07, 44.7kB/s]
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50%|####9 | 20.7M/41.5M [08:11<07:20, 49.4kB/s]
50%|##### | 20.8M/41.5M [08:11<09:44, 37.2kB/s]
50%|##### | 20.8M/41.5M [08:12<08:48, 41.1kB/s]
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| 20.8M/41.5M [08:13<07:33, 47.8kB/s]
50%|##### | 20.9M/41.5M [08:14<05:56, 60.7kB/s]
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51%|##### | 21.0M/41.5M [08:15<04:50, 74.1kB/s]
51%|##### | 21.0M/41.5M [08:15<04:29, 79.9kB/s]
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51%|##### | 21.0M/41.5M [08:16<04:45, 75.3kB/s]
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51%|##### | 21.0M/41.5M [08:16<04:15, 83.8kB/s]
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51%|##### | 21.1M/41.5M [08:17<04:57
, 71.9kB/s]
51%|##### | 21.1M/41.5M [08:17<04:41, 75.9kB/s]
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51%|##### | 21.1M/41.5M [08:18<05:14, 67.9kB/s]
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51%|#####1 | 21.2M/41.5M [08:18<06:08, 57.8kB/s]
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51%|#####1 | 21.2M/41.5M [08:19<04:53, 72.5kB/s]
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51%|#####1 | 21.2M/41.5M [08:19<04:28, 79.0kB/s]
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51%|#####1 | 21.3M/41.5M [08:20<04:52, 72.5kB/s]
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| 21.4M/41.5M [08:22<05:55, 59.4kB/s]
52%|#####1 | 21.4M/41.5M [08:22<07:29, 46.9kB/s]
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52%|#####1 | 21.5M/41.5M [08:26<09:45, 35.8kB/s]
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0, 44.5kB/s]
52%|#####1 | 21.5M/41.5M [08:26<07:44, 45.0kB/s]
52%|#####1 | 21.6M/41.5M [08:27<07:39, 45.5kB/s]
52%|#####1 | 21.6M/41.5M [08:27<05:59, 58.1kB/s]
52%|#####2 | 21.6M/41.5M [08:27<06:18, 55.1kB/s]
52%|#####2 | 21.6M/41.5M [08:27<06:45, 51.4kB/s]
52%|#####2 | 21.6M/41.5M [08:28<05:38, 61.5kB/s]
52%|#####2 | 21.6M/41.5M [08:28<09:03, 38.3kB/s]
52%|#####2 | 21.6M/41.5M [08:28<07:04, 49.1kB/s]
52%|#####2 | 21.6M/41.5M [08:28<07:08, 48.6kB/s]
52%|#####2 | 21.6M/41.5M [08:29<07:11, 48.2kB/s]
52%|#####2 | 21.7M/41.5M [08:29<07:14, 47.8kB/s]
52%|#####2 | 21.7M/41.5M [08:29<07:16, 47.6kB/s]
52%|#####2 | 21.7M/41.5M [08:29<09:18, 37.2kB/s]
52%|#####2 | 21.7M/41.5M [08:30<10:50, 31.9kB/s]
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52%|#####2 | 21.7M/41.5M [08:30<07:32, 45.8kB/s]
52%|#####2
| 21.7M/41.5M [08:30<07:29, 46.1kB/s]
52%|#####2 | 21.7M/41.5M [08:31<07:27, 46.3kB/s]
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52%|#####2 | 21.8M/41.5M [08:31<07:54, 43.6kB/s]
52%|#####2 | 21.8M/41.5M [08:32<06:10, 55.8kB/s]
53%|#####2 | 21.8M/41.5M [08:32<06:25, 53.5kB/s]
53%|#####2 | 21.8M/41.5M [08:32<06:39, 51.7kB/s]
53%|#####2 | 21.8M/41.5M [08:32<06:49, 50.4kB/s]
53%|#####2 | 21.8M/41.5M [08:32<05:29, 62.7kB/s]
53%|#####2 | 21.8M/41.5M [08:33<07:37, 45.1kB/s]
53%|#####2 | 21.8M/41.5M [08:33<07:32, 45.5kB/s]
53%|#####2 | 21.9M/41.5M [08:33<05:55, 57.9kB/s]
53%|#####2 | 21.9M/41.5M [08:33<06:14, 54.9kB/s]
53%|#####2 | 21.9M/41.5M [08:33<06:30, 52.7kB/s]
53%|#####2 | 21.9M/41.5M [08:33<06:42, 51.0kB/s]
53%|#####2 | 21.9M/41.5M [08:34<05:
24, 63.4kB/s]
53%|#####2 | 21.9M/41.5M [08:34<05:50, 58.5kB/s]
53%|#####2 | 21.9M/41.5M [08:34<06:12, 55.1kB/s]
53%|#####2 | 21.9M/41.5M [08:34<05:45, 59.4kB/s]
53%|#####2 | 21.9M/41.5M [08:34<05:27, 62.7kB/s]
53%|#####2 | 21.9M/41.5M [08:34<05:13, 65.4kB/s]
53%|#####2 | 22.0M/41.5M [08:35<05:08, 66.3kB/s]
53%|#####2 | 22.0M/41.5M [08:35<04:35, 74.2kB/s]
53%|#####2 | 22.0M/41.5M [08:35<04:34, 74.6kB/s]
53%|#####3 | 22.0M/41.5M [08:35<03:59, 85.2kB/s]
53%|#####3 | 22.0M/41.5M [08:35<03:52, 87.7kB/s]
53%|#####3 | 22.0M/41.5M [08:36<03:48, 89.5kB/s]
53%|#####3 | 22.0M/41.5M [08:36<03:19, 102kB/s]
53%|#####3 | 22.1M/41.5M [08:36<03:24, 99.5kB/s]
53%|#####3 | 22.1M/41.5M [08:36<03:03, 111kB/s]
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53%|#####3 | 22.1M/41.5M [08:37<03:21, 101kB/s]
53%|#####
3 | 22.1M/41.5M [08:37<04:05, 82.5kB/s]
53%|#####3 | 22.2M/41.5M [08:37<03:42, 91.1kB/s]
53%|#####3 | 22.2M/41.5M [08:37<03:55, 86.1kB/s]
53%|#####3 | 22.2M/41.5M [08:37<03:49, 88.3kB/s]
54%|#####3 | 22.2M/41.5M [08:38<04:49, 69.8kB/s]
54%|#####3 | 22.2M/41.5M [08:38<06:30, 51.7kB/s]
54%|#####3 | 22.2M/41.5M [08:38<04:59, 67.4kB/s]
54%|#####3 | 22.2M/41.5M [08:38<05:21, 62.7kB/s]
54%|#####3 | 22.2M/41.5M [08:39<05:43, 58.8kB/s]
54%|#####3 | 22.3M/41.5M [08:39<09:09, 36.7kB/s]
54%|#####3 | 22.3M/41.5M [08:40<08:23, 40.0kB/s]
54%|#####3 | 22.3M/41.5M [08:40<08:08, 41.3kB/s]
54%|#####3 | 22.3M/41.5M [08:40<06:23, 52.4kB/s]
54%|#####3 | 22.3M/41.5M [08:40<06:33, 51.1kB/s]
54%|#####3 | 22.3M/41.5M [08:40<06:41, 50.1kB/s]
54%|#####3 | 22.3M/41.5M [08:40<06:48, 49.2kB/s]
54%|#####3 | 22.3M/41.5M [08:41<06:53, 48.6kB/s]
54%|#####3 | 22.3M/41.5M [08:41<06
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54%|#####3 | 22.3M/41.5M [08:41<07:00, 47.8kB/s]
54%|#####3 | 22.4M/41.5M [08:41<09:05, 36.8kB/s]
54%|#####3 | 22.4M/41.5M [08:41<06:35, 50.6kB/s]
54%|#####3 | 22.4M/41.5M [08:42<06:43, 49.7kB/s]
54%|#####3 | 22.4M/41.5M [08:42<06:49, 48.9kB/s]
54%|#####3 | 22.4M/41.5M [08:42<05:26, 61.3kB/s]
54%|#####4 | 22.4M/41.5M [08:42<05:49, 57.2kB/s]
54%|#####4 | 22.4M/41.5M [08:42<06:08, 54.2kB/s]
54%|#####4 | 22.4M/41.5M [08:42<06:23, 52.1kB/s]
54%|#####4 | 22.4M/41.5M [08:43<08:32, 39.0kB/s]
54%|#####4 | 22.4M/41.5M [08:43<06:21, 52.4kB/s]
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54%|#####4 | 22.5M/41.5M [08:43<06:40, 49.9kB/s]
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54%|####
#4 | 22.5M/41.5M [08:44<06:48, 48.7kB/s]
54%|#####4 | 22.5M/41.5M [08:45<05:23, 61.4kB/s]
54%|#####4 | 22.5M/41.5M [08:45<05:47, 57.2kB/s]
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54%|#####4 | 22.6M/41.5M [08:45<05:29, 60.2kB/s]
54%|#####4 | 22.6M/41.5M [08:46<07:37, 43.4kB/s]
54%|#####4 | 22.6M/41.5M [08:46<07:28, 44.2kB/s]
54%|#####4 | 22.6M/41.5M [08:47<08:40, 38.0kB/s]
55%|#####4 | 22.6M/41.5M [08:47<06:49, 48.4kB/s]
55%|#####4 | 22.6M/41.5M [08:47<08:02, 41.0kB/s]
55%|#####4 | 22.6M/41.5M [08:47<07:50, 42.0kB/s]
55%|#####4 | 22.7M/41.5M [08:48<07:32, 43.6kB/s]
55%|#####4 | 22.7M/41.5M [08:48<07:26, 44.2kB/s]
55%|#####4 | 22.7M/41.5M [08:48<07:20, 44.8kB/s]
55%|#####4 | 22.7M/41.5M [08:48<07:15, 45.3kB/s]
55%|#####4 | 22.7M/41.5M [08:48<07:11, 45.7kB/s]
55%|#####4 | 22.7M/41.5M [08:49<0
7:08, 46.0kB/s]
55%|#####4 | 22.7M/41.5M [08:49<07:06, 46.2kB/s]
55%|#####4 | 22.7M/41.5M [08:49<07:04, 46.4kB/s]
55%|#####4 | 22.7M/41.5M [08:49<05:50, 56.2kB/s]
55%|#####4 | 22.7M/41.5M [08:49<05:42, 57.4kB/s]
55%|#####4 | 22.8M/41.5M [08:49<04:48, 68.2kB/s]
55%|#####4 | 22.8M/41.5M [08:50<05:54, 55.4kB/s]
55%|#####4 | 22.8M/41.5M [08:50<05:59, 54.5kB/s]
55%|#####4 | 22.8M/41.5M [08:51<06:19, 51.6kB/s]
55%|#####4 | 22.8M/41.5M [08:51<05:24, 60.3kB/s]
55%|#####5 | 22.8M/41.5M [08:51<05:41, 57.3kB/s]
55%|#####5 | 22.8M/41.5M [08:51<05:57, 54.7kB/s]
55%|#####5 | 22.8M/41.5M [08:51<08:09, 39.9kB/s]
55%|#####5 | 22.9M/41.5M [08:52<06:17, 51.7kB/s]
55%|#####5 | 22.9M/41.5M [08:52<06:26, 50.5kB/s]
55%|#####5 | 22.9M/41.5M [08:52<06:33, 49.6kB/s]
55%|#####5 | 22.9M/41.5M [08:52<06:39, 48.9kB/s]
55%|#####5 | 22.9M/41.5M [08:52<06:43, 48.3kB/s]
55%|###
##5 | 22.9M/41.5M [08:52<06:47, 47.9kB/s]
55%|#####5 | 22.9M/41.5M [08:53<10:44, 30.2kB/s]
55%|#####5 | 22.9M/41.5M [08:53<07:29, 43.4kB/s]
55%|#####5 | 22.9M/41.5M [08:53<07:20, 44.2kB/s]
55%|#####5 | 22.9M/41.5M [08:54<07:14, 44.8kB/s]
55%|#####5 | 22.9M/41.5M [08:54<07:08, 45.4kB/s]
55%|#####5 | 22.9M/41.5M [08:54<08:59, 36.0kB/s]
55%|#####5 | 23.0M/41.5M [08:54<08:04, 40.1kB/s]
55%|#####5 | 23.0M/41.5M [08:55<07:47, 41.6kB/s]
55%|#####5 | 23.0M/41.5M [08:55<06:01, 53.7kB/s]
55%|#####5 | 23.0M/41.5M [08:55<09:19, 34.7kB/s]
55%|#####5 | 23.0M/41.5M [08:55<08:43, 37.0kB/s]
55%|#####5 | 23.0M/41.5M [08:56<06:33, 49.2kB/s]
55%|#####5 | 23.0M/41.5M [08:56<09:45, 33.1kB/s]
56%|#####5 | 23.0M/41.5M [08:57<08:37, 37.4kB/s]
56%|#####5 | 23.0M/41.5M [08:57<08:14, 39.1kB/s]
56%|#####5 | 23.1M/41.5M [08:57<11:11, 28.8kB/s]
56%|#####5 | 23.1M/41.5M [08:58<
10:49, 29.7kB/s]
56%|#####5 | 23.1M/41.5M [08:58<09:40, 33.2kB/s]
56%|#####5 | 23.1M/41.5M [08:59<12:26, 25.8kB/s]
56%|#####5 | 23.1M/41.5M [08:59<11:09, 28.8kB/s]
56%|#####5 | 23.1M/41.5M [08:59<11:47, 27.3kB/s]
56%|#####5 | 23.1M/41.5M [09:00<14:03, 22.8kB/s]
56%|#####5 | 23.1M/41.5M [09:00<12:26, 25.8kB/s]
56%|#####5 | 23.1M/41.5M [09:01<16:10, 19.8kB/s]
56%|#####5 | 23.1M/41.5M [09:01<13:50, 23.2kB/s]
56%|#####5 | 23.2M/41.5M [09:01<11:59, 26.7kB/s]
56%|#####5 | 23.2M/41.5M [09:02<12:26, 25.7kB/s]
56%|#####5 | 23.2M/41.5M [09:02<14:42, 21.8kB/s]
56%|#####5 | 23.2M/41.5M [09:03<11:11, 28.6kB/s]
56%|#####5 | 23.2M/41.5M [09:03<11:46, 27.1kB/s]
56%|#####5 | 23.2M/41.5M [09:03<10:30, 30.4kB/s]
56%|#####5 | 23.2M/41.5M [09:03<09:30, 33.6kB/s]
56%|#####5 | 23.2M/41.5M [09:04<10:38, 30.0kB/s]
56%|#####5 | 23.2M/41.5M [09:04<09:33, 33.4kB/s]
56%|##
###6 | 23.2M/41.5M [09:04<08:45, 36.4kB/s]
56%|#####6 | 23.2M/41.5M [09:04<10:10, 31.4kB/s]
56%|#####6 | 23.2M/41.5M [09:05<13:12, 24.1kB/s]
56%|#####6 | 23.3M/41.5M [09:06<13:22, 23.8kB/s]
56%|#####6 | 23.3M/41.5M [09:06<13:25, 23.7kB/s]
56%|#####6 | 23.3M/41.5M [09:07<16:59, 18.7kB/s]
56%|#####6 | 23.3M/41.5M [09:07<14:13, 22.4kB/s]
56%|#####6 | 23.3M/41.5M [09:07<14:18, 22.2kB/s]
56%|#####6 | 23.3M/41.5M [09:08<21:49, 14.6kB/s]
56%|#####6 | 23.3M/41.5M [09:08<17:10, 18.5kB/s]
56%|#####6 | 23.3M/41.5M [09:09<16:06, 19.7kB/s]
56%|#####6 | 23.3M/41.5M [09:09<15:21, 20.7kB/s]
56%|#####6 | 23.3M/41.5M [09:09<15:05, 21.0kB/s]
56%|#####6 | 23.3M/41.5M [09:10<14:37, 21.7kB/s]
56%|#####6 | 23.4M/41.5M [09:10<14:17, 22.2kB/s]
56%|#####6 | 23.4M/41.5M [09:10<14:03, 22.5kB/s]
56%|#####6 | 23.4M/41.5M [09:11<14:23, 22.0kB/s]
56%|#####6 | 23.4M/41.5M [09:11
<12:06, 26.1kB/s]
56%|#####6 | 23.4M/41.5M [09:11<12:31, 25.3kB/s]
56%|#####6 | 23.4M/41.5M [09:12<10:47, 29.3kB/s]
56%|#####6 | 23.4M/41.5M [09:12<09:34, 33.0kB/s]
56%|#####6 | 23.4M/41.5M [09:12<06:42, 47.1kB/s]
56%|#####6 | 23.4M/41.5M [09:12<06:42, 47.0kB/s]
56%|#####6 | 23.4M/41.5M [09:12<06:43, 47.0kB/s]
56%|#####6 | 23.4M/41.5M [09:12<06:43, 47.0kB/s]
57%|#####6 | 23.4M/41.5M [09:13<06:43, 46.9kB/s]
57%|#####6 | 23.5M/41.5M [09:13<07:12, 43.8kB/s]
57%|#####6 | 23.5M/41.5M [09:13<08:07, 38.8kB/s]
57%|#####6 | 23.5M/41.5M [09:14<08:52, 35.4kB/s]
57%|#####6 | 23.5M/41.5M [09:14<08:24, 37.4kB/s]
57%|#####6 | 23.5M/41.5M [09:14<09:35, 32.8kB/s]
57%|#####6 | 23.5M/41.5M [09:15<08:51, 35.5kB/s]
57%|#####6 | 23.5M/41.5M [09:15<11:50, 26.5kB/s]
57%|#####6 | 23.5M/41.5M [09:15<08:10, 38.4kB/s]
57%|#####6 | 23.5M/41.5M [09:16<10:58, 28.6kB/s]
57%|#
####6 | 23.6M/41.5M [09:16<07:54, 39.7kB/s]
57%|#####6 | 23.6M/41.5M [09:16<07:37, 41.1kB/s]
57%|#####6 | 23.6M/41.5M [09:16<07:23, 42.3kB/s]
57%|#####6 | 23.6M/41.5M [09:16<07:12, 43.4kB/s]
57%|#####6 | 23.6M/41.5M [09:17<07:03, 44.3kB/s]
57%|#####6 | 23.6M/41.5M [09:17<06:57, 44.9kB/s]
57%|#####6 | 23.6M/41.5M [09:17<08:46, 35.7kB/s]
57%|#####6 | 23.6M/41.5M [09:17<08:10, 38.2kB/s]
57%|#####6 | 23.6M/41.5M [09:18<07:29, 41.7kB/s]
57%|#####6 | 23.6M/41.5M [09:18<05:51, 53.2kB/s]
57%|#####6 | 23.6M/41.5M [09:18<06:01, 51.7kB/s]
57%|#####7 | 23.7M/41.5M [09:18<06:10, 50.5kB/s]
57%|#####7 | 23.7M/41.5M [09:18<06:17, 49.5kB/s]
57%|#####7 | 23.7M/41.5M [09:19<06:23, 48.8kB/s]
57%|#####7 | 23.7M/41.5M [09:19<05:03, 61.5kB/s]
57%|#####7 | 23.7M/41.5M [09:19<05:25, 57.3kB/s]
57%|#####7 | 23.7M/41.5M [09:19<05:43, 54.2kB/s]
57%|#####7 | 23.7M/41.5M [09:1
9<05:57, 52.1kB/s]
57%|#####7 | 23.7M/41.5M [09:19<06:08, 50.5kB/s]
57%|#####7 | 23.7M/41.5M [09:20<08:08, 38.1kB/s]
57%|#####7 | 23.8M/41.5M [09:20<06:06, 50.8kB/s]
57%|#####7 | 23.8M/41.5M [09:20<07:34, 40.9kB/s]
57%|#####7 | 23.8M/41.5M [09:21<08:26, 36.7kB/s]
57%|#####7 | 23.8M/41.5M [09:21<09:42, 31.9kB/s]
57%|#####7 | 23.8M/41.5M [09:22<08:32, 36.2kB/s]
57%|#####7 | 23.8M/41.5M [09:22<09:31, 32.5kB/s]
57%|#####7 | 23.8M/41.5M [09:22<07:10, 43.0kB/s]
57%|#####7 | 23.8M/41.5M [09:23<08:26, 36.6kB/s]
57%|#####7 | 23.8M/41.5M [09:23<08:58, 34.4kB/s]
58%|#####7 | 23.9M/41.5M [09:23<07:34, 40.7kB/s]
58%|#####7 | 23.9M/41.5M [09:24<08:00, 38.5kB/s]
58%|#####7 | 23.9M/41.5M [09:24<07:41, 40.1kB/s]
58%|#####7 | 23.9M/41.5M [09:24<07:24, 41.5kB/s]
58%|#####7 | 23.9M/41.5M [09:24<09:44, 31.6kB/s]
58%|#####7 | 23.9M/41.5M [09:25<07:20, 41.9kB/s]
58%|
#####7 | 23.9M/41.5M [09:25<07:31, 40.8kB/s]
58%|#####7 | 23.9M/41.5M [09:25<07:17, 42.2kB/s]
58%|#####7 | 23.9M/41.5M [09:25<07:05, 43.3kB/s]
58%|#####7 | 23.9M/41.5M [09:25<06:56, 44.2kB/s]
58%|#####7 | 23.9M/41.5M [09:26<06:22, 48.1kB/s]
58%|#####7 | 24.0M/41.5M [09:26<06:25, 47.7kB/s]
58%|#####7 | 24.0M/41.5M [09:26<06:27, 47.4kB/s]
58%|#####7 | 24.0M/41.5M [09:26<08:23, 36.5kB/s]
58%|#####7 | 24.0M/41.5M [09:27<07:32, 40.5kB/s]
58%|#####7 | 24.0M/41.5M [09:27<09:17, 32.9kB/s]
58%|#####7 | 24.0M/41.5M [09:28<09:29, 32.2kB/s]
58%|#####7 | 24.0M/41.5M [09:28<11:00, 27.7kB/s]
58%|#####7 | 24.0M/41.5M [09:28<10:04, 30.3kB/s]
58%|#####7 | 24.0M/41.5M [09:29<09:14, 33.0kB/s]
58%|#####7 | 24.0M/41.5M [09:29<08:33, 35.6kB/s]
58%|#####7 | 24.1M/41.5M [09:29<08:01, 38.0kB/s]
58%|#####7 | 24.1M/41.5M [09:29<07:36, 40.0kB/s]
58%|#####8 | 24.1M/41.5M [09:
29<09:06, 33.4kB/s]
58%|#####8 | 24.1M/41.5M [09:30<09:35, 31.7kB/s]
58%|#####8 | 24.1M/41.5M [09:30<08:12, 37.0kB/s]
58%|#####8 | 24.1M/41.5M [09:31<08:26, 36.0kB/s]
58%|#####8 | 24.1M/41.5M [09:31<10:22, 29.3kB/s]
58%|#####8 | 24.1M/41.5M [09:31<09:22, 32.3kB/s]
58%|#####8 | 24.1M/41.5M [09:31<09:21, 32.4kB/s]
58%|#####8 | 24.1M/41.5M [09:32<10:20, 29.3kB/s]
58%|#####8 | 24.1M/41.5M [09:32<09:14, 32.8kB/s]
58%|#####8 | 24.2M/41.5M [09:32<08:26, 35.9kB/s]
58%|#####8 | 24.2M/41.5M [09:32<07:52, 38.5kB/s]
58%|#####8 | 24.2M/41.5M [09:33<07:27, 40.6kB/s]
58%|#####8 | 24.2M/41.5M [09:33<07:09, 42.3kB/s]
58%|#####8 | 24.2M/41.5M [09:33<06:56, 43.5kB/s]
58%|#####8 | 24.2M/41.5M [09:33<05:14, 57.7kB/s]
58%|#####8 | 24.2M/41.5M [09:33<05:31, 54.6kB/s]
58%|#####8 | 24.2M/41.5M [09:34<07:26, 40.5kB/s]
58%|#####8 | 24.2M/41.5M [09:34<06:54, 43.7kB/s]
58%
|#####8 | 24.3M/41.5M [09:34<05:55, 50.9kB/s]
58%|#####8 | 24.3M/41.5M [09:34<06:00, 50.0kB/s]
59%|#####8 | 24.3M/41.5M [09:35<06:06, 49.3kB/s]
59%|#####8 | 24.3M/41.5M [09:35<06:10, 48.7kB/s]
59%|#####8 | 24.3M/41.5M [09:35<06:13, 48.2kB/s]
59%|#####8 | 24.3M/41.5M [09:35<06:16, 47.9kB/s]
59%|#####8 | 24.3M/41.5M [09:35<06:18, 47.6kB/s]
59%|#####8 | 24.3M/41.5M [09:36<06:20, 47.3kB/s]
59%|#####8 | 24.3M/41.5M [09:36<05:24, 55.4kB/s]
59%|#####8 | 24.3M/41.5M [09:36<05:37, 53.3kB/s]
59%|#####8 | 24.4M/41.5M [09:36<05:27, 54.9kB/s]
59%|#####8 | 24.4M/41.5M [09:36<05:41, 52.6kB/s]
59%|#####8 | 24.4M/41.5M [09:37<07:33, 39.6kB/s]
59%|#####8 | 24.4M/41.5M [09:37<05:40, 52.7kB/s]
59%|#####8 | 24.4M/41.5M [09:37<05:50, 51.2kB/s]
59%|#####8 | 24.4M/41.5M [09:37<06:57, 42.9kB/s]
59%|#####8 | 24.4M/41.5M [09:38<08:29, 35.2kB/s]
59%|#####8 | 24.4M/41.5M [09
:38<09:38, 30.9kB/s]
59%|#####8 | 24.4M/41.5M [09:38<08:43, 34.2kB/s]
59%|#####8 | 24.4M/41.5M [09:38<08:02, 37.1kB/s]
59%|#####8 | 24.4M/41.5M [09:39<09:23, 31.7kB/s]
59%|#####8 | 24.4M/41.5M [09:39<08:30, 35.0kB/s]
59%|#####8 | 24.5M/41.5M [09:39<09:44, 30.6kB/s]
59%|#####8 | 24.5M/41.5M [09:39<08:43, 34.1kB/s]
59%|#####8 | 24.5M/41.5M [09:40<08:01, 37.1kB/s]
59%|#####8 | 24.5M/41.5M [09:40<07:31, 39.6kB/s]
59%|#####9 | 24.5M/41.5M [09:40<07:09, 41.5kB/s]
59%|#####9 | 24.5M/41.5M [09:40<06:46, 43.8kB/s]
59%|#####9 | 24.5M/41.5M [09:41<05:39, 52.4kB/s]
59%|#####9 | 24.5M/41.5M [09:41<05:26, 54.4kB/s]
59%|#####9 | 24.5M/41.5M [09:41<05:39, 52.4kB/s]
59%|#####9 | 24.5M/41.5M [09:41<07:26, 39.8kB/s]
59%|#####9 | 24.6M/41.5M [09:41<05:37, 52.6kB/s]
59%|#####9 | 24.6M/41.5M [09:42<05:47, 51.1kB/s]
59%|#####9 | 24.6M/41.5M [09:42<04:44, 62.4kB/s]
59
%|#####9 | 24.6M/41.5M [09:42<05:04, 58.1kB/s]
59%|#####9 | 24.6M/41.5M [09:42<04:20, 68.1kB/s]
59%|#####9 | 24.6M/41.5M [09:42<04:45, 62.0kB/s]
59%|#####9 | 24.6M/41.5M [09:42<05:07, 57.6kB/s]
59%|#####9 | 24.6M/41.5M [09:43<04:19, 68.2kB/s]
59%|#####9 | 24.6M/41.5M [09:43<03:53, 75.7kB/s]
59%|#####9 | 24.7M/41.5M [09:43<05:40, 51.8kB/s]
59%|#####9 | 24.7M/41.5M [09:44<05:53, 49.8kB/s]
60%|#####9 | 24.7M/41.5M [09:44<04:56, 59.4kB/s]
60%|#####9 | 24.7M/41.5M [09:44<05:12, 56.3kB/s]
60%|#####9 | 24.7M/41.5M [09:44<06:48, 43.0kB/s]
60%|#####9 | 24.7M/41.5M [09:44<06:40, 43.9kB/s]
60%|#####9 | 24.7M/41.5M [09:45<06:34, 44.6kB/s]
60%|#####9 | 24.7M/41.5M [09:45<06:28, 45.2kB/s]
60%|#####9 | 24.7M/41.5M [09:45<06:24, 45.6kB/s]
60%|#####9 | 24.7M/41.5M [09:45<06:21, 46.0kB/s]
60%|#####9 | 24.8M/41.5M [09:45<06:19, 46.2kB/s]
60%|#####9 | 24.8M/41.5M [0
9:45<06:17, 46.4kB/s]
60%|#####9 | 24.8M/41.5M [09:46<06:16, 46.6kB/s]
60%|#####9 | 24.8M/41.5M [09:46<06:15, 46.6kB/s]
60%|#####9 | 24.8M/41.5M [09:46<06:15, 46.7kB/s]
60%|#####9 | 24.8M/41.5M [09:46<08:05, 36.0kB/s]
60%|#####9 | 24.8M/41.5M [09:47<04:58, 58.5kB/s]
60%|#####9 | 24.8M/41.5M [09:47<05:14, 55.6kB/s]
60%|#####9 | 24.8M/41.5M [09:47<05:27, 53.3kB/s]
60%|#####9 | 24.8M/41.5M [09:47<07:11, 40.5kB/s]
60%|#####9 | 24.8M/41.5M [09:47<06:55, 42.0kB/s]
60%|#####9 | 24.9M/41.5M [09:48<05:17, 55.0kB/s]
60%|#####9 | 24.9M/41.5M [09:48<05:29, 52.8kB/s]
60%|#####9 | 24.9M/41.5M [09:48<05:40, 51.2kB/s]
60%|#####9 | 24.9M/41.5M [09:48<05:48, 50.0kB/s]
60%|###### | 24.9M/41.5M [09:48<04:38, 62.5kB/s]
60%|###### | 24.9M/41.5M [09:48<05:00, 58.0kB/s]
60%|###### | 24.9M/41.5M [09:49<05:17, 54.7kB/s]
60%|###### | 24.9M/41.5M [09:49<05:31, 52.4kB/s]
6
0%|###### | 24.9M/41.5M [09:49<05:42, 50.8kB/s]
60%|###### | 24.9M/41.5M [09:49<05:49, 49.6kB/s]
60%|###### | 24.9M/41.5M [09:49<05:55, 48.8kB/s]
60%|###### | 25.0M/41.5M [09:50<04:38, 62.2kB/s]
60%|###### | 25.0M/41.5M [09:50<05:00, 57.6kB/s]
60%|###### | 25.0M/41.5M [09:50<05:18, 54.4kB/s]
60%|###### | 25.0M/41.5M [09:50<04:21, 66.2kB/s]
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7
3%|#######2 | 30.1M/41.5M [11:20<02:15, 88.2kB/s]
73%|#######2 | 30.1M/41.5M [11:20<02:03, 96.4kB/s]
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[11:31<02:34, 71.9kB/s]
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]
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83%|########2 | 34.3M/41.5M [12:29<02:27, 50.9kB/s]
83%|########2 | 34.3M/41.5M [12:29<02:30, 49.9kB/s]
83%|########2 | 34.3M/41.5M [12:30<02:32, 49.1kB/s]
83%|########2 | 34.4M/41.5M [12:30<03:17, 37.9kB/s]
83%|########2 | 34.4M/41.5M [12:30<02:28, 50.3kB/s]
83%|########2 | 34.4M/41.5M [12:30<02:30, 49.5kB/s]
83%|########2 | 34.4M/41.5M [12:31<02:04, 59.9kB/s]
83%|########2 | 34.4M/41.5M [12:31<02:11, 56.6kB/s]
83%|########2 | 34.4M/41.5M [12:31<01:51, 66.4kB/s]
83%|########2 | 34.4M/41.5M [12:31<03:07, 39.4kB/s]
83%|########3 | 34.4M/41.5M [12:32<02:26, 50.4kB/s]
83%|########3 | 34.5M/41.5M [12:32<02:28, 49.6kB/s]
83%|########3 | 34.5M/41.5M [12:32<03:07, 39.4kB/s]
83%|########3 | 34.5M/41.5M [12:32<02:23, 51.2kB/s]
83%|########3 | 34.5M/41.5M [12:33<03:01, 40.6kB/s]
83%|########3 | 34.5M/41.5M [12:33<02:55, 41.9kB/s]
83%|########3 | 34.5M/41.5M [12:33<02:50, 43.1kB/s]
83%|########3 | 34.5
M/41.5M [12:33<02:46, 44.0kB/s]
83%|########3 | 34.5M/41.5M [12:33<02:07, 57.1kB/s]
83%|########3 | 34.5M/41.5M [12:34<02:14, 54.3kB/s]
83%|########3 | 34.5M/41.5M [12:34<02:19, 52.2kB/s]
83%|########3 | 34.5M/41.5M [12:34<02:23, 50.7kB/s]
83%|########3 | 34.6M/41.5M [12:34<03:09, 38.4kB/s]
83%|########3 | 34.6M/41.5M [12:34<01:54, 63.3kB/s]
83%|########3 | 34.6M/41.5M [12:35<02:02, 59.1kB/s]
83%|########3 | 34.6M/41.5M [12:35<02:09, 55.8kB/s]
83%|########3 | 34.6M/41.5M [12:35<01:48, 66.3kB/s]
83%|########3 | 34.6M/41.5M [12:35<01:58, 60.8kB/s]
83%|########3 | 34.6M/41.5M [12:35<01:42, 70.3kB/s]
83%|########3 | 34.6M/41.5M [12:36<01:53, 63.5kB/s]
84%|########3 | 34.7M/41.5M [12:36<02:15, 53.0kB/s]
84%|########3 | 34.7M/41.5M [12:36<01:47, 66.3kB/s]
84%|########3 | 34.7M/41.5M [12:36<01:37, 73.5kB/s]
84%|########3 | 34.7M/41.5M [12:37<01:54, 62.1kB/s]
84%|########3 | 34.7M/41.5M [12:37<01:42, 69.5kB
/s]
84%|########3 | 34.7M/41.5M [12:37<01:33, 75.6kB/s]
84%|########3 | 34.8M/41.5M [12:37<01:27, 80.4kB/s]
84%|########3 | 34.8M/41.5M [12:37<01:23, 84.0kB/s]
84%|########3 | 34.8M/41.5M [12:38<01:49, 64.4kB/s]
84%|########3 | 34.8M/41.5M [12:38<01:33, 75.2kB/s]
84%|########3 | 34.8M/41.5M [12:38<01:27, 79.9kB/s]
84%|########3 | 34.8M/41.5M [12:38<01:45, 65.9kB/s]
84%|########3 | 34.8M/41.5M [12:38<01:36, 72.4kB/s]
84%|########4 | 34.9M/41.5M [12:39<01:51, 62.2kB/s]
84%|########4 | 34.9M/41.5M [12:39<02:24, 48.1kB/s]
84%|########4 | 34.9M/41.5M [12:40<02:04, 55.7kB/s]
84%|########4 | 34.9M/41.5M [12:40<02:08, 53.9kB/s]
84%|########4 | 34.9M/41.5M [12:40<02:11, 52.4kB/s]
84%|########4 | 34.9M/41.5M [12:40<02:15, 51.1kB/s]
84%|########4 | 34.9M/41.5M [12:40<02:17, 50.0kB/s]
84%|########4 | 34.9M/41.5M [12:41<02:57, 38.8kB/s]
84%|########4 | 35.0M/41.5M [12:41<01:49, 62.3kB/s]
84%|########4 | 35.
0M/41.5M [12:41<01:57, 58.5kB/s]
84%|########4 | 35.0M/41.5M [12:41<02:03, 55.5kB/s]
84%|########4 | 35.0M/41.5M [12:41<02:08, 53.1kB/s]
84%|########4 | 35.0M/41.5M [12:41<02:12, 51.4kB/s]
84%|########4 | 35.0M/41.5M [12:42<01:47, 63.5kB/s]
84%|########4 | 35.0M/41.5M [12:42<01:55, 58.6kB/s]
84%|########4 | 35.0M/41.5M [12:42<01:38, 68.9kB/s]
84%|########4 | 35.0M/41.5M [12:42<01:48, 62.4kB/s]
84%|########4 | 35.0M/41.5M [12:42<01:34, 71.7kB/s]
85%|########4 | 35.1M/41.5M [12:42<01:26, 78.3kB/s]
85%|########4 | 35.1M/41.5M [12:43<01:37, 68.9kB/s]
85%|########4 | 35.1M/41.5M [12:43<01:48, 62.1kB/s]
85%|########4 | 35.1M/41.5M [12:43<01:56, 57.6kB/s]
85%|########4 | 35.1M/41.5M [12:43<01:21, 82.4kB/s]
85%|########4 | 35.1M/41.5M [12:43<01:17, 85.8kB/s]
85%|########4 | 35.1M/41.5M [12:44<01:38, 67.9kB/s]
85%|########4 | 35.2M/41.5M [12:44<01:29, 74.3kB/s]
85%|########4 | 35.2M/41.5M [12:44<02:04, 53.2k
B/s]
85%|########4 | 35.2M/41.5M [12:44<01:18, 83.9kB/s]
85%|########4 | 35.2M/41.5M [12:45<01:16, 86.1kB/s]
85%|########4 | 35.2M/41.5M [12:45<01:14, 88.1kB/s]
85%|########4 | 35.2M/41.5M [12:45<01:52, 58.2kB/s]
85%|########4 | 35.3M/41.5M [12:45<01:27, 74.8kB/s]
85%|########5 | 35.3M/41.5M [12:46<01:22, 78.9kB/s]
85%|########5 | 35.3M/41.5M [12:46<01:37, 66.5kB/s]
85%|########5 | 35.3M/41.5M [12:46<02:06, 51.1kB/s]
85%|########5 | 35.3M/41.5M [12:47<02:10, 49.6kB/s]
85%|########5 | 35.3M/41.5M [12:47<03:33, 30.3kB/s]
85%|########5 | 35.4M/41.5M [12:48<02:00, 53.2kB/s]
85%|########5 | 35.4M/41.5M [12:48<02:59, 35.6kB/s]
85%|########5 | 35.4M/41.5M [12:49<02:50, 37.5kB/s]
85%|########5 | 35.4M/41.5M [12:49<03:03, 34.8kB/s]
85%|########5 | 35.4M/41.5M [12:50<03:20, 31.8kB/s]
85%|########5 | 35.4M/41.5M [12:50<03:06, 34.2kB/s]
85%|########5 | 35.4M/41.5M [12:50<02:59, 35.5kB/s]
85%|########5 | 35
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85%|########5 | 35.4M/41.5M [12:50<03:00, 35.2kB/s]
85%|########5 | 35.4M/41.5M [12:51<02:47, 37.7kB/s]
85%|########5 | 35.5M/41.5M [12:51<02:38, 39.9kB/s]
85%|########5 | 35.5M/41.5M [12:51<02:31, 41.7kB/s]
85%|########5 | 35.5M/41.5M [12:51<02:26, 43.1kB/s]
86%|########5 | 35.5M/41.5M [12:51<02:22, 44.1kB/s]
86%|########5 | 35.5M/41.5M [12:51<01:48, 58.1kB/s]
86%|########5 | 35.5M/41.5M [12:52<01:54, 54.9kB/s]
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86%|########5 | 35.5M/41.5M [12:52<02:03, 50.9kB/s]
86%|########5 | 35.5M/41.5M [12:52<01:24, 74.1kB/s]
86%|########5 | 35.5M/41.5M [12:52<01:29, 69.3kB/s]
86%|########5 | 35.6M/41.5M [12:52<01:21, 76.6kB/s]
86%|########5 | 35.6M/41.5M [12:53<01:15, 81.7kB/s]
86%|########5 | 35.6M/41.5M [12:53<01:26, 71.3kB/s]
86%|########5 | 35.6M/41.5M [12:53<01:19, 78.0kB/s]
86%|########5 | 35.6M/41.5M [12:53<01:03, 96.7
kB/s]
86%|########5 | 35.6M/41.5M [12:53<01:03, 95.9kB/s]
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86%|########6 | 35.7M/41.5M [12:54<01:04, 94.5kB/s]
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87%|########6 | 3
5.9M/41.5M [12:57<00:54, 107kB/s]
87%|########6 | 36.0M/41.5M [12:57<00:58, 99.0kB/s]
87%|########6 | 36.0M/41.5M [12:57<00:59, 97.5kB/s]
87%|########6 | 36.0M/41.5M [12:57<00:59, 96.4kB/s]
87%|########6 | 36.0M/41.5M [12:58<01:17, 73.9kB/s]
87%|########6 | 36.0M/41.5M [12:58<01:10, 81.3kB/s]
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87%|########6 | 36.0M/41.5M [12:58<01:34, 60.3kB/s]
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87%|########6 | 36.1M/41.5M [13:00<02:43, 34.6kB/s]
87%|########7 | 36.1M/41.5M [13:00<01:59, 47.1kB/s]
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87%|########7 | 36.1M/41.5M [13:01<02:48, 33.4kB/s]
87%|########7 | 36.1M/41.5M [13:01<02:09, 43.
2kB/s]
87%|########7 | 36.2M/41.5M [13:02<03:28, 26.8kB/s]
87%|########7 | 36.2M/41.5M [13:02<03:06, 30.0kB/s]
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87%|########7 | 36.2M/41.5M [13:03<03:09, 29.2kB/s]
87%|########7 | 36.2M/41.5M [13:04<03:21, 27.5kB/s]
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87%|########7 | 36.2M/41.5M [13:04<03:06, 29.6kB/s]
87%|########7 | 36.2M/41.5M [13:04<03:14, 28.4kB/s]
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36.3M/41.5M [13:08<02:28, 36.4kB/s]
88%|########7 | 36.3M/41.5M [13:08<02:52, 31.4kB/s]
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88%|########7 | 36.5M/41.5M [13:11<01:30, 58.2kB/s]
88%|########7 | 36.5M/41.5M [13:11<01:34, 55
.2kB/s]
88%|########7 | 36.5M/41.5M [13:11<01:38, 53.0kB/s]
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88%|########8 | 36.6M/41.5M [13:12<01:33, 55.3kB/s]
88%|########8 | 36.6M/41.5M [13:13<01:37, 52.8kB/s]
88%|########8 | 36.6M/41.5M [13:13<01:19, 65.1kB/s]
88%|########8 | 36.6M/41.5M [13:13<01:52, 45.8kB/s]
88%|########8 | 36.6M/41.5M [13:13<01:28, 57.7kB/s]
88%|########8 | 36.6M/41.5M [13:13<01:33, 54.9kB/s]
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88%|########8 | 36.7M/41.5M [13:15<01:33, 53.8kB/s]
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89%|########8 | 36.7M/41.5M [13:15<01:14, 67.4kB/s]
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89%|########8 | 36.7M/41.5M [13:16<01:07, 74.0kB/s]
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7.2kB/s]
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| 37.2M/41.5M [13:23<01:06, 67.5kB/s]
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81%|########1 | 33.6M/41.5M [00:12<00:01, 5.70MB/s]
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@@ -283,11 +283,6 @@ Look up prediction top 1 index in 1000 class synset.
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 15 minutes 3.801 seconds)
-
-
.. _sphx_glr_download_how_to_compile_models_from_oneflow.py:
diff --git a/docs/_sources/how_to/compile_models/from_paddle.rst.txt b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
index aa21cbe41..6e2f013bf 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -201,7 +201,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 10.043 seconds)
+ **Total running time of the script:** ( 1 minutes 5.428 seconds)
.. _sphx_glr_download_how_to_compile_models_from_paddle.py:
diff --git a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
index dbbb57d6e..6ead76e6e 100644
--- a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
@@ -79,7 +79,7 @@ Load a pretrained PyTorch model
.. code-block:: none
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
-
0%| | 0.00/44.7M [00:00<?, ?B/s]
35%|###5 | 15.7M/44.7M [00:00<00:00, 165MB/s]
85%|########4 | 37.9M/44.7M [00:00<00:00, 205MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 207MB/s]
+
0%| | 0.00/44.7M [00:00<?, ?B/s]
41%|####1 | 18.4M/44.7M [00:00<00:00, 193MB/s]
94%|#########3| 41.8M/44.7M [00:00<00:00, 224MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 222MB/s]
diff --git a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
index 49fa5a4e0..ff0de430c 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -372,7 +372,7 @@ Run the corresponding model on tensorflow
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 4.194 seconds)
+ **Total running time of the script:** ( 1 minutes 1.773 seconds)
.. _sphx_glr_download_how_to_compile_models_from_tensorflow.py:
diff --git a/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt b/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
index 1f335a9c2..d62a5d0dd 100644
--- a/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
@@ -5,15 +5,15 @@
Computation times
=================
-**20:02.165** total execution time for **how_to_compile_models** files:
+**05:25.499** total execution time for **how_to_compile_models** files:
-- **15:03.801**: :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)
-- **01:10.043**: :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)
-- **01:04.194**: :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``)
-- **00:58.420**: :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)
-- **00:26.134**: :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)
-- **00:22.174**: :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)
-- **00:21.776**: :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``)
-- **00:19.872**: :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)
-- **00:13.175**: :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)
-- **00:02.575**: :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)
+- **01:05.428**: :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)
+- **01:01.773**: :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``)
+- **00:58.152**: :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)
+- **00:37.768**: :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)
+- **00:25.640**: :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)
+- **00:21.234**: :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``)
+- **00:21.018**: :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)
+- **00:19.070**: :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)
+- **00:12.955**: :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)
+- **00:02.462**: :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)
diff --git a/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt b/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt
index 8276359d2..dfe45f635 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt
@@ -393,7 +393,7 @@ Execute on TVM
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.1503 15.7701 19.3974 15.6904 1.0867
+ 15.6645 15.6655 15.7586 15.5795 0.0495
diff --git a/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt b/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
index dced8c2f5..64f195e5f 100644
--- a/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
@@ -108,7 +108,7 @@ Load pre-trained maskrcnn from torchvision and do tracing
.. code-block:: none
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
-
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+
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/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3878: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
for i in range(dim)
/usr/local/lib/python3.7/dist-packages/torchvision/models/detection/anchor_utils.py:127: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
@@ -253,7 +253,7 @@ Get boxes with score larger than 0.9
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 3 minutes 8.997 seconds)
+ **Total running time of the script:** ( 3 minutes 1.076 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_object_detection_pytorch.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
index e8df7924d..82d9d4257 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -187,7 +187,7 @@ training. Other models require a full post training calibration.
.. code-block:: none
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
-
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38%|###8 | 5.18M/13.6M [00:00<00:00, 53.9MB/s]
77%|#######7 | 10.5M/13.6M [00:00<00:00, 54.6MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 55.9MB/s]
+
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96%|#########6| 13.1M/13.6M [00:00<00:00, 137MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 126MB/s]
@@ -344,7 +344,7 @@ Here we give an example of how to measure performance of TVM compiled models.
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 90.4552 90.2989 94.5511 90.0995 0.4961
+ 90.2287 90.1454 91.4315 89.9442 0.2731
@@ -384,7 +384,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 7.533 seconds)
+ **Total running time of the script:** ( 1 minutes 4.281 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_prequantized.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt b/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
index df0d49372..e25ca8cec 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
@@ -351,7 +351,7 @@ Here we give an example of how to measure performance of TVM compiled models.
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 119.6798 119.6605 121.6868 119.0101 0.4068
+ 120.4160 120.3347 121.8931 119.6589 0.4836
@@ -385,7 +385,7 @@ Here we give an example of how to measure performance of TVM compiled models.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 0.555 seconds)
+ **Total running time of the script:** ( 1 minutes 58.754 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_prequantized_tflite.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
index 124a3d3ab..a820396ce 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -221,7 +221,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 17.266 seconds)
+ **Total running time of the script:** ( 1 minutes 11.293 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_quantized.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt b/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
index 981863b5f..4d4dbc522 100644
--- a/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
@@ -137,7 +137,7 @@ Convert and compile model for CPU.
data: None
input_sym_arg_type = in_param.infer_type()[0]
Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/ssd_512_resnet50_v1_voc-9c8b225a.zip...
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@@ -202,7 +202,7 @@ Display result
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 25.587 seconds)
+ **Total running time of the script:** ( 2 minutes 22.816 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_ssd_gluoncv.py:
diff --git a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
index efc215c4a..37310df7a 100644
--- a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
@@ -5,13 +5,13 @@
Computation times
=================
-**10:52.875** total execution time for **how_to_deploy_models** files:
+**10:27.838** total execution time for **how_to_deploy_models** files:
-- **03:08.997**: :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``)
-- **02:25.587**: :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``)
-- **02:00.555**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)
-- **01:17.266**: :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``)
-- **01:07.533**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)
-- **00:29.837**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)
-- **00:22.905**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)
-- **00:00.195**: :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)
+- **03:01.076**: :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``)
+- **02:22.816**: :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``)
+- **01:58.754**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)
+- **01:11.293**: :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``)
+- **01:04.281**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)
+- **00:27.466**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)
+- **00:21.958**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)
+- **00:00.194**: :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)
diff --git a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
index 4df9ee9ae..d0804113c 100644
--- a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
@@ -423,7 +423,7 @@ First let us define two helper functions to get the mobilenet model and a cat im
.. code-block:: none
- Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip28708bd6-e2e7-431b-a9e1-3504f1d6944f from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip18529069-f3d4-4d72-93a3-b3e2ab179560 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
diff --git a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
index 8586f71b7..721141875 100644
--- a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
@@ -5,9 +5,9 @@
Computation times
=================
-**00:38.110** total execution time for **how_to_extend_tvm** files:
+**00:38.116** total execution time for **how_to_extend_tvm** files:
-- **00:34.614**: :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``)
-- **00:02.240**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)
-- **00:01.058**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)
-- **00:00.198**: :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``)
+- **00:34.630**: :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``)
+- **00:02.231**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)
+- **00:01.052**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)
+- **00:00.202**: :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``)
diff --git a/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt b/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
index bcaf6162d..9f11a29f2 100644
--- a/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
@@ -199,10 +199,10 @@ profile the execution time of each passes.
.. code-block:: none
Printing results of timing profile...
- InferType: 6008us [6008us] (45.58%; 45.58%)
- FoldScaleAxis: 7175us [2us] (54.42%; 54.42%)
- FoldConstant: 7173us [1470us] (54.41%; 99.97%)
- InferType: 5703us [5703us] (43.26%; 79.51%)
+ InferType: 5941us [5941us] (45.23%; 45.23%)
+ FoldScaleAxis: 7193us [2us] (54.77%; 54.77%)
+ FoldConstant: 7191us [1500us] (54.75%; 99.97%)
+ InferType: 5692us [5692us] (43.34%; 79.15%)
@@ -239,10 +239,10 @@ Refer to following sections and :py:func:`tvm.instrument.pass_instrument` for th
.. code-block:: none
Printing results of timing profile...
- InferType: 5752us [5752us] (44.45%; 44.45%)
- FoldScaleAxis: 7188us [2us] (55.55%; 55.55%)
- FoldConstant: 7186us [1516us] (55.53%; 99.97%)
- InferType: 5669us [5669us] (43.81%; 78.90%)
+ InferType: 5731us [5731us] (44.61%; 44.61%)
+ FoldScaleAxis: 7115us [2us] (55.39%; 55.39%)
+ FoldConstant: 7113us [1479us] (55.37%; 99.97%)
+ InferType: 5634us [5634us] (43.85%; 79.20%)
diff --git a/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt b/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
index 1d67312cc..186c4e44c 100644
--- a/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
@@ -295,7 +295,7 @@ latency of convolution.
.. code-block:: none
- Convolution: 47.055970 ms
+ Convolution: 34.784763 ms
diff --git a/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt b/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
index 67ba67273..74bf0726e 100644
--- a/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
@@ -628,7 +628,7 @@ be able to run on our build server
.. code-block:: none
- conv2d with tensor core: 6.924260 ms
+ conv2d with tensor core: 7.953390 ms
diff --git a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
index 465e60d1e..7384e9d88 100644
--- a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
@@ -118,8 +118,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
.. code-block:: none
- Numpy running time: 0.018607
- Baseline: 3.435015
+ Numpy running time: 0.018422
+ Baseline: 3.297649
@@ -210,7 +210,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.295261
+ Opt1: 0.307990
@@ -309,7 +309,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.332947
+ Opt2: 0.345867
@@ -401,7 +401,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.117341
+ Opt3: 0.116493
@@ -520,7 +520,7 @@ flattening.
.. code-block:: none
- Opt4: 0.110480
+ Opt4: 0.110559
@@ -638,7 +638,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.111648
+ Opt5: 0.110912
@@ -759,7 +759,7 @@ Futhermore, we can also utilize multi-core processors to do the thread-level par
.. code-block:: none
- Opt6: 0.145031
+ Opt6: 0.145567
diff --git a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
index f41f18955..feb496872 100644
--- a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
@@ -5,8 +5,8 @@
Computation times
=================
-**00:35.022** total execution time for **how_to_optimize_operators** files:
+**00:34.962** total execution time for **how_to_optimize_operators** files:
-- **00:32.362**: :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)
-- **00:01.428**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``)
-- **00:01.232**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)
+- **00:32.253**: :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)
+- **00:01.463**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``)
+- **00:01.246**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt
index b55e36646..2e0bd12cc 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt
@@ -5,11 +5,11 @@
Computation times
=================
-**05:09.129** total execution time for **how_to_tune_with_autoscheduler** files:
-
-- **02:32.364**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``)
-- **01:21.356**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)
-- **00:41.256**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)
-- **00:16.864**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)
-- **00:08.878**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)
-- **00:08.412**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)
+**04:50.823** total execution time for **how_to_tune_with_autoscheduler** files:
+
+- **02:17.970**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``)
+- **01:19.832**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)
+- **00:40.372**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)
+- **00:15.789**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)
+- **00:08.567**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)
+- **00:08.293**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
index 6941975a4..45fabb945 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
@@ -222,222 +222,237 @@ cooperative fetching, unrolling and operator fusion.
compute: Buffer(compute_2: Pointer(float32), float32, [25088], [])}
buffer_map = {data_1: data, kernel_1: kernel, bias_1: bias, compute_1: compute}
preflattened_buffer_map = {data_1: data_3: Buffer(data_2, float32, [1, 512, 7, 7], []), kernel_1: kernel_3: Buffer(kernel_2, float32, [512, 512, 3, 3], []), bias_1: bias_3: Buffer(bias_2, float32, [1, 512, 1, 1], []), compute_1: compute_3: Buffer(compute_2, float32, [1, 512, 7, 7], [])} {
- attr [IterVar(blockIdx.x: int32, (nullptr), "ThreadIndex", "blockIdx.x")] "thread_extent" = 32;
+ attr [IterVar(blockIdx.x: int32, (nullptr), "ThreadIndex", "blockIdx.x")] "thread_extent" = 64;
allocate(conv2d_nchw: Pointer(local float32), float32, [14]), storage_scope = local;
- allocate(pad_temp.shared: Pointer(shared float32), float32, [2016]), storage_scope = shared;
- allocate(kernel.shared: Pointer(shared float32), float32, [1536]), storage_scope = shared;
- attr [IterVar(threadIdx.x: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56 {
- conv2d_nchw_1: Buffer(conv2d_nchw, float32, [14], [], scope="local", align=32)[0] = 0f32
- conv2d_nchw_1[1] = 0f32
+ allocate(pad_temp.shared: Pointer(shared float32), float32, [252]), storage_scope = shared;
+ allocate(kernel.shared: Pointer(shared float32), float32, [96]), storage_scope = shared;
+ attr [IterVar(threadIdx.x: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28 {
+ conv2d_nchw_1: Buffer(conv2d_nchw, float32, [4], [], scope="local", align=8)[0] = 0f32
conv2d_nchw_1[2] = 0f32
- conv2d_nchw_1[3] = 0f32
conv2d_nchw_1[4] = 0f32
- conv2d_nchw_1[5] = 0f32
conv2d_nchw_1[6] = 0f32
- conv2d_nchw_1[7] = 0f32
conv2d_nchw_1[8] = 0f32
- conv2d_nchw_1[9] = 0f32
conv2d_nchw_1[10] = 0f32
- conv2d_nchw_1[11] = 0f32
conv2d_nchw_1[12] = 0f32
+ conv2d_nchw_1[1] = 0f32
+ conv2d_nchw_1[3] = 0f32
+ conv2d_nchw_1[5] = 0f32
+ conv2d_nchw_1[7] = 0f32
+ conv2d_nchw_1[9] = 0f32
+ conv2d_nchw_1[11] = 0f32
conv2d_nchw_1[13] = 0f32
- for (rc.outer.outer: int32, 0, 16) {
- for (ry.outer.outer: int32, 0, 3) {
- let cse_var_3: int32 = (rc.outer.outer*1568)
- let cse_var_2: int32 = (ry.outer.outer*7)
- let cse_var_1: int32 = (ry.outer.outer*3)
+ for (rc.outer.outer: int32, 0, 128) {
+ for (rx.outer.outer: int32, 0, 3) {
+ let cse_var_2: int32 = (rc.outer.outer*196)
+ let cse_var_1: int32 = (rc.outer.outer*36)
{
- attr [IterVar(threadIdx.x_1: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1: Buffer(pad_temp.shared, float32, [2016], [], scope="shared")[threadIdx.x_1] = @tir.if_then_else(((((1 <= (floordiv(threadIdx.x_1, 9) + ry.outer.outer)) && ((floordiv(threadIdx.x_1, 9) + ry.outer.outer) < 8)) && (1 <= floormod(threadIdx.x_1, 9))) && (floormod(threadIdx.x_1, 9) < 8)), data[((((cse_var_3 + (floordiv(threadIdx.x_1, 9)*7)) + cse_var_2) + floormod(threadIdx.x_1, 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 56)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 56), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 56), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 2), 9))) && (floormod((threadIdx.x_1 + 2), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 56), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 2), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 112)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 112), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 112), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 4), 9))) && (floormod((threadIdx.x_1 + 4), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 112), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 4), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 168)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 168), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 168), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 6), 9))) && (floormod((threadIdx.x_1 + 6), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 168), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 6), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 224)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 224), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 224), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 8), 9))) && (floormod((threadIdx.x_1 + 8), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 224), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 8), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 280)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 280), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 280), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 1), 9))) && (floormod((threadIdx.x_1 + 1), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 280), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 1), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 336)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 336), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 336), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 3), 9))) && (floormod((threadIdx.x_1 + 3), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 336), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 3), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 392)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 392), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 392), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 5), 9))) && (floormod((threadIdx.x_1 + 5), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 392), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 5), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 448)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 448), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 448), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 7), 9))) && (floormod((threadIdx.x_1 + 7), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 448), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 7), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 504)] = @tir.if_then_else(((((1 <= (floordiv(threadIdx.x_1, 9) + ry.outer.outer)) && ((floordiv(threadIdx.x_1, 9) + ry.outer.outer) < 8)) && (1 <= floormod(threadIdx.x_1, 9))) && (floormod(threadIdx.x_1, 9) < 8)), data[((((cse_var_3 + (floordiv(threadIdx.x_1, 9)*7)) + cse_var_2) + floormod(threadIdx.x_1, 9)) + 384)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 560)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 560), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 560), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 2), 9))) && (floormod((threadIdx.x_1 + 2), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 560), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 2), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 616)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 616), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 616), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 4), 9))) && (floormod((threadIdx.x_1 + 4), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 616), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 4), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 672)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 672), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 672), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 6), 9))) && (floormod((threadIdx.x_1 + 6), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 672), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 6), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 728)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 728), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 728), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 8), 9))) && (floormod((threadIdx.x_1 + 8), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 728), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 8), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 784)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 784), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 784), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 1), 9))) && (floormod((threadIdx.x_1 + 1), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 784), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 1), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 840)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 840), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 840), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 3), 9))) && (floormod((threadIdx.x_1 + 3), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 840), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 3), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 896)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 896), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 896), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 5), 9))) && (floormod((threadIdx.x_1 + 5), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 896), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 5), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 952)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 952), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 952), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 7), 9))) && (floormod((threadIdx.x_1 + 7), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 952), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 7), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1008)] = @tir.if_then_else(((((1 <= (floordiv(threadIdx.x_1, 9) + ry.outer.outer)) && ((floordiv(threadIdx.x_1, 9) + ry.outer.outer) < 8)) && (1 <= floormod(threadIdx.x_1, 9))) && (floormod(threadIdx.x_1, 9) < 8)), data[((((cse_var_3 + (floordiv(threadIdx.x_1, 9)*7)) + cse_var_2) + floormod(threadIdx.x_1, 9)) + 776)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1064)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1064), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1064), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 2), 9))) && (floormod((threadIdx.x_1 + 2), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1064), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 2), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1120)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1120), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1120), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 4), 9))) && (floormod((threadIdx.x_1 + 4), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1120), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 4), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1176)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1176), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1176), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 6), 9))) && (floormod((threadIdx.x_1 + 6), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1176), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 6), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1232)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1232), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1232), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 8), 9))) && (floormod((threadIdx.x_1 + 8), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1232), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 8), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1288)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1288), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1288), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 1), 9))) && (floormod((threadIdx.x_1 + 1), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1288), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 1), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1344)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1344), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1344), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 3), 9))) && (floormod((threadIdx.x_1 + 3), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1344), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 3), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1400)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1400), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1400), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 5), 9))) && (floormod((threadIdx.x_1 + 5), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1400), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 5), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1456)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1456), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1456), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 7), 9))) && (floormod((threadIdx.x_1 + 7), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1456), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 7), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1512)] = @tir.if_then_else(((((1 <= (floordiv(threadIdx.x_1, 9) + ry.outer.outer)) && ((floordiv(threadIdx.x_1, 9) + ry.outer.outer) < 8)) && (1 <= floormod(threadIdx.x_1, 9))) && (floormod(threadIdx.x_1, 9) < 8)), data[((((cse_var_3 + (floordiv(threadIdx.x_1, 9)*7)) + cse_var_2) + floormod(threadIdx.x_1, 9)) + 1168)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1568)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1568), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1568), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 2), 9))) && (floormod((threadIdx.x_1 + 2), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1568), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 2), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1624)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1624), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1624), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 4), 9))) && (floormod((threadIdx.x_1 + 4), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1624), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 4), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1680)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1680), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1680), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 6), 9))) && (floormod((threadIdx.x_1 + 6), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1680), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 6), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1736)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1736), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1736), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 8), 9))) && (floormod((threadIdx.x_1 + 8), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1736), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 8), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1792)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1792), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1792), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 1), 9))) && (floormod((threadIdx.x_1 + 1), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1792), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 1), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1848)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1848), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1848), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 3), 9))) && (floormod((threadIdx.x_1 + 3), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1848), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 3), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1904)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1904), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1904), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 5), 9))) && (floormod((threadIdx.x_1 + 5), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1904), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 5), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56;
- pad_temp.shared_1[(threadIdx.x_1 + 1960)] = @tir.if_then_else(((((1 <= (floordiv(floormod((threadIdx.x_1 + 1960), 63), 9) + ry.outer.outer)) && ((floordiv(floormod((threadIdx.x_1 + 1960), 63), 9) + ry.outer.outer) < 8)) && (1 <= floormod((threadIdx.x_1 + 7), 9))) && (floormod((threadIdx.x_1 + 7), 9) < 8)), data[((((cse_var_3 + (floordiv((threadIdx.x_1 + 1960), 9)*7)) + cse_var_2) + floormod((threadIdx.x_1 + 7), 9)) - 8)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_2: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56 {
- kernel.shared_1: Buffer(kernel.shared, float32, [1536], [], scope="shared")[(threadIdx.x_2*16)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod((threadIdx.x_2*16), 96), 3)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 1)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 1), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 2)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 2), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 3)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 1), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 4)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 4), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 5)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 5), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 6)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 2), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 7)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 7), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 8)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 8), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 9)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 3), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 10)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 10), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 11)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 11), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 12)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 4), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 13)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 13), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 14)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 14), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- kernel.shared_1[((threadIdx.x_2*16) + 15)] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 6)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 5), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- }
- attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 56 {
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 896)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 896), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 897)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 11), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 898)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 898), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 899)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv(((threadIdx.x_2*16) + 896), 3) + 1), 32)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 900)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 12), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 901)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 901), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 902)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv(((threadIdx.x_2*16) + 896), 3) + 2), 32)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 903)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 13), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 904)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 904), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 905)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv(((threadIdx.x_2*16) + 896), 3) + 3), 32)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 906)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 14), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 907)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 907), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 908)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv(((threadIdx.x_2*16) + 896), 3) + 4), 32)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 909)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv((threadIdx.x_2*16), 3) + 15), 32)*9)) + cse_var_1) + floormod((threadIdx.x_2*16), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 910)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floordiv(floormod(((threadIdx.x_2*16) + 910), 96), 3)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 1), 3))]
- }
- if @tir.likely((threadIdx.x_2 < 40), dtype=bool) {
- kernel.shared_1[((threadIdx.x_2*16) + 911)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 2) + 28), 3)*4608)) + (rc.outer.outer*288)) + (floormod((floordiv(((threadIdx.x_2*16) + 896), 3) + 5), 32)*9)) + cse_var_1) + floormod(((threadIdx.x_2*16) + 2), 3))]
- }
- }
- for (rc.outer.inner: int32, 0, 32) {
- conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9))]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 1)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 2)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 3)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 4)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 5)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 6)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
- conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9))]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 1)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 2)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 3)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 4)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 5)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 6)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
- conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 1)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 2)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 3)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 4)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 5)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 6)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
- conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 1)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 2)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 3)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 4)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 5)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 6)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
- conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 2)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 3)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 4)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 5)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 6)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 8)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
- conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 2)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
- conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 3)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
- conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 4)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
- conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 5)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
- conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 6)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
- conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
- conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + (floormod(threadIdx.x, 7)*9)) + 8)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ attr [IterVar(threadIdx.x_1: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1: Buffer(pad_temp.shared, float32, [252], [], scope="shared")[threadIdx.x_1] = @tir.if_then_else((((7 <= threadIdx.x_1) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((cse_var_2 + threadIdx.x_1) + rx.outer.outer) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 28)] = @tir.if_then_else(((1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[((((cse_var_2 + ((floordiv(threadIdx.x_1, 7) + 4)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 56)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 8), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 8), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 8), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 8), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dtyp [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 84)] = @tir.if_then_else(((1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 12), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 3), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 112)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 7), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 7), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 16), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 7), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dt [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 140)] = @tir.if_then_else(((1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 20), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 2), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 168)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 6), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 6), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 24), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 6), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dt [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 196)] = @tir.if_then_else(((1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 28), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 1), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ pad_temp.shared_1[(threadIdx.x_1 + 224)] = @tir.if_then_else((((floormod((floordiv(threadIdx.x_1, 7) + 5), 9) < 8) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 32), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 5), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_2: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ kernel.shared_1: Buffer(kernel.shared, float32, [96], [], scope="shared")[threadIdx.x_2] = kernel[(((((blockIdx.x*36864) + (floordiv(threadIdx.x_2, 12)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 12)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ kernel.shared_1[(threadIdx.x_2 + 28)] = kernel[(((((blockIdx.x*36864) + (floordiv((floordiv(threadIdx.x_2, 4) + 7), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 4), 12)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ kernel.shared_1[(threadIdx.x_2 + 56)] = kernel[(((((blockIdx.x*36864) + (floordiv((floordiv(threadIdx.x_2, 4) + 14), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 8), 12)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 28;
+ if @tir.likely((threadIdx.x_2 < 12), dtype=bool) {
+ kernel.shared_1[(threadIdx.x_2 + 84)] = kernel[(((((blockIdx.x*36864) + cse_var_1) + (threadIdx.x_2*3)) + rx.outer.outer) + 32256)]
}
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[floormod(threadIdx.x, 7)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 7)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 14)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 21)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 28)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 35)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 42)]*kernel.shared_1[(floordiv(threadIdx.x, 7)*24)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 7)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 49)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 1)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 49)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 56)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 2)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 63)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 70)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 77)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 84)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 91)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 98)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 105)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 3)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 70)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 77)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 84)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 91)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 98)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 105)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 112)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 4)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 77)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 84)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 91)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 98)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 105)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 112)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 119)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 5)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[floormod(threadIdx.x, 7)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 7)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 12)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 7)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 49)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 13)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 49)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 56)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 14)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 63)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 70)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 77)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 84)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 91)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 98)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 105)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 15)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 70)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 77)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 84)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 91)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 98)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 105)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 112)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 16)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 77)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 84)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 91)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 98)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 105)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 112)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 119)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 17)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 126)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 133)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 140)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 147)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 154)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 161)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 168)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 6)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 133)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 140)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 147)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 154)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 161)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 168)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 175)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 7)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 140)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 147)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 154)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 161)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 168)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 175)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 182)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 8)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 189)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 196)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 203)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 210)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 217)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 224)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 231)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 9)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 196)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 203)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 210)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 217)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 224)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 231)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 238)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 10)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 203)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 210)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 217)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 224)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 231)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 238)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 245)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 11)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 126)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 133)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 140)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 147)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 154)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 161)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 168)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 18)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 133)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 140)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 147)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 154)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 161)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 168)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 175)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 19)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 140)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 147)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 154)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 161)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 168)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 175)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 182)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 20)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 189)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 196)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 203)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 210)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 217)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 224)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 231)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 21)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 196)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 203)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 210)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 217)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 224)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 231)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 238)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 22)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 203)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 210)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 217)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 224)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 231)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 238)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(floormod(threadIdx.x, 7) + 245)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*24) + 23)]))
}
}
}
for (i1.inner: int32, 0, 2) {
- for (i3.inner: int32, 0, 7) {
- compute[(((((blockIdx.x*784) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + (floormod(threadIdx.x, 7)*7)) + i3.inner)] = max((conv2d_nchw_1[((i1.inner*7) + i3.inner)] + bias[(((blockIdx.x*16) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
- }
+ compute[((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7))] = max((conv2d_nchw_1[i1.inner] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ compute[(((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7)) + 7)] = max((conv2d_nchw_1[(i1.inner + 2)] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ compute[(((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7)) + 14)] = max((conv2d_nchw_1[(i1.inner + 4)] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ compute[(((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7)) + 21)] = max((conv2d_nchw_1[(i1.inner + 6)] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ compute[(((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7)) + 28)] = max((conv2d_nchw_1[(i1.inner + 8)] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ compute[(((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7)) + 35)] = max((conv2d_nchw_1[(i1.inner + 10)] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ compute[(((((blockIdx.x*392) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + floormod(threadIdx.x, 7)) + 42)] = max((conv2d_nchw_1[(i1.inner + 12)] + bias[(((blockIdx.x*8) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
}
}
}
@@ -490,7 +505,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 0.204 ms
+ Execution time of this operator: 0.217 ms
@@ -534,36 +549,36 @@ They can be used for debugging and learning the behavior of the auto-scheduler.
conv2d_nchw_nn_o_o_i, conv2d_nchw_nn_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_i, factor=1)
conv2d_nchw_nn_o_o_o_i, conv2d_nchw_nn_o_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_o_i, factor=1)
conv2d_nchw_nn_o_o_o_o, conv2d_nchw_nn_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_o_o_i, factor=1)
- conv2d_nchw_ff_o_i, conv2d_nchw_ff_i = s[conv2d_nchw].split(conv2d_nchw_ff, factor=2)
- conv2d_nchw_ff_o_o_i, conv2d_nchw_ff_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_i, factor=1)
- conv2d_nchw_ff_o_o_o_i, conv2d_nchw_ff_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_i, factor=8)
+ conv2d_nchw_ff_o_i, conv2d_nchw_ff_i = s[conv2d_nchw].split(conv2d_nchw_ff, factor=1)
+ conv2d_nchw_ff_o_o_i, conv2d_nchw_ff_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_i, factor=2)
+ conv2d_nchw_ff_o_o_o_i, conv2d_nchw_ff_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_i, factor=4)
conv2d_nchw_ff_o_o_o_o, conv2d_nchw_ff_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_o_i, factor=1)
conv2d_nchw_yy_o_i, conv2d_nchw_yy_i = s[conv2d_nchw].split(conv2d_nchw_yy, factor=1)
conv2d_nchw_yy_o_o_i, conv2d_nchw_yy_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_i, factor=1)
- conv2d_nchw_yy_o_o_o_i, conv2d_nchw_yy_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_i, factor=7)
- conv2d_nchw_yy_o_o_o_o, conv2d_nchw_yy_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_o_i, factor=1)
- conv2d_nchw_xx_o_i, conv2d_nchw_xx_i = s[conv2d_nchw].split(conv2d_nchw_xx, factor=7)
+ conv2d_nchw_yy_o_o_o_i, conv2d_nchw_yy_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_i, factor=1)
+ conv2d_nchw_yy_o_o_o_o, conv2d_nchw_yy_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_o_i, factor=7)
+ conv2d_nchw_xx_o_i, conv2d_nchw_xx_i = s[conv2d_nchw].split(conv2d_nchw_xx, factor=1)
conv2d_nchw_xx_o_o_i, conv2d_nchw_xx_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_i, factor=1)
- conv2d_nchw_xx_o_o_o_i, conv2d_nchw_xx_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_i, factor=1)
+ conv2d_nchw_xx_o_o_o_i, conv2d_nchw_xx_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_i, factor=7)
conv2d_nchw_xx_o_o_o_o, conv2d_nchw_xx_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_o_i, factor=1)
- conv2d_nchw_rc_o_i, conv2d_nchw_rc_i = s[conv2d_nchw].split(conv2d_nchw_rc, factor=1)
- conv2d_nchw_rc_o_o, conv2d_nchw_rc_o_i = s[conv2d_nchw].split(conv2d_nchw_rc_o_i, factor=32)
- conv2d_nchw_ry_o_i, conv2d_nchw_ry_i = s[conv2d_nchw].split(conv2d_nchw_ry, factor=1)
+ conv2d_nchw_rc_o_i, conv2d_nchw_rc_i = s[conv2d_nchw].split(conv2d_nchw_rc, factor=2)
+ conv2d_nchw_rc_o_o, conv2d_nchw_rc_o_i = s[conv2d_nchw].split(conv2d_nchw_rc_o_i, factor=2)
+ conv2d_nchw_ry_o_i, conv2d_nchw_ry_i = s[conv2d_nchw].split(conv2d_nchw_ry, factor=3)
conv2d_nchw_ry_o_o, conv2d_nchw_ry_o_i = s[conv2d_nchw].split(conv2d_nchw_ry_o_i, factor=1)
conv2d_nchw_rx_o_i, conv2d_nchw_rx_i = s[conv2d_nchw].split(conv2d_nchw_rx, factor=1)
- conv2d_nchw_rx_o_o, conv2d_nchw_rx_o_i = s[conv2d_nchw].split(conv2d_nchw_rx_o_i, factor=3)
+ conv2d_nchw_rx_o_o, conv2d_nchw_rx_o_i = s[conv2d_nchw].split(conv2d_nchw_rx_o_i, factor=1)
s[conv2d_nchw].reorder(conv2d_nchw_nn_o_o_o_o, conv2d_nchw_ff_o_o_o_o, conv2d_nchw_yy_o_o_o_o, conv2d_nchw_xx_o_o_o_o, conv2d_nchw_nn_o_o_o_i, conv2d_nchw_ff_o_o_o_i, conv2d_nchw_yy_o_o_o_i, conv2d_nchw_xx_o_o_o_i, conv2d_nchw_nn_o_o_i, conv2d_nchw_ff_o_o_i, conv2d_nchw_yy_o_o_i, conv2d_nchw_xx_o_o_i, conv2d_nchw_rc_o_o, conv2d_nchw_ry_o_o, conv2d_nchw_rx_o_o, conv2d_nchw_rc_o_i, conv2d_nchw_ry_o_i, conv2d_nchw_rx_o_i, conv2d_nchw_nn_o_i, conv2d_nchw_ff_o_i, conv2d_nchw_yy_o_i, conv2 [...]
compute_i0_o_i, compute_i0_i = s[compute].split(compute_i0, factor=1)
compute_i0_o_o_i, compute_i0_o_i = s[compute].split(compute_i0_o_i, factor=1)
compute_i0_o_o_o, compute_i0_o_o_i = s[compute].split(compute_i0_o_o_i, factor=1)
compute_i1_o_i, compute_i1_i = s[compute].split(compute_i1, factor=2)
- compute_i1_o_o_i, compute_i1_o_i = s[compute].split(compute_i1_o_i, factor=8)
+ compute_i1_o_o_i, compute_i1_o_i = s[compute].split(compute_i1_o_i, factor=4)
compute_i1_o_o_o, compute_i1_o_o_i = s[compute].split(compute_i1_o_o_i, factor=1)
compute_i2_o_i, compute_i2_i = s[compute].split(compute_i2, factor=1)
- compute_i2_o_o_i, compute_i2_o_i = s[compute].split(compute_i2_o_i, factor=7)
- compute_i2_o_o_o, compute_i2_o_o_i = s[compute].split(compute_i2_o_o_i, factor=1)
- compute_i3_o_i, compute_i3_i = s[compute].split(compute_i3, factor=7)
- compute_i3_o_o_i, compute_i3_o_i = s[compute].split(compute_i3_o_i, factor=1)
+ compute_i2_o_o_i, compute_i2_o_i = s[compute].split(compute_i2_o_i, factor=1)
+ compute_i2_o_o_o, compute_i2_o_o_i = s[compute].split(compute_i2_o_o_i, factor=7)
+ compute_i3_o_i, compute_i3_i = s[compute].split(compute_i3, factor=1)
+ compute_i3_o_o_i, compute_i3_o_i = s[compute].split(compute_i3_o_i, factor=7)
compute_i3_o_o_o, compute_i3_o_o_i = s[compute].split(compute_i3_o_o_i, factor=1)
s[compute].reorder(compute_i0_o_o_o, compute_i1_o_o_o, compute_i2_o_o_o, compute_i3_o_o_o, compute_i0_o_o_i, compute_i1_o_o_i, compute_i2_o_o_i, compute_i3_o_o_i, compute_i0_o_i, compute_i1_o_i, compute_i2_o_i, compute_i3_o_i, compute_i0_i, compute_i1_i, compute_i2_i, compute_i3_i)
s[conv2d_nchw].compute_at(s[compute], compute_i3_o_i)
@@ -581,14 +596,14 @@ They can be used for debugging and learning the behavior of the auto-scheduler.
compute_i0_o_i_i1_o_i_fused_i2_o_i_fused_i3_o_i_fused = s[compute].fuse(compute_i0_o_i, compute_i1_o_i, compute_i2_o_i, compute_i3_o_i)
s[compute].bind(compute_i0_o_i_i1_o_i_fused_i2_o_i_fused_i3_o_i_fused, te.thread_axis("threadIdx.x"))
kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused = s[kernel_shared].fuse(kernel_shared_ax0, kernel_shared_ax1, kernel_shared_ax2, kernel_shared_ax3)
- kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=16)
+ kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=1)
s[kernel_shared].vectorize(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i)
- kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=56)
+ kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=28)
s[kernel_shared].bind(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i, te.thread_axis("threadIdx.x"))
pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused = s[pad_temp_shared].fuse(pad_temp_shared_ax0, pad_temp_shared_ax1, pad_temp_shared_ax2, pad_temp_shared_ax3)
pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=1)
s[pad_temp_shared].vectorize(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i)
- pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=56)
+ pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=28)
s[pad_temp_shared].bind(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i, te.thread_axis("threadIdx.x"))
s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "auto_unroll_max_step", 512)
s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "unroll_explicit", True)
@@ -608,178 +623,221 @@ They can be used for debugging and learning the behavior of the auto-scheduler.
#define int64_t long long
#define uint64_t unsigned long long
#endif
- extern "C" __global__ void __launch_bounds__(56) default_function_kernel0(float* __restrict__ data, float* __restrict__ kernel, float* __restrict__ compute, float* __restrict__ bias) {
+ extern "C" __global__ void __launch_bounds__(28) default_function_kernel0(float* __restrict__ data, float* __restrict__ kernel, float* __restrict__ compute, float* __restrict__ bias) {
float conv2d_nchw[14];
- __shared__ float pad_temp_shared[2016];
- __shared__ float kernel_shared[1536];
+ __shared__ float pad_temp_shared[252];
+ __shared__ float kernel_shared[96];
conv2d_nchw[0] = 0.000000e+00f;
- conv2d_nchw[1] = 0.000000e+00f;
conv2d_nchw[2] = 0.000000e+00f;
- conv2d_nchw[3] = 0.000000e+00f;
conv2d_nchw[4] = 0.000000e+00f;
- conv2d_nchw[5] = 0.000000e+00f;
conv2d_nchw[6] = 0.000000e+00f;
- conv2d_nchw[7] = 0.000000e+00f;
conv2d_nchw[8] = 0.000000e+00f;
- conv2d_nchw[9] = 0.000000e+00f;
conv2d_nchw[10] = 0.000000e+00f;
- conv2d_nchw[11] = 0.000000e+00f;
conv2d_nchw[12] = 0.000000e+00f;
+ conv2d_nchw[1] = 0.000000e+00f;
+ conv2d_nchw[3] = 0.000000e+00f;
+ conv2d_nchw[5] = 0.000000e+00f;
+ conv2d_nchw[7] = 0.000000e+00f;
+ conv2d_nchw[9] = 0.000000e+00f;
+ conv2d_nchw[11] = 0.000000e+00f;
conv2d_nchw[13] = 0.000000e+00f;
- for (int rc_outer_outer = 0; rc_outer_outer < 16; ++rc_outer_outer) {
- for (int ry_outer_outer = 0; ry_outer_outer < 3; ++ry_outer_outer) {
+ for (int rc_outer_outer = 0; rc_outer_outer < 128; ++rc_outer_outer) {
+ for (int rx_outer_outer = 0; rx_outer_outer < 3; ++rx_outer_outer) {
__syncthreads();
- pad_temp_shared[((int)threadIdx.x)] = (((((1 <= ((((int)threadIdx.x) / 9) + ry_outer_outer)) && (((((int)threadIdx.x) / 9) + ry_outer_outer) < 8)) && (1 <= (((int)threadIdx.x) % 9))) && ((((int)threadIdx.x) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + ((((int)threadIdx.x) / 9) * 7)) + (ry_outer_outer * 7)) + (((int)threadIdx.x) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 56)] = (((((1 <= ((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 2) % 9))) && (((((int)threadIdx.x) + 2) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 56) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 2) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 112)] = (((((1 <= ((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 4) % 9))) && (((((int)threadIdx.x) + 4) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 112) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 4) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 168)] = (((((1 <= ((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 6) % 9))) && (((((int)threadIdx.x) + 6) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 168) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 6) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 224)] = (((((1 <= ((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 8) % 9))) && (((((int)threadIdx.x) + 8) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 224) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 8) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 280)] = (((((1 <= ((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 1) % 9))) && (((((int)threadIdx.x) + 1) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 280) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 1) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 336)] = (((((1 <= ((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 3) % 9))) && (((((int)threadIdx.x) + 3) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 336) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 3) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 392)] = (((((1 <= ((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 5) % 9))) && (((((int)threadIdx.x) + 5) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 392) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 5) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 448)] = (((((1 <= ((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 7) % 9))) && (((((int)threadIdx.x) + 7) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 448) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 7) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 504)] = (((((1 <= ((((int)threadIdx.x) / 9) + ry_outer_outer)) && (((((int)threadIdx.x) / 9) + ry_outer_outer) < 8)) && (1 <= (((int)threadIdx.x) % 9))) && ((((int)threadIdx.x) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + ((((int)threadIdx.x) / 9) * 7)) + (ry_outer_outer * 7)) + (((int)threadIdx.x) % 9)) + 384)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 560)] = (((((1 <= ((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 2) % 9))) && (((((int)threadIdx.x) + 2) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 560) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 2) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 616)] = (((((1 <= ((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 4) % 9))) && (((((int)threadIdx.x) + 4) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 616) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 4) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 672)] = (((((1 <= ((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 6) % 9))) && (((((int)threadIdx.x) + 6) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 672) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 6) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 728)] = (((((1 <= ((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 8) % 9))) && (((((int)threadIdx.x) + 8) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 728) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 8) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 784)] = (((((1 <= ((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 1) % 9))) && (((((int)threadIdx.x) + 1) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 784) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 1) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 840)] = (((((1 <= ((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 3) % 9))) && (((((int)threadIdx.x) + 3) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 840) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 3) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 896)] = (((((1 <= ((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 5) % 9))) && (((((int)threadIdx.x) + 5) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 896) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 5) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 952)] = (((((1 <= ((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 7) % 9))) && (((((int)threadIdx.x) + 7) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 952) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 7) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1008)] = (((((1 <= ((((int)threadIdx.x) / 9) + ry_outer_outer)) && (((((int)threadIdx.x) / 9) + ry_outer_outer) < 8)) && (1 <= (((int)threadIdx.x) % 9))) && ((((int)threadIdx.x) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + ((((int)threadIdx.x) / 9) * 7)) + (ry_outer_outer * 7)) + (((int)threadIdx.x) % 9)) + 776)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1064)] = (((((1 <= ((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 2) % 9))) && (((((int)threadIdx.x) + 2) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1064) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 2) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1120)] = (((((1 <= ((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 4) % 9))) && (((((int)threadIdx.x) + 4) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1120) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 4) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1176)] = (((((1 <= ((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 6) % 9))) && (((((int)threadIdx.x) + 6) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1176) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 6) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1232)] = (((((1 <= ((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 8) % 9))) && (((((int)threadIdx.x) + 8) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1232) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 8) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1288)] = (((((1 <= ((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 1) % 9))) && (((((int)threadIdx.x) + 1) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1288) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 1) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1344)] = (((((1 <= ((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 3) % 9))) && (((((int)threadIdx.x) + 3) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1344) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 3) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1400)] = (((((1 <= ((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 5) % 9))) && (((((int)threadIdx.x) + 5) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1400) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 5) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1456)] = (((((1 <= ((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 7) % 9))) && (((((int)threadIdx.x) + 7) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1456) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 7) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1512)] = (((((1 <= ((((int)threadIdx.x) / 9) + ry_outer_outer)) && (((((int)threadIdx.x) / 9) + ry_outer_outer) < 8)) && (1 <= (((int)threadIdx.x) % 9))) && ((((int)threadIdx.x) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + ((((int)threadIdx.x) / 9) * 7)) + (ry_outer_outer * 7)) + (((int)threadIdx.x) % 9)) + 1168)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1568)] = (((((1 <= ((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 56) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 2) % 9))) && (((((int)threadIdx.x) + 2) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1568) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 2) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1624)] = (((((1 <= ((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 49) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 4) % 9))) && (((((int)threadIdx.x) + 4) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1624) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 4) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1680)] = (((((1 <= ((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 42) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 6) % 9))) && (((((int)threadIdx.x) + 6) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1680) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 6) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1736)] = (((((1 <= ((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 35) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 8) % 9))) && (((((int)threadIdx.x) + 8) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1736) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 8) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1792)] = (((((1 <= ((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 28) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 1) % 9))) && (((((int)threadIdx.x) + 1) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1792) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 1) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1848)] = (((((1 <= ((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 21) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 3) % 9))) && (((((int)threadIdx.x) + 3) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1848) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 3) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1904)] = (((((1 <= ((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 14) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 5) % 9))) && (((((int)threadIdx.x) + 5) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1904) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 5) % 9)) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1960)] = (((((1 <= ((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer)) && (((((((int)threadIdx.x) + 7) % 63) / 9) + ry_outer_outer) < 8)) && (1 <= ((((int)threadIdx.x) + 7) % 9))) && (((((int)threadIdx.x) + 7) % 9) < 8)) ? data[(((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1960) / 9) * 7)) + (ry_outer_outer * 7)) + ((((int)threadIdx.x) + 7) % 9)) - 8)] : 0.000000e+00f);
- kernel_shared[(((int)threadIdx.x) * 16)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + ((((((int)threadIdx.x) % 6) * 16) / 3) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 1)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 1) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 2)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 2) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 3)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 1) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 4)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 4) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 5)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 5) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 6)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 2) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 7)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 7) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 8)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 8) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 9)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 3) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 10)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 10) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 11)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 11) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 12)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 4) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 13)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 13) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 14)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) % 6) * 16) + 14) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- kernel_shared[((((int)threadIdx.x) * 16) + 15)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 5) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 896)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) + 32) % 96) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 897)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 11) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 898)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) + 34) % 96) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 899)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + ((((((((int)threadIdx.x) * 16) + 896) / 3) + 1) & 31) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 900)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 12) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 901)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) + 37) % 96) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 902)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + ((((((((int)threadIdx.x) * 16) + 896) / 3) + 2) & 31) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 903)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 13) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 904)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) + 40) % 96) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 905)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + ((((((((int)threadIdx.x) * 16) + 896) / 3) + 3) & 31) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 906)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 14) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 907)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) + 43) % 96) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 908)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + ((((((((int)threadIdx.x) * 16) + 896) / 3) + 4) & 31) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 909)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) / 3) + 15) & 31) * 9)) + (ry_outer_outer * 3)) + ((((int)threadIdx.x) * 16) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 910)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + (((((((int)threadIdx.x) * 16) + 46) % 96) / 3) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 1) % 3))];
- }
- if (((int)threadIdx.x) < 40) {
- kernel_shared[((((int)threadIdx.x) * 16) + 911)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 56) / 6) * 4608)) + (rc_outer_outer * 288)) + ((((((((int)threadIdx.x) * 16) + 896) / 3) + 5) & 31) * 9)) + (ry_outer_outer * 3)) + (((((int)threadIdx.x) * 16) + 2) % 3))];
+ pad_temp_shared[((int)threadIdx.x)] = ((((7 <= ((int)threadIdx.x)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((rc_outer_outer * 196) + ((int)threadIdx.x)) + rx_outer_outer) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 28)] = (((1 <= (rx_outer_outer + (((int)threadIdx.x) % 7))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((rc_outer_outer * 196) + ((int)threadIdx.x)) + rx_outer_outer) + 20)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 56)] = (((((1 <= (((((int)threadIdx.x) / 7) + 8) % 9)) && ((((((int)threadIdx.x) / 7) + 8) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 56) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 8) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 84)] = (((1 <= (rx_outer_outer + (((int)threadIdx.x) % 7))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 84) / 63) * 49)) + (((((int)threadIdx.x) / 7) + 3) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 112)] = (((((1 <= (((((int)threadIdx.x) / 7) + 7) % 9)) && ((((((int)threadIdx.x) / 7) + 7) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 112) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 7) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 140)] = (((1 <= (rx_outer_outer + (((int)threadIdx.x) % 7))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 140) / 63) * 49)) + (((((int)threadIdx.x) / 7) + 2) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 168)] = (((((1 <= (((((int)threadIdx.x) / 7) + 6) % 9)) && ((((((int)threadIdx.x) / 7) + 6) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 168) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 6) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 196)] = (((1 <= (rx_outer_outer + (((int)threadIdx.x) % 7))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 196) / 63) * 49)) + (((((int)threadIdx.x) / 7) + 1) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 224)] = ((((((int)threadIdx.x) < 21) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 196) + (((((int)threadIdx.x) + 224) / 63) * 49)) + (((((int)threadIdx.x) / 7) + 5) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ kernel_shared[((int)threadIdx.x)] = kernel[(((((((int)blockIdx.x) * 36864) + ((((int)threadIdx.x) / 12) * 4608)) + (rc_outer_outer * 36)) + ((((int)threadIdx.x) % 12) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 28)] = kernel[(((((((int)blockIdx.x) * 36864) + (((((int)threadIdx.x) + 28) / 12) * 4608)) + (rc_outer_outer * 36)) + (((((int)threadIdx.x) + 4) % 12) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 56)] = kernel[(((((((int)blockIdx.x) * 36864) + (((((int)threadIdx.x) + 56) / 12) * 4608)) + (rc_outer_outer * 36)) + (((((int)threadIdx.x) + 8) % 12) * 3)) + rx_outer_outer)];
+ if (((int)threadIdx.x) < 12) {
+ kernel_shared[(((int)threadIdx.x) + 84)] = kernel[(((((((int)blockIdx.x) * 36864) + (rc_outer_outer * 36)) + (((int)threadIdx.x) * 3)) + rx_outer_outer) + 32256)];
}
__syncthreads();
- for (int rc_outer_inner = 0; rc_outer_inner < 32; ++rc_outer_inner) {
- conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9))] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 1)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 2)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 3)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 4)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 5)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 6)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
- conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9))] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 1)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 2)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 3)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 4)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 5)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 6)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
- conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 1)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 2)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 3)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 4)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 5)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 6)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
- conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 1)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 2)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 3)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 4)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 5)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 6)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
- conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 2)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 3)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 4)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 5)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 6)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 8)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
- conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 2)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 3)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 4)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 5)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 6)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + ((((int)threadIdx.x) % 7) * 9)) + 8)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
- }
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((int)threadIdx.x) % 7)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 7)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 14)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 21)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 28)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 35)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 42)] * kernel_shared[((((int)threadIdx.x) / 7) * 24)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 7)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 49)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 1)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 49)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 56)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 2)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 63)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 70)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 77)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 84)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 91)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 98)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 105)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 3)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 70)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 77)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 84)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 91)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 98)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 105)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 112)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 4)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 77)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 84)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 91)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 98)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 105)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 112)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 119)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 5)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((int)threadIdx.x) % 7)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 7)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 12)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 7)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 49)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 13)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 49)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 56)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 14)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 63)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 70)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 77)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 84)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 91)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 98)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 105)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 15)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 70)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 77)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 84)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 91)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 98)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 105)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 112)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 16)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 77)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 84)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 91)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 98)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 105)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 112)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 119)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 17)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 126)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 133)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 140)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 147)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 154)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 161)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 168)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 6)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 133)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 140)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 147)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 154)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 161)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 168)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 175)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 7)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 140)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 147)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 154)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 161)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 168)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 175)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 182)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 8)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 189)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 196)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 203)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 210)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 217)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 224)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 231)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 9)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 196)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 203)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 210)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 217)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 224)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 231)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 238)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 10)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 203)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 210)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 217)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 224)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 231)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 238)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 245)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 11)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 126)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 133)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 140)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 147)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 154)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 161)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 168)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 18)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 133)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 140)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 147)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 154)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 161)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 168)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 175)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 19)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 140)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 147)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 154)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 161)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 168)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 175)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 182)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 20)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 189)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 196)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 203)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 210)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 217)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 224)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 231)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 21)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 196)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 203)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 210)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 217)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 224)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 231)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 238)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 22)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 203)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 210)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 217)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 224)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 231)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 238)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[((((int)threadIdx.x) % 7) + 245)] * kernel_shared[(((((int)threadIdx.x) / 7) * 24) + 23)]));
}
}
for (int i1_inner = 0; i1_inner < 2; ++i1_inner) {
- for (int i3_inner = 0; i3_inner < 7; ++i3_inner) {
- compute[(((((((int)blockIdx.x) * 784) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + ((((int)threadIdx.x) % 7) * 7)) + i3_inner)] = max((conv2d_nchw[((i1_inner * 7) + i3_inner)] + bias[(((((int)blockIdx.x) * 16) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
- }
+ compute[((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7))] = max((conv2d_nchw[i1_inner] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ compute[(((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7)) + 7)] = max((conv2d_nchw[(i1_inner + 2)] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ compute[(((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7)) + 14)] = max((conv2d_nchw[(i1_inner + 4)] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ compute[(((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7)) + 21)] = max((conv2d_nchw[(i1_inner + 6)] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ compute[(((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7)) + 28)] = max((conv2d_nchw[(i1_inner + 8)] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ compute[(((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7)) + 35)] = max((conv2d_nchw[(i1_inner + 10)] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ compute[(((((((int)blockIdx.x) * 392) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (((int)threadIdx.x) % 7)) + 42)] = max((conv2d_nchw[(i1_inner + 12)] + bias[(((((int)blockIdx.x) * 8) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
}
}
@@ -838,7 +896,7 @@ In the example below we resume the status and do more 5 trials.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 32.364 seconds)
+ **Total running time of the script:** ( 2 minutes 17.970 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt
index 269310f83..6aa12a243 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt
@@ -614,7 +614,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 9.8119 9.8334 9.8462 9.7562 0.0397
+ 9.8472 9.8649 9.8758 9.8008 0.0331
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
index 8c196be33..ab3ccab3f 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
@@ -633,7 +633,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 755.9184 757.1248 758.0160 752.6144 2.3644
+ 755.5663 755.6586 757.8834 753.1568 1.9307
@@ -658,7 +658,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 21.356 seconds)
+ **Total running time of the script:** ( 1 minutes 19.832 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_network_x86.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
index a4ea8338f..eee29abdc 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
@@ -362,78 +362,76 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [65536], []),
compute: Buffer(compute_2: Pointer(float32), float32, [65536], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute}
- preflattened_buffer_map = {placeholder_5: placeholder_15: Buffer(placeholder_10, float32, [128, 256], []), placeholder_8: placeholder_16: Buffer(placeholder_13, int32, [33], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_7: placeholder_17: Buffer(placeholder_12, int32, [4916], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_9: placeholder_19: Buffer(placeholder_14, float32, [128, 512], [])} {
- for (i0.outer.i1.outer.fused: int32, 0, 64) "parallel" {
- allocate(compute_4: Pointer(global float32), float32, [1024]), storage_scope = global {
+ preflattened_buffer_map = {placeholder_6: placeholder_15: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_7: placeholder_16: Buffer(placeholder_12, int32, [4916], []), placeholder_8: placeholder_17: Buffer(placeholder_13, int32, [33], []), placeholder_9: placeholder_18: Buffer(placeholder_14, float32, [128, 512], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_5: placeholder_19: Buffer(placeholder_10, float32, [128, 256], [])} {
+ for (i0.outer.i1.outer.fused: int32, 0, 256) "parallel" {
+ allocate(compute_4: Pointer(global float32), float32, [256]), storage_scope = global {
for (i.outer.inner: int32, 0, 4) {
- for (nb_j.inner: int32, 0, 2) {
- for (i.inner.init: int32, 0, 8) {
- let cse_var_1: int32 = (((i.outer.inner*256) + (i.inner.init*32)) + (nb_j.inner*16))
- {
- compute_5: Buffer(compute_4, float32, [1024], [])[cse_var_1] = 0f32
- compute_5[(cse_var_1 + 1)] = 0f32
- compute_5[(cse_var_1 + 2)] = 0f32
- compute_5[(cse_var_1 + 3)] = 0f32
- compute_5[(cse_var_1 + 4)] = 0f32
- compute_5[(cse_var_1 + 5)] = 0f32
- compute_5[(cse_var_1 + 6)] = 0f32
- compute_5[(cse_var_1 + 7)] = 0f32
- compute_5[(cse_var_1 + 8)] = 0f32
- compute_5[(cse_var_1 + 9)] = 0f32
- compute_5[(cse_var_1 + 10)] = 0f32
- compute_5[(cse_var_1 + 11)] = 0f32
- compute_5[(cse_var_1 + 12)] = 0f32
- compute_5[(cse_var_1 + 13)] = 0f32
- compute_5[(cse_var_1 + 14)] = 0f32
- compute_5[(cse_var_1 + 15)] = 0f32
- }
+ for (i.inner.init: int32, 0, 4) {
+ let cse_var_1: int32 = ((i.outer.inner*64) + (i.inner.init*16))
+ {
+ compute_5: Buffer(compute_4, float32, [256], [])[cse_var_1] = 0f32
+ compute_5[(cse_var_1 + 1)] = 0f32
+ compute_5[(cse_var_1 + 2)] = 0f32
+ compute_5[(cse_var_1 + 3)] = 0f32
+ compute_5[(cse_var_1 + 4)] = 0f32
+ compute_5[(cse_var_1 + 5)] = 0f32
+ compute_5[(cse_var_1 + 6)] = 0f32
+ compute_5[(cse_var_1 + 7)] = 0f32
+ compute_5[(cse_var_1 + 8)] = 0f32
+ compute_5[(cse_var_1 + 9)] = 0f32
+ compute_5[(cse_var_1 + 10)] = 0f32
+ compute_5[(cse_var_1 + 11)] = 0f32
+ compute_5[(cse_var_1 + 12)] = 0f32
+ compute_5[(cse_var_1 + 13)] = 0f32
+ compute_5[(cse_var_1 + 14)] = 0f32
+ compute_5[(cse_var_1 + 15)] = 0f32
}
- for (elem_idx: int32, 0, let cse_var_2: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])) {
- for (i.inner: int32, 0, 8) {
- let cse_var_21: int32 = (elem_idx*16)
- let cse_var_20: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
- let cse_var_19: int32 = (((i.outer.inner*256) + (i.inner*32)) + (nb_j.inner*16))
- let cse_var_18: int32 = (cse_var_19 + 1)
- let cse_var_17: int32 = (cse_var_19 + 11)
- let cse_var_16: int32 = (cse_var_19 + 12)
- let cse_var_15: int32 = (cse_var_19 + 13)
- let cse_var_14: int32 = (cse_var_19 + 14)
- let cse_var_13: int32 = (cse_var_19 + 15)
- let cse_var_12: int32 = (cse_var_19 + 2)
- let cse_var_11: int32 = (cse_var_19 + 3)
- let cse_var_10: int32 = (cse_var_19 + 4)
- let cse_var_9: int32 = (cse_var_19 + 5)
- let cse_var_8: int32 = (cse_var_19 + 6)
- let cse_var_7: int32 = (cse_var_19 + 7)
- let cse_var_6: int32 = (cse_var_19 + 8)
- let cse_var_5: int32 = (cse_var_19 + 9)
- let cse_var_4: int32 = (((floordiv(i0.outer.i1.outer.fused, 16)*8192) + (i.outer.inner*2048)) + (i.inner*256))
- let cse_var_3: int32 = (cse_var_19 + 10)
- {
- compute_5[cse_var_19] = (compute_5[cse_var_19] + (placeholder_1[((placeholder_3[cse_var_20]*16) + cse_var_21)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_18] = (compute_5[cse_var_18] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 1)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_12] = (compute_5[cse_var_12] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 2)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_11] = (compute_5[cse_var_11] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 3)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_10] = (compute_5[cse_var_10] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 4)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_9] = (compute_5[cse_var_9] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 5)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_8] = (compute_5[cse_var_8] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 6)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_7] = (compute_5[cse_var_7] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 7)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_6] = (compute_5[cse_var_6] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 8)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_5] = (compute_5[cse_var_5] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 9)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_3] = (compute_5[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 10)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_17] = (compute_5[cse_var_17] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 11)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_16] = (compute_5[cse_var_16] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 12)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_15] = (compute_5[cse_var_15] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 13)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_14] = (compute_5[cse_var_14] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 14)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_13] = (compute_5[cse_var_13] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 15)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- }
+ }
+ for (elem_idx: int32, 0, let cse_var_2: int32 = floormod(i0.outer.i1.outer.fused, 32) in (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])) {
+ for (i.inner: int32, 0, 4) {
+ let cse_var_21: int32 = floormod(i0.outer.i1.outer.fused, 32)
+ let cse_var_20: int32 = (elem_idx*16)
+ let cse_var_19: int32 = ((i.outer.inner*64) + (i.inner*16))
+ let cse_var_18: int32 = (cse_var_19 + 10)
+ let cse_var_17: int32 = (cse_var_19 + 11)
+ let cse_var_16: int32 = (cse_var_19 + 12)
+ let cse_var_15: int32 = (cse_var_19 + 13)
+ let cse_var_14: int32 = (cse_var_19 + 14)
+ let cse_var_13: int32 = (cse_var_19 + 15)
+ let cse_var_12: int32 = (cse_var_19 + 2)
+ let cse_var_11: int32 = (cse_var_19 + 3)
+ let cse_var_10: int32 = (cse_var_19 + 4)
+ let cse_var_9: int32 = (cse_var_19 + 5)
+ let cse_var_8: int32 = (cse_var_19 + 6)
+ let cse_var_7: int32 = (cse_var_19 + 7)
+ let cse_var_6: int32 = (cse_var_19 + 8)
+ let cse_var_5: int32 = (cse_var_19 + 9)
+ let cse_var_4: int32 = (cse_var_19 + 1)
+ let cse_var_3: int32 = (((floordiv(i0.outer.i1.outer.fused, 32)*4096) + (i.outer.inner*1024)) + (i.inner*256))
+ {
+ compute_5[cse_var_19] = (compute_5[cse_var_19] + (placeholder_1[((placeholder_3[cse_var_21]*16) + cse_var_20)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_4] = (compute_5[cse_var_4] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 1)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_12] = (compute_5[cse_var_12] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 2)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_11] = (compute_5[cse_var_11] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 3)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_10] = (compute_5[cse_var_10] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 4)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_9] = (compute_5[cse_var_9] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 5)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_8] = (compute_5[cse_var_8] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 6)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_7] = (compute_5[cse_var_7] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 7)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_6] = (compute_5[cse_var_6] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 8)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_5] = (compute_5[cse_var_5] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 9)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_18] = (compute_5[cse_var_18] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 10)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_17] = (compute_5[cse_var_17] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 11)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_16] = (compute_5[cse_var_16] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 12)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_15] = (compute_5[cse_var_15] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 13)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_14] = (compute_5[cse_var_14] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 14)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
+ compute_5[cse_var_13] = (compute_5[cse_var_13] + (placeholder_1[(((placeholder_3[cse_var_21]*16) + cse_var_20) + 15)]*max(placeholder[(cse_var_3 + placeholder_2[(placeholder_3[cse_var_21] + elem_idx)])], 0f32)))
}
}
}
}
- for (i0.inner: int32, 0, 32) {
- let cse_var_22: int32 = (((floordiv(i0.outer.i1.outer.fused, 16)*16384) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32))
- compute[ramp(cse_var_22, 1, 32)] = max((compute_5[ramp((i0.inner*32), 1, 32)] + placeholder_4[ramp(cse_var_22, 1, 32)]), broadcast(0f32, 32))
+ for (i0.inner: int32, 0, 16) {
+ let cse_var_22: int32 = (((floordiv(i0.outer.i1.outer.fused, 32)*8192) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 32)*16))
+ compute[ramp(cse_var_22, 1, 16)] = max((compute_5[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_22, 1, 16)]), broadcast(0f32, 16))
}
}
}
@@ -487,7 +485,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 1.836 ms
+ Execution time of this operator: 2.114 ms
diff --git a/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt b/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
index 6fdf1d719..640f6cd52 100644
--- a/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:44.958** total execution time for **how_to_tune_with_autotvm** files:
+**00:44.499** total execution time for **how_to_tune_with_autotvm** files:
-- **00:44.090**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)
-- **00:00.228**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)
-- **00:00.216**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.py``)
-- **00:00.213**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``)
-- **00:00.211**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``)
+- **00:43.601**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)
+- **00:00.243**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)
+- **00:00.221**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.py``)
+- **00:00.219**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``)
+- **00:00.216**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``)
diff --git a/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt b/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt
index b0794a52a..f32e080de 100644
--- a/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt
@@ -859,8 +859,8 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 32]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2885496
- No: 6 GFLOPS: 42.34/42.34 result: MeasureResult(costs=(0.005467297105263158,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6116833686828613, timestamp=1651651611.1036348) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
- No: 7 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 6 GFLOPS: 103.96/103.96 result: MeasureResult(costs=(0.0022269264791666666,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.5949070453643799, timestamp=1651650136.8941896) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
+ No: 7 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -983,7 +983,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 16, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6225319
- No: 8 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 8 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1106,7 +1106,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,943546
- No: 9 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 9 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1229,7 +1229,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 16, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 32]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2868708
- No: 10 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 10 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 142, in build
res = future.result()
File "/usr/lib/python3.7/concurrent/futures/_base.py", line 435, in result
@@ -1247,7 +1247,7 @@ for this template
TimeoutError
[('tile_f', [-1, 32, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4691833
- No: 11 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 11 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1370,7 +1370,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 2, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1042124
- No: 12 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 12 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1493,7 +1493,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10013405
- No: 13 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 13 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1616,7 +1616,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 8, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6732082
- No: 14 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 14 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1739,7 +1739,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 4, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7536735
- No: 15 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 15 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1862,7 +1862,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,482121
- No: 16 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 16 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1985,7 +1985,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 32, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2824525
- No: 17 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 17 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2108,7 +2108,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4559286
- No: 18 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 18 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2231,7 +2231,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 32, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 512]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9677544
- No: 19 GFLOPS: 0.00/42.34 result: Traceback (most recent call last):
+ No: 19 GFLOPS: 0.00/103.96 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 721, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 685, in run_through_rpc
@@ -2319,7 +2319,7 @@ for this template
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007f11adb18fa2
+ 12: 0x00007f38fd076fa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2384,7 +2384,7 @@ for this template
21: _PyFunction_FastCallKeywords
20: _PyEval_EvalFrameDefault
19: _PyFunction_FastCall [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6390073
- No: 20 GFLOPS: 143.42/143.42 result: MeasureResult(costs=(0.0016141227419354837,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.3566863536834717, timestamp=1651651636.9078462) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
+ No: 20 GFLOPS: 144.55/144.55 result: MeasureResult(costs=(0.00160148995,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4383623600006104, timestamp=1651650163.3591824) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
@@ -2437,7 +2437,7 @@ and measure running time.
Best config:
[('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
- Time cost of this operator: 0.002041
+ Time cost of this operator: 0.002059
diff --git a/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt b/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt
index 83e2b9c7f..7fd63516c 100644
--- a/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt
@@ -292,10 +292,10 @@ Timing the untuned program
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 311.6 98.638 (1, 2, 10, 10, 3) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.2 1.013 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 1.101 0.349 (1, 1, 10, 10, 3) 1 1
- Total_time - 315.901 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 312.2 98.726 (1, 2, 10, 10, 3) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.121 0.987 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.908 0.287 (1, 1, 10, 10, 3) 1 1
+ Total_time - 316.229 - - - -
@@ -357,10 +357,10 @@ Timing the tuned program
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 218.2 98.712 (1, 1, 10, 10, 6) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.946 0.88 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.901 0.408 (1, 3, 10, 10, 1) 1 1
- Total_time - 221.047 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 216.8 98.684 (1, 1, 10, 10, 6) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.971 0.897 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.921 0.419 (1, 3, 10, 10, 1) 1 1
+ Total_time - 219.692 - - - -
diff --git a/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt b/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
index f9a1ec1df..3f924e2b0 100644
--- a/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:44.530** total execution time for **how_to_work_with_microtvm** files:
+**00:44.192** total execution time for **how_to_work_with_microtvm** files:
-- **00:40.464**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)
-- **00:03.475**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)
-- **00:00.201**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_ethosu.py` (``micro_ethosu.py``)
-- **00:00.197**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tvmc.py` (``micro_tvmc.py``)
-- **00:00.193**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_reference_vm.py` (``micro_reference_vm.py``)
+- **00:40.187**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)
+- **00:03.424**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)
+- **00:00.197**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_ethosu.py` (``micro_ethosu.py``)
+- **00:00.194**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tvmc.py` (``micro_tvmc.py``)
+- **00:00.188**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_reference_vm.py` (``micro_reference_vm.py``)
diff --git a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
index f68e625fe..644ba0f31 100644
--- a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
@@ -5,8 +5,8 @@
Computation times
=================
-**00:08.802** total execution time for **how_to_work_with_relay** files:
+**00:08.908** total execution time for **how_to_work_with_relay** files:
-- **00:06.851**: :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)
-- **00:01.734**: :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)
-- **00:00.216**: :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``)
+- **00:07.022**: :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)
+- **00:01.668**: :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)
+- **00:00.218**: :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``)
diff --git a/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt b/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt
index 1c0384c55..6deffce16 100644
--- a/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt
@@ -5,13 +5,13 @@
Computation times
=================
-**00:05.660** total execution time for **how_to_work_with_schedules** files:
+**00:05.622** total execution time for **how_to_work_with_schedules** files:
-- **00:02.102**: :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)
-- **00:01.109**: :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)
-- **00:00.738**: :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)
-- **00:00.711**: :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)
-- **00:00.305**: :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)
-- **00:00.240**: :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``)
-- **00:00.237**: :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)
-- **00:00.218**: :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)
+- **00:02.081**: :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)
+- **00:01.101**: :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)
+- **00:00.728**: :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)
+- **00:00.714**: :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)
+- **00:00.304**: :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)
+- **00:00.238**: :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``)
+- **00:00.236**: :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)
+- **00:00.220**: :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)
diff --git a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
index 068952991..c9120366b 100644
--- a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
@@ -318,7 +318,7 @@ The importing needs to happen before the tensorized GEMV being executed.
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C}
preflattened_buffer_map = {A_1: A_3: Buffer(A_2, float32, [1024, 64], []), B_1: B_3: Buffer(B_2, float32, [512, 64], []), C_1: C_3: Buffer(C_2, float32, [1024, 512], [])} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmp1jcx_q0l/input0.cc'\nsource_filename = \"/tmp/tmp1jcx_q0l/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = alloca float*, align 8\n %8 = alloca float*, align 8\n %9 = alloca floa [...]
+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmp358ay0p7/input0.cc'\nsource_filename = \"/tmp/tmp358ay0p7/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = alloca float*, align 8\n %8 = alloca float*, align 8\n %9 = alloca floa [...]
for (i, 0, 1024) {
for (j.outer: int32, 0, 32) {
@tir.call_extern("gemv_update", @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), C_2, ((i*512) + (j.outer*16)), 16, 2, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), A_2, (i*64), 64, 1, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), B_2, (j.outer*1024), 1024, 1, dtype=handle), 16, 64, 64, dtype=int32)
diff --git a/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
index 4e2242422..cb5799152 100644
--- a/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
@@ -5,7 +5,7 @@
Computation times
=================
-**00:21.359** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:20.376** total execution time for **topic_vta_tutorials_autotvm** files:
-- **00:21.154**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``)
-- **00:00.205**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``)
+- **00:20.176**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``)
+- **00:00.201**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``)
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
index 06bc9d37b..881e78d18 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -265,7 +265,7 @@ The compilation steps are:
DeprecationWarning,
/workspace/vta/tutorials/frontend/deploy_classification.py:213: DeprecationWarning: legacy graph executor behavior of producing json / lib / params will be removed in the next release. Please see documents of tvm.contrib.graph_executor.GraphModule for the new recommended usage.
relay_prog, target=tvm.target.Target(target, host=env.target_host), params=params
- resnet18_v1 inference graph built in 22.87s!
+ resnet18_v1 inference graph built in 21.32s!
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
index 71a129662..bd7f651d7 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -301,7 +301,7 @@ The compilation steps are:
/workspace/python/tvm/relay/build_module.py:439: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
- yolov3-tiny inference graph built in 15.68s!
+ yolov3-tiny inference graph built in 15.08s!
diff --git a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
index 63516fd65..a848806c3 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
@@ -5,7 +5,7 @@
Computation times
=================
-**01:30.681** total execution time for **topic_vta_tutorials_frontend** files:
+**01:28.542** total execution time for **topic_vta_tutorials_frontend** files:
-- **00:47.753**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``)
-- **00:42.929**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``)
+- **00:47.150**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``)
+- **00:41.392**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``)
diff --git a/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
index c3f39acde..1be22199a 100644
--- a/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
@@ -5,7 +5,7 @@
Computation times
=================
-**00:03.843** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.478** total execution time for **topic_vta_tutorials_optimize** files:
-- **00:03.286**: :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)
-- **00:00.557**: :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``)
+- **00:02.939**: :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)
+- **00:00.538**: :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``)
diff --git a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
index 5ed9799ea..c47464e00 100644
--- a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
@@ -5,7 +5,7 @@
Computation times
=================
-**00:01.002** total execution time for **topic_vta_tutorials** files:
+**00:01.014** total execution time for **topic_vta_tutorials** files:
-- **00:00.506**: :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``)
-- **00:00.495**: :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``)
+- **00:00.510**: :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``)
+- **00:00.504**: :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``)
diff --git a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
index ebebf4453..c5efd802f 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -306,7 +306,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 94.233 ms
+ Execution time of this operator: 93.699 ms
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index c898ce84c..49888804b 100644
--- a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
@@ -268,7 +268,7 @@ standard deviation.
.. code-block:: none
- {'mean': 493.7532687299995, 'median': 493.45023005000144, 'std': 0.6770297200500106}
+ {'mean': 494.81908133000053, 'median': 494.46491210000545, 'std': 1.271678161028298}
@@ -482,31 +482,30 @@ the tuning data to.
.. code-block:: none
-
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 1/25] Current/Best: 18.36/ 19.14 GFLOPS | Progress: (4/10) | 4.80 s
[Task 1/25] Current/Best: 11.60/ 23.14 GFLOPS | Progress: (8/10) | 8.47 s
[Task 1/25] Current/Best: 5.75/ 23.14 GFLOPS | Progress: (10/10) | 10.89 s Done.
-
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 2/25] Current/Best: 13.20/ 14.53 GFLOPS | Progress: (4/10) | 2.97 s
[Task 2/25] Current/Best: 20.91/ 20.91 GFLOPS | Progress: (8/10) | 4.34 s
[Task 2/25] Current/Best: 14.94/ 20.91 GFLOPS | Progress: (10/10) | 4.91 s Done.
-
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 3/25] Current/Best: 11.92/ 11.92 GFLOPS | Progress: (4/10) | 3.13 s
[Task 3/25] Current/Best: 8.42/ 19.65 GFLOPS | Progress: (8/10) | 5.32 s
[Task 3/25] Current/Best: 7.42/ 19.65 GFLOPS | Progress: (10/10) | 6.86 s Done.
-
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 4/25] Current/Best: 3.51/ 16.92 GFLOPS | Progress: (4/10) | 8.24 s
[Task 4/25] Current/Best: 16.60/ 16.92 GFLOPS | Progress: (8/10) | 12.61 s
[Task 4/25] Current/Best: 6.76/ 16.92 GFLOPS | Progress: (10/10) | 13.39 s Done.
-
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 5/25] Current/Best: 13.95/ 16.20 GFLOPS | Progress: (4/10) | 2.66 s
[Task 5/25] Current/Best: 18.31/ 18.31 GFLOPS | Progress: (8/10) | 4.71 s
[Task 5/25] Current/Best: 13.09/ 23.74 GFLOPS | Progress: (10/10) | 6.01 s Done.
-
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 6/25] Current/Best: 11.95/ 20.26 GFLOPS | Progress: (4/10) | 2.82 s
[Task 6/25] Current/Best: 13.40/ 20.26 GFLOPS | Progress: (8/10) | 5.37 s
[Task 6/25] Current/Best: 9.73/ 20.26 GFLOPS | Progress: (10/10) | 6.58 s Done.
-
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 7/25] Current/Best: 18.44/ 18.44 GFLOPS | Progress: (4/10) | 3.41 s
[Task 7/25] Current/Best: 9.84/ 18.44 GFLOPS | Progress: (8/10) | 6.55 s
[Task 7/25] Current/Best: 12.69/ 18.44 GFLOPS | Progress: (10/10) | 8.25 s Done.
-
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 8/25] Current/Best: 15.82/ 18.46 GFLOPS | Progress: (4/10) | 5.32 s
[Task 8/25] Current/Best: 10.41/ 18.46 GFLOPS | Progress: (8/10) | 11.44 s
[Task 8/25] Current/Best: 7.05/ 18.46 GFLOPS | Progress: (10/10) | 22.31 s
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 9/25] Current/Best: 14.56/ 14.56 GFLOPS | Progress: (4/10) | 3.48 s
[Task 9/25] Current/Best: 4.78/ 14.56 GFLOPS | Progress: (8/10) | 5.61 s
[Task 9/25] Current/Best: 12.28/ 14.56 GFLOPS | Progress: (10/10) | 7.14 s Done.
-
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 10/25] Current/Best: 3.78/ 13.34 GFLOPS | Progress: (4/10) | 2.72 s
[Task 10/25] Current/Best: 21.01/ 21.01 GFLOPS | Progress: (8/10) | 4.59 s
[Task 10/25] Current/Best: 14.69/ 21.01 GFLOPS | Progress: (10/10) | 5.48 s Done.
-
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 11/25] Current/Best: 12.93/ 22.37 GFLOPS | Progress: (4/10) | 2.56 s
[Task 11/25] Current/Best: 10.82/ 22.37 GFLOPS | Progress: (8/10) | 5.28 s
[Task 11/25] Current/Best: 20.02/ 22.37 GFLOPS | Progress: (10/10) | 5.96 s Done.
-
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 12/25] Current/Best: 8.06/ 20.28 GFLOPS | Progress: (4/10) | 3.49 s
[Task 12/25] Current/Best: 15.72/ 20.28 GFLOPS | Progress: (8/10) | 7.05 s
[Task 12/25] Current/Best: 9.25/ 20.28 GFLOPS | Progress: (10/10) | 7.95 s Done.
-
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 13/25] Current/Best: 12.26/ 18.68 GFLOPS | Progress: (4/10) | 4.14 s
[Task 13/25] Current/Best: 1.57/ 18.68 GFLOPS | Progress: (8/10) | 8.69 s
[Task 13/25] Current/Best: 19.72/ 19.72 GFLOPS | Progress: (10/10) | 9.94 s Done.
-
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 14/25] Current/Best: 17.46/ 18.07 GFLOPS | Progress: (4/10) | 3.27 s
[Task 14/25] Current/Best: 6.02/ 18.07 GFLOPS | Progress: (8/10) | 5.57 s
[Task 14/25] Current/Best: 19.13/ 19.13 GFLOPS | Progress: (10/10) | 6.85 s Done.
-
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 15/25] Current/Best: 6.72/ 20.40 GFLOPS | Progress: (4/10) | 2.41 s
[Task 15/25] Current/Best: 5.19/ 24.19 GFLOPS | Progress: (8/10) | 3.84 s
[Task 15/25] Current/Best: 15.81/ 24.19 GFLOPS | Progress: (10/10) | 4.39 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 16/25] Current/Best: 13.97/ 17.53 GFLOPS | Progress: (4/10) | 2.93 s Done.
+
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 1/25] Current/Best: 17.58/ 17.58 GFLOPS | Progress: (4/10) | 6.69 s
[Task 1/25] Current/Best: 22.70/ 22.70 GFLOPS | Progress: (8/10) | 10.30 s
[Task 1/25] Current/Best: 11.47/ 22.70 GFLOPS | Progress: (10/10) | 12.81 s Done.
+
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 2/25] Current/Best: 7.12/ 19.58 GFLOPS | Progress: (4/10) | 2.15 s
[Task 2/25] Current/Best: 16.61/ 19.58 GFLOPS | Progress: (8/10) | 3.27 s
[Task 2/25] Current/Best: 17.25/ 19.58 GFLOPS | Progress: (10/10) | 3.83 s Done.
+
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 3/25] Current/Best: 24.21/ 24.21 GFLOPS | Progress: (4/10) | 2.73 s
[Task 3/25] Current/Best: 16.06/ 24.21 GFLOPS | Progress: (8/10) | 4.46 s
[Task 3/25] Current/Best: 15.59/ 24.21 GFLOPS | Progress: (10/10) | 5.39 s Done.
+
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 4/25] Current/Best: 6.47/ 12.89 GFLOPS | Progress: (4/10) | 6.81 s
[Task 4/25] Current/Best: 17.45/ 17.45 GFLOPS | Progress: (8/10) | 8.28 s
[Task 4/25] Current/Best: 6.34/ 17.45 GFLOPS | Progress: (10/10) | 9.11 s Done.
+
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 5/25] Current/Best: 3.12/ 17.05 GFLOPS | Progress: (4/10) | 3.01 s
[Task 5/25] Current/Best: 10.59/ 17.05 GFLOPS | Progress: (8/10) | 5.03 s
[Task 5/25] Current/Best: 13.51/ 17.05 GFLOPS | Progress: (10/10) | 6.59 s Done.
+
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 6/25] Current/Best: 20.68/ 21.07 GFLOPS | Progress: (4/10) | 3.10 s
[Task 6/25] Current/Best: 7.93/ 21.07 GFLOPS | Progress: (8/10) | 5.69 s
[Task 6/25] Current/Best: 18.71/ 21.07 GFLOPS | Progress: (10/10) | 8.16 s Done.
+
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 7/25] Current/Best: 23.49/ 23.49 GFLOPS | Progress: (4/10) | 2.50 s
[Task 7/25] Current/Best: 13.88/ 23.49 GFLOPS | Progress: (8/10) | 4.55 s
[Task 7/25] Current/Best: 12.24/ 23.49 GFLOPS | Progress: (10/10) | 6.07 s Done.
+
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 8/25] Current/Best: 2.61/ 17.83 GFLOPS | Progress: (4/10) | 3.60 s
[Task 8/25] Current/Best: 6.98/ 17.83 GFLOPS | Progress: (8/10) | 12.18 s
[Task 8/25] Current/Best: 9.59/ 17.83 GFLOPS | Progress: (10/10) | 13.77 s Done.
+
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 9/25] Current/Best: 20.15/ 20.15 GFLOPS | Progress: (4/10) | 2.72 s
[Task 9/25] Current/Best: 13.86/ 20.46 GFLOPS | Progress: (8/10) | 8.88 s
[Task 9/25] Current/Best: 19.72/ 20.46 GFLOPS | Progress: (10/10) | 9.53 s Done.
+
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 10/25] Current/Best: 4.26/ 22.12 GFLOPS | Progress: (4/10) | 2.58 s
[Task 10/25] Current/Best: 10.80/ 22.12 GFLOPS | Progress: (8/10) | 4.46 s
[Task 10/25] Current/Best: 14.75/ 22.12 GFLOPS | Progress: (10/10) | 5.09 s Done.
+
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 11/25] Current/Best: 10.88/ 16.68 GFLOPS | Progress: (4/10) | 2.75 s
[Task 11/25] Current/Best: 14.38/ 23.42 GFLOPS | Progress: (8/10) | 4.73 s
[Task 11/25] Current/Best: 12.21/ 23.79 GFLOPS | Progress: (10/10) | 5.96 s Done.
+
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 12/25] Current/Best: 11.77/ 11.77 GFLOPS | Progress: (4/10) | 7.75 s
[Task 12/25] Current/Best: 16.92/ 19.20 GFLOPS | Progress: (8/10) | 11.91 s
[Task 12/25] Current/Best: 10.72/ 19.20 GFLOPS | Progress: (10/10) | 13.27 s Done.
+
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 13/25] Current/Best: 14.58/ 20.09 GFLOPS | Progress: (4/10) | 3.45 s
[Task 13/25] Current/Best: 23.01/ 23.44 GFLOPS | Progress: (8/10) | 5.01 s
[Task 13/25] Current/Best: 6.24/ 23.44 GFLOPS | Progress: (10/10) | 6.30 s Done.
+
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 14/25] Current/Best: 5.49/ 16.02 GFLOPS | Progress: (4/10) | 4.16 s
[Task 14/25] Current/Best: 14.09/ 19.04 GFLOPS | Progress: (8/10) | 11.40 s
[Task 14/25] Current/Best: 14.40/ 19.04 GFLOPS | Progress: (10/10) | 13.61 s Done.
+
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 15/25] Current/Best: 12.52/ 16.39 GFLOPS | Progress: (4/10) | 3.60 s
[Task 15/25] Current/Best: 6.75/ 16.39 GFLOPS | Progress: (8/10) | 6.54 s
[Task 15/25] Current/Best: 18.62/ 19.12 GFLOPS | Progress: (10/10) | 7.10 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 16/25] Current/Best: 15.26/ 18.82 GFLOPS | Progress: (4/10) | 2.71 s
[Task 16/25] Current/Best: 5.87/ 18.82 GFLOPS | Progress: (8/10) | 4.92 s
[Task 16/25] Current/Best: 10.71/ 18.82 GFLOPS | Progress: (10/10) | 6.08 s Done.
+
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 17/25] Current/Best: 7.71/ 19.95 GFLOPS | Progress: (4/10) | 2.94 s
[Task 17/25] Current/Best: 11.76/ 19.95 GFLOPS | Progress: (8/10) | 5.13 s
[Task 17/25] Current/Best: 6.22/ 19.95 GFLOPS | Progress: (10/10) | 6.70 s Done.
+
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 18/25] Current/Best: 19.74/ 21.28 GFLOPS | Progress: (4/10) | 2.46 s
[Task 18/25] Current/Best: 16.02/ 23.03 GFLOPS | Progress: (8/10) | 4.00 s
[Task 18/25] Current/Best: 16.99/ 23.03 GFLOPS | Progress: (10/10) | 4.88 s Done.
+
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 19/25] Current/Best: 1.55/ 22.07 GFLOPS | Progress: (4/10) | 5.29 s
[Task 19/25] Current/Best: 11.78/ 22.77 GFLOPS | Progress: (8/10) | 7.85 s
[Task 19/25] Current/Best: 11.78/ 22.77 GFLOPS | Progress: (10/10) | 8.94 s Done.
+
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 20/25] Current/Best: 21.77/ 21.77 GFLOPS | Progress: (4/10) | 4.76 s
[Task 20/25] Current/Best: 15.50/ 21.77 GFLOPS | Progress: (8/10) | 6.72 s
[Task 20/25] Current/Best: 15.66/ 21.77 GFLOPS | Progress: (10/10) | 7.56 s Done.
+
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 21/25] Current/Best: 20.41/ 20.41 GFLOPS | Progress: (4/10) | 2.24 s
[Task 21/25] Current/Best: 2.74/ 20.41 GFLOPS | Progress: (8/10) | 4.35 s
[Task 21/25] Current/Best: 2.74/ 20.41 GFLOPS | Progress: (10/10) | 5.55 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s Done.
Done.
-
[Task 16/25] Current/Best: 10.20/ 21.95 GFLOPS | Progress: (8/10) | 6.11 s
[Task 16/25] Current/Best: 3.08/ 21.95 GFLOPS | Progress: (10/10) | 7.10 s Done.
-
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 17/25] Current/Best: 12.28/ 20.02 GFLOPS | Progress: (4/10) | 4.03 s
[Task 17/25] Current/Best: 15.74/ 20.02 GFLOPS | Progress: (8/10) | 6.68 s
[Task 17/25] Current/Best: 10.92/ 20.02 GFLOPS | Progress: (10/10) | 8.37 s Done.
-
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 18/25] Current/Best: 8.83/ 18.47 GFLOPS | Progress: (4/10) | 3.18 s
[Task 18/25] Current/Best: 10.76/ 18.47 GFLOPS | Progress: (8/10) | 6.71 s
[Task 18/25] Current/Best: 8.56/ 18.47 GFLOPS | Progress: (10/10) | 13.65 s Done.
-
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 19/25] Current/Best: 8.65/ 22.70 GFLOPS | Progress: (4/10) | 3.05 s
[Task 19/25] Current/Best: 11.77/ 22.70 GFLOPS | Progress: (8/10) | 6.05 s
[Task 19/25] Current/Best: 22.08/ 22.70 GFLOPS | Progress: (10/10) | 8.52 s Done.
-
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 20/25] Current/Best: 15.65/ 18.04 GFLOPS | Progress: (4/10) | 2.47 s
[Task 20/25] Current/Best: 9.78/ 21.00 GFLOPS | Progress: (8/10) | 5.40 s
[Task 20/25] Current/Best: 14.04/ 21.00 GFLOPS | Progress: (10/10) | 6.38 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 21/25] Current/Best: 13.52/ 13.52 GFLOPS | Progress: (4/10) | 2.99 s
[Task 21/25] Current/Best: 12.26/ 14.54 GFLOPS | Progress: (8/10) | 4.87 s
[Task 21/25] Current/Best: 16.76/ 16.76 GFLOPS | Progress: (10/10) | 5.98 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 22/25] Current/Best: 14.86/ 15.92 GFLOPS | Progress: (4/10) | 3.62 s
[Task 22/25] Current/Best: 6.40/ 16.61 GFLOPS | Progress: (8/10) | 5.46 s
[Task 22/25] Current/Best: 2.70/ 19.68 GFLOPS | Progress: (10/10) | 6.41
s Done.
-
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 23/25] Current/Best: 5.33/ 10.48 GFLOPS | Progress: (4/10) | 6.59 s
[Task 23/25] Current/Best: 19.37/ 19.64 GFLOPS | Progress: (8/10) | 8.97 s
[Task 23/25] Current/Best: 14.27/ 19.64 GFLOPS | Progress: (10/10) | 10.84 s Done.
-
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 24/25] Current/Best: 3.21/ 4.94 GFLOPS | Progress: (4/10) | 26.44 s
[Task 24/25] Current/Best: 6.04/ 9.21 GFLOPS | Progress: (8/10) | 390.56 s
[Task 24/25] Current/Best: 2.43/ 9.21 GFLOPS | Progress: (10/10) | 1811.42 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s Done.
- Done.
- Done.
-
[Task 25/25] Current/Best: 8.14/ 8.14 GFLOPS | Progress: (4/10) | 14.29 s
[Task 25/25] Current/Best: 5.20/ 9.97 GFLOPS | Progress: (8/10) | 41.18 s
[Task 25/25] Current/Best: 3.98/ 9.97 GFLOPS | Progress: (10/10) | 42.07 s
+
[Task 22/25] Current/Best: 20.97/ 20.97 GFLOPS | Progress: (4/10) | 5.81 s
[Task 22/25] Current/Best: 16.98/ 20.97 GFLOPS | Progress: (8/10) | 9.86 s
[Task 22/25] Current/Best: 17.29/ 20.97 GFLOPS | Progress: (10/10) | 10.51 s Done.
+
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 23/25] Current/Best: 19.44/ 19.44 GFLOPS | Progress: (4/10) | 3.40 s
[Task 23/25] Current/Best: 18.25/ 20.68 GFLOPS | Progress: (8/10) | 5.25 s
[Task 23/25] Current/Best: 18.13/ 20.68 GFLOPS | Progress: (10/10) | 6.46 s Done.
+
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 24/25] Current/Best: 6.19/ 6.19 GFLOPS | Progress: (4/10) | 7.56 s
[Task 24/25] Current/Best: 3.66/ 8.85 GFLOPS | Progress: (8/10) | 21.51 s
[Task 24/25] Current/Best: 5.91/ 8.85 GFLOPS | Progress: (10/10) | 22.46 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 25/25] Current/Best: 8.34/ 8.34 GFLOPS | Progress: (4/10) | 11.22 s
[Task 25/25] Current/Best: 7.89/ 8.65 GFLOPS | Progress: (8/10) | 13.51 s
[Task 25/25] Current/Best: 8.86/ 8.86 GFLOPS | Progress: (10/10) | 38.78 s
The output from this tuning process will look something like this:
@@ -564,14 +563,6 @@ model using optimized operators to speed up our computations.
-.. rst-class:: sphx-glr-script-out
-
- Out:
-
- .. code-block:: none
-
- Done.
-
Verify that the optimized model runs and produces the same results:
@@ -603,7 +594,7 @@ Verify that the optimized model runs and produces the same results:
.. code-block:: none
class='n02123045 tabby, tabby cat' with probability=0.621104
- class='n02123159 tiger cat' with probability=0.356379
+ class='n02123159 tiger cat' with probability=0.356378
class='n02124075 Egyptian cat' with probability=0.019712
class='n02129604 tiger, Panthera tigris' with probability=0.001215
class='n04040759 radiator' with probability=0.000262
@@ -656,8 +647,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 440.06395049000275, 'median': 439.62063920000674, 'std': 1.249499167278835}
- unoptimized: {'mean': 493.7532687299995, 'median': 493.45023005000144, 'std': 0.6770297200500106}
+ optimized: {'mean': 428.74853812000083, 'median': 428.1781065500013, 'std': 1.1610721133414101}
+ unoptimized: {'mean': 494.81908133000053, 'median': 494.46491210000545, 'std': 1.271678161028298}
@@ -677,7 +668,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 37 minutes 29.350 seconds)
+ **Total running time of the script:** ( 7 minutes 13.209 seconds)
.. _sphx_glr_download_tutorial_autotvm_relay_x86.py:
diff --git a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
index be9341d1f..f804c1ed7 100644
--- a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
+++ b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
@@ -235,7 +235,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.248e-07 secs/op
+ 1.181e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index a23b52711..232b21639 100644
--- a/docs/_sources/tutorial/intro_topi.rst.txt
+++ b/docs/_sources/tutorial/intro_topi.rst.txt
@@ -233,7 +233,7 @@ As you can see, scheduled stages of computation have been accumulated and we can
.. code-block:: none
- [stage(a, placeholder(a, 0xc038ff0)), stage(b, placeholder(b, 0x22b9a0c0)), stage(T_add, compute(T_add, body=[(a[ax0, ax1, ax2] + b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min=0, ext=10))], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[(a[ax0, ax1, ax2]*b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min [...]
+ [stage(a, placeholder(a, 0x1fe78a60)), stage(b, placeholder(b, 0x3bffbd0)), stage(T_add, compute(T_add, body=[(a[ax0, ax1, ax2] + b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min=0, ext=10))], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[(a[ax0, ax1, ax2]*b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min [...]
diff --git a/docs/_sources/tutorial/sg_execution_times.rst.txt b/docs/_sources/tutorial/sg_execution_times.rst.txt
index 7db42a726..4c7cf2fdc 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,17 +5,17 @@
Computation times
=================
-**40:07.008** total execution time for **tutorial** files:
+**09:46.652** total execution time for **tutorial** files:
-- **37:29.350**: :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)
-- **01:01.080**: :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)
-- **00:44.624**: :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``)
-- **00:26.242**: :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)
-- **00:23.323**: :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)
-- **00:01.283**: :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)
-- **00:00.720**: :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)
-- **00:00.212**: :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``)
-- **00:00.050**: :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``)
-- **00:00.044**: :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``)
-- **00:00.042**: :ref:`sphx_glr_tutorial_install.py` (``install.py``)
-- **00:00.039**: :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``)
+- **07:13.209**: :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)
+- **00:59.303**: :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)
+- **00:36.795**: :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``)
+- **00:29.031**: :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)
+- **00:25.985**: :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)
+- **00:01.263**: :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)
+- **00:00.699**: :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)
+- **00:00.189**: :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``)
+- **00:00.052**: :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``)
+- **00:00.049**: :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``)
+- **00:00.039**: :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``)
+- **00:00.039**: :ref:`sphx_glr_tutorial_install.py` (``install.py``)
diff --git a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
index 062c9b04c..510c2e1b4 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -335,7 +335,7 @@ compile and run this new schedule with the parallel operation applied:
.. code-block:: none
- parallel: 0.000006
+ parallel: 0.000008
@@ -438,10 +438,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 8.131170002343424e-06 1.0
- naive 5.868e-06 0.721667361315632
- parallel 6.0954e-06 0.7496338163195814
- vector 2.4727899999999997e-05 3.0411244621466964
+ numpy 7.729390001713909e-06 1.0
+ naive 5.8371e-06 0.7551824915945096
+ parallel 7.7031e-06 0.9965986964420118
+ vector 2.4538e-05 3.17463603137621
@@ -830,7 +830,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.018501
+ Numpy running time: 0.017793
@@ -886,7 +886,7 @@ optimizations.
.. code-block:: none
- none: 3.431038
+ none: 3.305652
@@ -985,7 +985,7 @@ schedule.
.. code-block:: none
- blocking: 0.295513
+ blocking: 0.291275
@@ -1077,7 +1077,7 @@ already cache friendly from our previous optimizations.
.. code-block:: none
- vectorization: 0.334770
+ vectorization: 0.331214
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1149,7 +1149,7 @@ more cache friendly.
.. code-block:: none
- loop permutation: 0.117690
+ loop permutation: 0.117891
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1246,7 +1246,7 @@ optimized schedule.
.. code-block:: none
- array packing: 0.110159
+ array packing: 0.110045
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1337,7 +1337,7 @@ to `C` when all the block results are ready.
.. code-block:: none
- block caching: 0.110532
+ block caching: 0.111021
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1421,7 +1421,7 @@ of thread-level parallelization.
.. code-block:: none
- parallelization: 0.144453
+ parallelization: 0.144811
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1500,13 +1500,13 @@ working, we can compare the results.
.. code-block:: none
Operator Timing Performance
- none 3.4310381961 1.0
- blocking 0.29551253590000004 0.08612918860416766
- vectorization 0.33477000200000007 0.09757105076257303
- loop permutation 0.1176902307 0.03430163815540625
- array packing 0.11015862299999998 0.03210649858844922
- block caching 0.11053163930000001 0.03221521678937861
- parallelization 0.1444532432 0.042101904713330626
+ none 3.3056521090000004 1.0
+ blocking 0.2912748915 0.08811420013224386
+ vectorization 0.3312144428 0.10019640055232441
+ loop permutation 0.1178905123 0.035663314956534645
+ array packing 0.1100447278 0.03328986964490037
+ block caching 0.1110210738 0.03358522619416996
+ parallelization 0.14481118980000002 0.04380714758390203
@@ -1541,11 +1541,6 @@ operations with tunable parameters that allows you to automatically optimize
the computation for specific platforms.
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 1 minutes 1.080 seconds)
-
-
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
diff --git a/docs/commit_hash b/docs/commit_hash
index dfba68eb1..1801091bd 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-01e160616f71ad7089a91ff7cbe03b8189d2f8cf
+a0c61038b6fd25f0a1cf8673a76b9ff6d8fa5052
diff --git a/docs/how_to/compile_models/from_mxnet.html b/docs/how_to/compile_models/from_mxnet.html
index 40c2619d1..0857f3f38 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -401,7 +401,7 @@
</div>
<img alt="../../_images/sphx_glr_from_mxnet_001.png" class="sphx-glr-single-img" src="../../_images/sphx_glr_from_mxnet_001.png" />
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip043cc264-4629-4bfd-9c1c-16a85ae75591 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip3c9c1e6c-31ef-4005-a713-1d77ab7fb756 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index 6fee4cc15..95caa62f0 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -406,3671 +406,97 @@ python3 -m pip install -f https://release.oneflow.info <span class="nv">oneflow<
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
0%| | 0.00/41.5M [00:00<?, ?B/s]
- 0%| | 16.0k/41.5M [00:00<07:41, 94.3kB/s]
- 0%| | 32.0k/41.5M [00:00<07:42, 93.9kB/s]
- 0%| | 64.0k/41.5M [00:00<05:17, 137kB/s]
- 0%| | 96.0k/41.5M [00:00<04:36, 157kB/s]
- 0%| | 128k/41.5M [00:00<04:18, 168kB/s]
- 0%| | 152k/41.5M [00:01<04:33, 159kB/s]
- 0%| | 168k/41.5M [00:01<05:15, 137kB/s]
- 0%| | 192k/41.5M [00:01<05:12, 138kB/s]
- 1%| | 224k/41.5M [00:01<04:41, 154kB/s]
- 1%| | 248k/41.5M [00:01<04:48, 150kB/s]
- 1%| | 264k/41.5M [00:01<05:26, 133kB/s]
- 1%| | 280k/41.5M [00:02<09:35, 75.1kB/s]
- 1%| | 296k/41.5M [00:02<09:06, 79.0kB/s]
- 1%| | 312k/41.5M [00:02<08:43, 82.5kB/s]
- 1%| | 328k/41.5M [00:02<08:26, 85.3kB/s]
- 1%| | 344k/41.5M [00:03<10:53, 66.1kB/s]
- 1%| | 352k/41.5M [00:03<13:35, 52.9kB/s]
- 1%| | 368k/41.5M [00:04<14:45, 48.7kB/s]
- 1%| | 376k/41.5M [00:04<14:52, 48.3kB/s]
- 1%| | 384k/41.5M [00:04<14:57, 48.0kB/s]
- 1%| | 392k/41.5M [00:04<22:09, 32.4kB/s]
- 1%| | 400k/41.5M [00:05<20:27, 35.1kB/s]
- 1%| | 408k/41.5M [00:05<27:09, 26.5kB/s]
- 1%| | 424k/41.5M [00:05<22:04, 32.5kB/s]
- 1%|1 | 432k/41.5M [00:06<20:29, 35.0kB/s]
- 1%|1 | 440k/41.5M [00:06<23:01, 31.2kB/s]
- 1%|1 | 448k/41.5M [00:06<20:59, 34.2kB/s]
- 1%|1 | 456k/41.5M [00:06<19:25, 36.9kB/s]
- 1%|1 | 464k/41.5M [00:07<22:34, 31.8kB/s]
- 1%|1 | 472k/41.5M [00:07<20:29, 35.0kB/s]
- 1%|1 | 480k/41.5M [00:07<18:58, 37.8kB/s]
- 1%|1 | 488k/41.5M [00:07<17:53, 40.1kB/s]
- 1%|1 | 496k/41.5M [00:07<17:07, 41.8kB/s]
- 1%|1 | 504k/41.5M [00:08<21:06, 33.9kB/s]
- 1%|1 | 512k/41.5M [00:08<19:22, 37.0kB/s]
- 1%|1 | 520k/41.5M [00:08<18:09, 39.5kB/s]
- 1%|1 | 528k/41.5M [00:08<17:17, 41.4kB/s]
- 1%|1 | 536k/41.5M [00:09<21:15, 33.7kB/s]
- 1%|1 | 552k/41.5M [00:09<19:07, 37.4kB/s]
- 1%|1 | 560k/41.5M [00:09<18:26, 38.8kB/s]
- 1%|1 | 568k/41.5M [00:10<25:35, 28.0kB/s]
- 1%|1 | 576k/41.5M [00:10<22:46, 31.4kB/s]
- 1%|1 | 584k/41.5M [00:10<20:42, 34.5kB/s]
- 1%|1 | 592k/41.5M [00:10<23:30, 30.4kB/s]
- 1%|1 | 600k/41.5M [00:11<26:19, 27.2kB/s]
- 1%|1 | 608k/41.5M [00:11<23:05, 30.9kB/s]
- 1%|1 | 616k/41.5M [00:11<21:02, 34.0kB/s]
- 1%|1 | 624k/41.5M [00:12<28:21, 25.2kB/s]
- 1%|1 | 632k/41.5M [00:12<25:35, 27.9kB/s]
- 2%|1 | 640k/41.5M [00:12<31:35, 22.6kB/s]
- 2%|1 | 648k/41.5M [00:13<31:15, 22.8kB/s]
- 2%|1 | 656k/41.5M [00:13<31:01, 23.0kB/s]
- 2%|1 | 664k/41.5M [00:13<26:17, 27.1kB/s]
- 2%|1 | 672k/41.5M [00:14<27:32, 25.9kB/s]
- 2%|1 | 680k/41.5M [00:14<23:50, 29.9kB/s]
- 2%|1 | 688k/41.5M [00:14<21:15, 33.6kB/s]
- 2%|1 | 696k/41.5M [00:14<19:26, 36.7kB/s]
- 2%|1 | 704k/41.5M [00:14<18:10, 39.2kB/s]
- 2%|1 | 712k/41.5M [00:15<17:17, 41.2kB/s]
- 2%|1 | 720k/41.5M [00:15<21:14, 33.6kB/s]
- 2%|1 | 744k/41.5M [00:15<17:50, 39.9kB/s]
- 2%|1 | 760k/41.5M [00:16<16:16, 43.7kB/s]
- 2%|1 | 768k/41.5M [00:16<18:43, 38.0kB/s]
- 2%|1 | 776k/41.5M [00:16<17:56, 39.7kB/s]
- 2%|1 | 784k/41.5M [00:16<17:16, 41.2kB/s]
- 2%|1 | 792k/41.5M [00:17<16:44, 42.5kB/s]
- 2%|1 | 800k/41.5M [00:17<16:19, 43.6kB/s]
- 2%|1 | 808k/41.5M [00:17<16:00, 44.5kB/s]
- 2%|1 | 824k/41.5M [00:17<12:17, 57.8kB/s]
- 2%|1 | 832k/41.5M [00:17<12:59, 54.7kB/s]
- 2%|1 | 848k/41.5M [00:17<10:47, 65.8kB/s]
- 2%|2 | 856k/41.5M [00:18<11:46, 60.4kB/s]
- 2%|2 | 864k/41.5M [00:18<16:16, 43.6kB/s]
- 2%|2 | 888k/41.5M [00:18<10:32, 67.3kB/s]
- 2%|2 | 904k/41.5M [00:18<12:02, 58.9kB/s]
- 2%|2 | 920k/41.5M [00:19<10:37, 66.8kB/s]
- 2%|2 | 928k/41.5M [00:19<15:16, 46.5kB/s]
- 2%|2 | 944k/41.5M [00:19<11:39, 60.8kB/s]
- 2%|2 | 960k/41.5M [00:20<15:18, 46.3kB/s]
- 2%|2 | 968k/41.5M [00:20<15:16, 46.4kB/s]
- 2%|2 | 976k/41.5M [00:20<15:14, 46.5kB/s]
- 2%|2 | 984k/41.5M [00:20<15:12, 46.6kB/s]
- 2%|2 | 992k/41.5M [00:21<18:58, 37.3kB/s]
- 2%|2 | 0.98M/41.5M [00:21<21:56, 32.3kB/s]
- 2%|2 | 0.98M/41.5M [00:21<21:05, 33.6kB/s]
- 2%|2 | 0.99M/41.5M [00:22<27:53, 25.4kB/s]
- 2%|2 | 1.00M/41.5M [00:22<23:09, 30.6kB/s]
- 2%|2 | 1.01M/41.5M [00:22<29:34, 23.9kB/s]
- 2%|2 | 1.02M/41.5M [00:23<29:45, 23.8kB/s]
- 2%|2 | 1.02M/41.5M [00:23<30:32, 23.2kB/s]
- 2%|2 | 1.03M/41.5M [00:24<38:42, 18.3kB/s]
- 3%|2 | 1.04M/41.5M [00:24<36:09, 19.6kB/s]
- 3%|2 | 1.05M/41.5M [00:24<34:22, 20.6kB/s]
- 3%|2 | 1.05M/41.5M [00:25<28:35, 24.7kB/s]
- 3%|2 | 1.06M/41.5M [00:25<29:03, 24.3kB/s]
- 3%|2 | 1.08M/41.5M [00:25<22:36, 31.2kB/s]
- 3%|2 | 1.09M/41.5M [00:26<24:28, 28.9kB/s]
- 3%|2 | 1.09M/41.5M [00:26<25:56, 27.2kB/s]
- 3%|2 | 1.10M/41.5M [00:26<22:58, 30.7kB/s]
- 3%|2 | 1.11M/41.5M [00:26<20:46, 34.0kB/s]
- 3%|2 | 1.12M/41.5M [00:27<23:25, 30.1kB/s]
- 3%|2 | 1.12M/41.5M [00:27<21:00, 33.6kB/s]
- 3%|2 | 1.13M/41.5M [00:27<28:04, 25.1kB/s]
- 3%|2 | 1.15M/41.5M [00:28<22:07, 31.9kB/s]
- 3%|2 | 1.16M/41.5M [00:28<20:23, 34.6kB/s]
- 3%|2 | 1.16M/41.5M [00:28<22:53, 30.8kB/s]
- 3%|2 | 1.17M/41.5M [00:28<20:46, 33.9kB/s]
- 3%|2 | 1.18M/41.5M [00:29<19:10, 36.8kB/s]
- 3%|2 | 1.19M/41.5M [00:29<17:59, 39.2kB/s]
- 3%|2 | 1.20M/41.5M [00:29<17:07, 41.1kB/s]
- 3%|2 | 1.20M/41.5M [00:29<16:30, 42.6kB/s]
- 3%|2 | 1.21M/41.5M [00:29<16:04, 43.8kB/s]
- 3%|2 | 1.22M/41.5M [00:30<15:45, 44.7kB/s]
- 3%|2 | 1.23M/41.5M [00:30<15:31, 45.3kB/s]
- 3%|2 | 1.24M/41.5M [00:30<11:50, 59.4kB/s]
- 3%|3 | 1.25M/41.5M [00:30<12:37, 55.7kB/s]
- 3%|3 | 1.26M/41.5M [00:30<13:14, 53.1kB/s]
- 3%|3 | 1.27M/41.5M [00:30<10:47, 65.1kB/s]
- 3%|3 | 1.28M/41.5M [00:31<15:16, 46.0kB/s]
- 3%|3 | 1.29M/41.5M [00:31<15:11, 46.2kB/s]
- 3%|3 | 1.30M/41.5M [00:31<15:08, 46.4kB/s]
- 3%|3 | 1.31M/41.5M [00:32<18:17, 38.4kB/s]
- 3%|3 | 1.32M/41.5M [00:32<17:30, 40.1kB/s]
- 3%|3 | 1.33M/41.5M [00:32<16:52, 41.6kB/s]
- 3%|3 | 1.34M/41.5M [00:32<20:19, 34.5kB/s]
- 3%|3 | 1.34M/41.5M [00:32<18:51, 37.2kB/s]
- 3%|3 | 1.35M/41.5M [00:33<17:45, 39.5kB/s]
- 3%|3 | 1.36M/41.5M [00:33<16:57, 41.4kB/s]
- 3%|3 | 1.37M/41.5M [00:33<16:22, 42.8kB/s]
- 3%|3 | 1.38M/41.5M [00:33<15:57, 43.9kB/s]
- 3%|3 | 1.38M/41.5M [00:33<15:39, 44.7kB/s]
- 3%|3 | 1.40M/41.5M [00:34<15:20, 45.7kB/s]
- 3%|3 | 1.41M/41.5M [00:34<12:54, 54.2kB/s]
- 3%|3 | 1.42M/41.5M [00:34<19:10, 36.5kB/s]
- 3%|3 | 1.45M/41.5M [00:35<17:06, 40.9kB/s]
- 4%|3 | 1.46M/41.5M [00:35<14:55, 46.8kB/s]
- 4%|3 | 1.47M/41.5M [00:35<15:37, 44.7kB/s]
- 4%|3 | 1.48M/41.5M [00:36<15:28, 45.2kB/s]
- 4%|3 | 1.48M/41.5M [00:36<15:20, 45.6kB/s]
- 4%|3 | 1.49M/41.5M [00:36<15:14, 45.9kB/s]
- 4%|3 | 1.50M/41.5M [00:36<15:09, 46.1kB/s]
- 4%|3 | 1.51M/41.5M [00:36<15:04, 46.3kB/s]
- 4%|3 | 1.52M/41.5M [00:36<15:01, 46.5kB/s]
- 4%|3 | 1.52M/41.5M [00:37<13:54, 50.2kB/s]
- 4%|3 | 1.53M/41.5M [00:37<14:11, 49.2kB/s]
- 4%|3 | 1.55M/41.5M [00:37<14:30, 48.1kB/s]
- 4%|3 | 1.56M/41.5M [00:37<11:43, 59.5kB/s]
- 4%|3 | 1.57M/41.5M [00:37<12:25, 56.2kB/s]
- 4%|3 | 1.58M/41.5M [00:38<13:00, 53.6kB/s]
- 4%|3 | 1.59M/41.5M [00:38<10:44, 64.9kB/s]
- 4%|3 | 1.60M/41.5M [00:38<11:40, 59.7kB/s]
- 4%|3 | 1.62M/41.5M [00:38<10:01, 69.5kB/s]
- 4%|3 | 1.62M/41.5M [00:38<11:04, 62.9kB/s]
- 4%|3 | 1.64M/41.5M [00:38<09:40, 72.0kB/s]
- 4%|3 | 1.66M/41.5M [00:39<09:29, 73.3kB/s]
- 4%|4 | 1.66M/41.5M [00:39<12:53, 54.0kB/s]
- 4%|4 | 1.69M/41.5M [00:39<09:43, 71.5kB/s]
- 4%|4 | 1.70M/41.5M [00:39<10:38, 65.3kB/s]
- 4%|4 | 1.70M/41.5M [00:40<11:29, 60.5kB/s]
- 4%|4 | 1.72M/41.5M [00:40<09:58, 69.6kB/s]
- 4%|4 | 1.73M/41.5M [00:40<09:05, 76.4kB/s]
- 4%|4 | 1.75M/41.5M [00:40<08:32, 81.3kB/s]
- 4%|4 | 1.77M/41.5M [00:41<12:55, 53.7kB/s]
- 4%|4 | 1.79M/41.5M [00:41<09:40, 71.7kB/s]
- 4%|4 | 1.80M/41.5M [00:41<11:06, 62.5kB/s]
- 4%|4 | 1.81M/41.5M [00:41<11:42, 59.2kB/s]
- 4%|4 | 1.83M/41.5M [00:42<10:19, 67.2kB/s]
- 4%|4 | 1.84M/41.5M [00:42<11:09, 62.1kB/s]
- 4%|4 | 1.85M/41.5M [00:42<09:50, 70.4kB/s]
- 4%|4 | 1.86M/41.5M [00:42<10:49, 64.0kB/s]
- 5%|4 | 1.88M/41.5M [00:42<09:34, 72.3kB/s]
- 5%|4 | 1.88M/41.5M [00:43<13:43, 50.4kB/s]
- 5%|4 | 1.90M/41.5M [00:43<11:22, 60.8kB/s]
- 5%|4 | 1.91M/41.5M [00:43<12:05, 57.2kB/s]
- 5%|4 | 1.91M/41.5M [00:43<12:42, 54.4kB/s]
- 5%|4 | 1.92M/41.5M [00:43<13:12, 52.3kB/s]
- 5%|4 | 1.93M/41.5M [00:44<17:27, 39.6kB/s]
- 5%|4 | 1.95M/41.5M [00:44<13:08, 52.6kB/s]
- 5%|4 | 1.95M/41.5M [00:44<13:31, 51.1kB/s]
- 5%|4 | 1.96M/41.5M [00:44<17:31, 39.4kB/s]
- 5%|4 | 1.98M/41.5M [00:44<13:16, 52.0kB/s]
- 5%|4 | 1.98M/41.5M [00:45<13:36, 50.7kB/s]
- 5%|4 | 1.99M/41.5M [00:45<13:53, 49.7kB/s]
- 5%|4 | 2.00M/41.5M [00:45<14:06, 48.9kB/s]
- 5%|4 | 2.01M/41.5M [00:45<14:16, 48.3kB/s]
- 5%|4 | 2.02M/41.5M [00:45<14:23, 47.9kB/s]
- 5%|4 | 2.03M/41.5M [00:46<11:16, 61.2kB/s]
- 5%|4 | 2.04M/41.5M [00:46<15:38, 44.1kB/s]
- 5%|4 | 2.05M/41.5M [00:46<15:15, 45.2kB/s]
- 5%|4 | 2.06M/41.5M [00:46<15:07, 45.6kB/s]
- 5%|4 | 2.07M/41.5M [00:47<15:01, 45.9kB/s]
- 5%|5 | 2.08M/41.5M [00:47<14:56, 46.1kB/s]
- 5%|5 | 2.09M/41.5M [00:47<18:49, 36.6kB/s]
- 5%|5 | 2.09M/41.5M [00:47<21:45, 31.6kB/s]
- 5%|5 | 2.11M/41.5M [00:48<18:37, 37.0kB/s]
- 5%|5 | 2.12M/41.5M [00:48<17:40, 38.9kB/s]
- 5%|5 | 2.12M/41.5M [00:48<16:54, 40.7kB/s]
- 5%|5 | 2.13M/41.5M [00:48<16:18, 42.2kB/s]
- 5%|5 | 2.14M/41.5M [00:48<15:51, 43.4kB/s]
- 5%|5 | 2.15M/41.5M [00:49<15:31, 44.3kB/s]
- 5%|5 | 2.16M/41.5M [00:49<15:16, 45.0kB/s]
- 5%|5 | 2.16M/41.5M [00:49<19:22, 35.5kB/s]
- 5%|5 | 2.18M/41.5M [00:49<13:55, 49.4kB/s]
- 5%|5 | 2.19M/41.5M [00:50<14:05, 48.7kB/s]
- 5%|5 | 2.20M/41.5M [00:50<18:02, 38.1kB/s]
- 5%|5 | 2.21M/41.5M [00:50<16:35, 41.4kB/s]
- 5%|5 | 2.22M/41.5M [00:51<19:33, 35.1kB/s]
- 5%|5 | 2.23M/41.5M [00:51<17:34, 39.0kB/s]
- 5%|5 | 2.24M/41.5M [00:51<20:10, 34.0kB/s]
- 5%|5 | 2.25M/41.5M [00:51<18:50, 36.4kB/s]
- 5%|5 | 2.26M/41.5M [00:52<21:30, 31.9kB/s]
- 5%|5 | 2.27M/41.5M [00:52<19:39, 34.9kB/s]
- 5%|5 | 2.27M/41.5M [00:52<18:15, 37.5kB/s]
- 5%|5 | 2.28M/41.5M [00:52<17:13, 39.8kB/s]
- 6%|5 | 2.29M/41.5M [00:53<16:28, 41.6kB/s]
- 6%|5 | 2.30M/41.5M [00:53<15:55, 43.0kB/s]
- 6%|5 | 2.30M/41.5M [00:53<19:50, 34.5kB/s]
- 6%|5 | 2.32M/41.5M [00:53<17:26, 39.2kB/s]
- 6%|5 | 2.33M/41.5M [00:54<31:06, 22.0kB/s]
- 6%|5 | 2.34M/41.5M [00:54<26:48, 25.5kB/s]
- 6%|5 | 2.34M/41.5M [00:55<39:19, 17.4kB/s]
- 6%|5 | 2.35M/41.5M [00:55<32:25, 21.1kB/s]
- 6%|5 | 2.36M/41.5M [00:56<31:29, 21.7kB/s]
- 6%|5 | 2.37M/41.5M [00:56<26:35, 25.7kB/s]
- 6%|5 | 2.38M/41.5M [00:56<27:21, 25.0kB/s]
- 6%|5 | 2.38M/41.5M [00:57<23:35, 29.0kB/s]
- 6%|5 | 2.39M/41.5M [00:57<20:54, 32.7kB/s]
- 6%|5 | 2.40M/41.5M [00:57<23:21, 29.2kB/s]
- 6%|5 | 2.41M/41.5M [00:57<20:44, 32.9kB/s]
- 6%|5 | 2.41M/41.5M [00:58<23:14, 29.4kB/s]
- 6%|5 | 2.42M/41.5M [00:58<20:38, 33.1kB/s]
- 6%|5 | 2.43M/41.5M [00:58<18:49, 36.3kB/s]
- 6%|5 | 2.45M/41.5M [00:58<13:29, 50.5kB/s]
- 6%|5 | 2.45M/41.5M [00:58<13:45, 49.6kB/s]
- 6%|5 | 2.46M/41.5M [00:58<13:58, 48.8kB/s]
- 6%|5 | 2.48M/41.5M [00:59<14:12, 48.0kB/s]
- 6%|6 | 2.49M/41.5M [00:59<11:34, 58.9kB/s]
- 6%|6 | 2.50M/41.5M [00:59<12:12, 55.8kB/s]
- 6%|6 | 2.51M/41.5M [00:59<12:44, 53.4kB/s]
- 6%|6 | 2.52M/41.5M [01:00<13:11, 51.6kB/s]
- 6%|6 | 2.52M/41.5M [01:00<18:19, 37.2kB/s]
- 6%|6 | 2.53M/41.5M [01:00<17:16, 39.4kB/s]
- 6%|6 | 2.54M/41.5M [01:00<16:30, 41.2kB/s]
- 6%|6 | 2.55M/41.5M [01:00<13:33, 50.2kB/s]
- 6%|6 | 2.56M/41.5M [01:01<13:47, 49.4kB/s]
- 6%|6 | 2.57M/41.5M [01:01<12:37, 53.9kB/s]
- 6%|6 | 2.58M/41.5M [01:01<13:07, 51.8kB/s]
- 6%|6 | 2.59M/41.5M [01:01<13:30, 50.3kB/s]
- 6%|6 | 2.59M/41.5M [01:01<17:53, 38.0kB/s]
- 6%|6 | 2.61M/41.5M [01:02<16:24, 41.4kB/s]
- 6%|6 | 2.62M/41.5M [01:02<15:56, 42.6kB/s]
- 6%|6 | 2.62M/41.5M [01:02<15:34, 43.6kB/s]
- 6%|6 | 2.63M/41.5M [01:03<23:03, 29.4kB/s]
- 6%|6 | 2.64M/41.5M [01:03<20:40, 32.8kB/s]
- 6%|6 | 2.65M/41.5M [01:03<27:08, 25.0kB/s]
- 6%|6 | 2.66M/41.5M [01:04<21:27, 31.6kB/s]
- 6%|6 | 2.67M/41.5M [01:04<23:16, 29.1kB/s]
- 6%|6 | 2.68M/41.5M [01:04<24:43, 27.4kB/s]
- 6%|6 | 2.69M/41.5M [01:05<25:51, 26.2kB/s]
- 6%|6 | 2.70M/41.5M [01:05<30:43, 22.1kB/s]
- 7%|6 | 2.70M/41.5M [01:06<26:06, 26.0kB/s]
- 7%|6 | 2.71M/41.5M [01:06<23:44, 28.5kB/s]
- 7%|6 | 2.72M/41.5M [01:06<24:14, 28.0kB/s]
- 7%|6 | 2.73M/41.5M [01:06<22:22, 30.3kB/s]
- 7%|6 | 2.73M/41.5M [01:06<20:01, 33.8kB/s]
- 7%|6 | 2.74M/41.5M [01:07<18:22, 36.9kB/s]
- 7%|6 | 2.75M/41.5M [01:07<16:09, 41.9kB/s]
- 7%|6 | 2.76M/41.5M [01:07<15:38, 43.3kB/s]
- 7%|6 | 2.77M/41.5M [01:07<15:17, 44.3kB/s]
- 7%|6 | 2.78M/41.5M [01:07<12:21, 54.7kB/s]
- 7%|6 | 2.79M/41.5M [01:07<12:00, 56.3kB/s]
- 7%|6 | 2.80M/41.5M [01:08<12:38, 53.5kB/s]
- 7%|6 | 2.81M/41.5M [01:08<10:19, 65.5kB/s]
- 7%|6 | 2.82M/41.5M [01:08<12:05, 55.9kB/s]
- 7%|6 | 2.84M/41.5M [01:08<09:27, 71.4kB/s]
- 7%|6 | 2.85M/41.5M [01:08<08:38, 78.2kB/s]
- 7%|6 | 2.87M/41.5M [01:09<10:36, 63.6kB/s]
- 7%|6 | 2.88M/41.5M [01:09<09:29, 71.1kB/s]
- 7%|6 | 2.89M/41.5M [01:09<14:07, 47.8kB/s]
- 7%|7 | 2.91M/41.5M [01:10<13:19, 50.6kB/s]
- 7%|7 | 2.92M/41.5M [01:10<13:40, 49.3kB/s]
- 7%|7 | 2.93M/41.5M [01:10<13:48, 48.8kB/s]
- 7%|7 | 2.94M/41.5M [01:10<13:55, 48.4kB/s]
- 7%|7 | 2.95M/41.5M [01:11<20:48, 32.4kB/s]
- 7%|7 | 2.96M/41.5M [01:11<15:19, 43.9kB/s]
- 7%|7 | 2.97M/41.5M [01:11<18:18, 36.8kB/s]
- 7%|7 | 2.98M/41.5M [01:11<17:21, 38.8kB/s]
- 7%|7 | 2.98M/41.5M [01:12<23:57, 28.1kB/s]
- 7%|7 | 2.99M/41.5M [01:12<21:22, 31.5kB/s]
- 7%|7 | 3.00M/41.5M [01:12<19:25, 34.6kB/s]
- 7%|7 | 3.01M/41.5M [01:12<17:59, 37.4kB/s]
- 7%|7 | 3.02M/41.5M [01:13<16:55, 39.7kB/s]
- 7%|7 | 3.02M/41.5M [01:13<16:10, 41.6kB/s]
- 7%|7 | 3.03M/41.5M [01:13<15:38, 43.0kB/s]
- 7%|7 | 3.04M/41.5M [01:14<23:45, 28.3kB/s]
- 7%|7 | 3.05M/41.5M [01:14<20:57, 32.1kB/s]
- 7%|7 | 3.05M/41.5M [01:14<18:58, 35.4kB/s]
- 7%|7 | 3.06M/41.5M [01:14<21:52, 30.7kB/s]
- 7%|7 | 3.07M/41.5M [01:14<19:37, 34.2kB/s]
- 7%|7 | 3.08M/41.5M [01:15<18:01, 37.2kB/s]
- 7%|7 | 3.09M/41.5M [01:15<21:12, 31.6kB/s]
- 7%|7 | 3.09M/41.5M [01:15<23:26, 28.6kB/s]
- 7%|7 | 3.10M/41.5M [01:16<26:10, 25.6kB/s]
- 7%|7 | 3.11M/41.5M [01:16<22:37, 29.6kB/s]
- 8%|7 | 3.12M/41.5M [01:16<23:16, 28.8kB/s]
- 8%|7 | 3.12M/41.5M [01:16<24:09, 27.7kB/s]
- 8%|7 | 3.13M/41.5M [01:17<21:54, 30.6kB/s]
- 8%|7 | 3.14M/41.5M [01:17<19:37, 34.2kB/s]
- 8%|7 | 3.15M/41.5M [01:17<18:01, 37.2kB/s]
- 8%|7 | 3.16M/41.5M [01:17<16:12, 41.4kB/s]
- 8%|7 | 3.16M/41.5M [01:17<15:37, 42.9kB/s]
- 8%|7 | 3.17M/41.5M [01:18<19:30, 34.3kB/s]
- 8%|7 | 3.18M/41.5M [01:18<17:56, 37.3kB/s]
- 8%|7 | 3.19M/41.5M [01:18<21:07, 31.7kB/s]
- 8%|7 | 3.20M/41.5M [01:19<23:21, 28.7kB/s]
- 8%|7 | 3.20M/41.5M [01:19<26:02, 25.7kB/s]
- 8%|7 | 3.21M/41.5M [01:19<22:30, 29.7kB/s]
- 8%|7 | 3.22M/41.5M [01:20<28:35, 23.4kB/s]
- 8%|7 | 3.23M/41.5M [01:20<29:31, 22.6kB/s]
- 8%|7 | 3.23M/41.5M [01:21<35:00, 19.1kB/s]
- 8%|7 | 3.24M/41.5M [01:21<33:03, 20.2kB/s]
- 8%|7 | 3.25M/41.5M [01:21<27:24, 24.4kB/s]
- 8%|7 | 3.26M/41.5M [01:22<27:44, 24.1kB/s]
- 8%|7 | 3.27M/41.5M [01:22<23:41, 28.2kB/s]
- 8%|7 | 3.27M/41.5M [01:22<20:51, 32.0kB/s]
- 8%|7 | 3.28M/41.5M [01:22<18:52, 35.4kB/s]
- 8%|7 | 3.30M/41.5M [01:22<13:26, 49.7kB/s]
- 8%|7 | 3.30M/41.5M [01:22<13:38, 48.9kB/s]
- 8%|7 | 3.31M/41.5M [01:23<13:47, 48.4kB/s]
- 8%|8 | 3.33M/41.5M [01:23<10:56, 61.0kB/s]
- 8%|8 | 3.34M/41.5M [01:23<15:03, 44.3kB/s]
- 8%|8 | 3.36M/41.5M [01:23<09:53, 67.4kB/s]
- 8%|8 | 3.37M/41.5M [01:23<10:43, 62.2kB/s]
- 8%|8 | 3.38M/41.5M [01:24<12:13, 54.5kB/s]
- 8%|8 | 3.39M/41.5M [01:24<09:36, 69.4kB/s]
- 8%|8 | 3.40M/41.5M [01:24<10:35, 62.9kB/s]
- 8%|8 | 3.41M/41.5M [01:24<14:45, 45.1kB/s]
- 8%|8 | 3.42M/41.5M [01:25<11:40, 56.9kB/s]
- 8%|8 | 3.43M/41.5M [01:25<15:23, 43.2kB/s]
- 8%|8 | 3.45M/41.5M [01:25<14:50, 44.8kB/s]
- 8%|8 | 3.45M/41.5M [01:25<14:41, 45.2kB/s]
- 8%|8 | 3.46M/41.5M [01:26<14:34, 45.6kB/s]
- 8%|8 | 3.47M/41.5M [01:26<14:28, 45.9kB/s]
- 8%|8 | 3.48M/41.5M [01:26<21:54, 30.3kB/s]
- 8%|8 | 3.48M/41.5M [01:26<19:47, 33.6kB/s]
- 8%|8 | 3.49M/41.5M [01:27<18:11, 36.5kB/s]
- 8%|8 | 3.50M/41.5M [01:27<18:52, 35.2kB/s]
- 8%|8 | 3.51M/41.5M [01:27<17:29, 37.9kB/s]
- 8%|8 | 3.52M/41.5M [01:27<16:31, 40.2kB/s]
- 8%|8 | 3.52M/41.5M [01:27<15:49, 41.9kB/s]
- 9%|8 | 3.53M/41.5M [01:28<15:19, 43.3kB/s]
- 9%|8 | 3.54M/41.5M [01:28<14:58, 44.3kB/s]
- 9%|8 | 3.55M/41.5M [01:28<14:35, 45.4kB/s]
- 9%|8 | 3.57M/41.5M [01:28<13:09, 50.4kB/s]
- 9%|8 | 3.58M/41.5M [01:29<13:22, 49.5kB/s]
- 9%|8 | 3.59M/41.5M [01:29<13:33, 48.9kB/s]
- 9%|8 | 3.60M/41.5M [01:29<13:47, 48.0kB/s]
- 9%|8 | 3.61M/41.5M [01:29<13:51, 47.8kB/s]
- 9%|8 | 3.62M/41.5M [01:29<13:55, 47.5kB/s]
- 9%|8 | 3.62M/41.5M [01:30<17:36, 37.6kB/s]
- 9%|8 | 3.63M/41.5M [01:30<16:40, 39.7kB/s]
- 9%|8 | 3.64M/41.5M [01:30<15:57, 41.5kB/s]
- 9%|8 | 3.65M/41.5M [01:30<15:25, 42.9kB/s]
- 9%|8 | 3.66M/41.5M [01:30<15:02, 43.9kB/s]
- 9%|8 | 3.66M/41.5M [01:31<14:46, 44.8kB/s]
- 9%|8 | 3.67M/41.5M [01:31<14:34, 45.4kB/s]
- 9%|8 | 3.68M/41.5M [01:31<14:26, 45.8kB/s]
- 9%|8 | 3.69M/41.5M [01:31<18:31, 35.7kB/s]
- 9%|8 | 3.70M/41.5M [01:31<13:14, 49.9kB/s]
- 9%|8 | 3.71M/41.5M [01:32<13:27, 49.1kB/s]
- 9%|8 | 3.72M/41.5M [01:32<13:36, 48.5kB/s]
- 9%|8 | 3.73M/41.5M [01:32<13:44, 48.0kB/s]
- 9%|9 | 3.74M/41.5M [01:32<13:52, 47.5kB/s]
- 9%|9 | 3.75M/41.5M [01:33<16:05, 41.0kB/s]
- 9%|9 | 3.77M/41.5M [01:33<16:16, 40.5kB/s]
- 9%|9 | 3.78M/41.5M [01:33<15:27, 42.6kB/s]
- 9%|9 | 3.79M/41.5M [01:34<15:10, 43.4kB/s]
- 9%|9 | 3.80M/41.5M [01:34<14:54, 44.2kB/s]
- 9%|9 | 3.80M/41.5M [01:34<14:42, 44.8kB/s]
- 9%|9 | 3.81M/41.5M [01:34<14:31, 45.3kB/s]
- 9%|9 | 3.82M/41.5M [01:34<14:23, 45.7kB/s]
- 9%|9 | 3.83M/41.5M [01:34<14:17, 46.0kB/s]
- 9%|9 | 3.84M/41.5M [01:35<14:13, 46.3kB/s]
- 9%|9 | 3.85M/41.5M [01:35<14:08, 46.5kB/s]
- 9%|9 | 3.87M/41.5M [01:35<11:20, 57.9kB/s]
- 9%|9 | 3.88M/41.5M [01:36<12:18, 53.4kB/s]
- 9%|9 | 3.90M/41.5M [01:36<10:30, 62.5kB/s]
- 9%|9 | 3.91M/41.5M [01:36<11:11, 58.7kB/s]
- 9%|9 | 3.91M/41.5M [01:36<11:48, 55.6kB/s]
- 9%|9 | 3.92M/41.5M [01:36<15:38, 42.0kB/s]
- 9%|9 | 3.94M/41.5M [01:37<14:58, 43.8kB/s]
- 10%|9 | 3.95M/41.5M [01:37<17:53, 36.7kB/s]
- 10%|9 | 3.95M/41.5M [01:37<20:20, 32.3kB/s]
- 10%|9 | 3.96M/41.5M [01:38<19:33, 33.5kB/s]
- 10%|9 | 3.97M/41.5M [01:38<25:34, 25.6kB/s]
- 10%|9 | 3.98M/41.5M [01:39<34:46, 18.9kB/s]
- 10%|9 | 3.98M/41.5M [01:39<36:48, 17.8kB/s]
- 10%|9 | 3.99M/41.5M [01:40<34:15, 19.1kB/s]
- 10%|9 | 4.00M/41.5M [01:40<32:24, 20.2kB/s]
- 10%|9 | 4.01M/41.5M [01:40<31:05, 21.1kB/s]
- 10%|9 | 4.02M/41.5M [01:41<26:02, 25.1kB/s]
- 10%|9 | 4.02M/41.5M [01:41<26:36, 24.6kB/s]
- 10%|9 | 4.03M/41.5M [01:41<22:50, 28.7kB/s]
- 10%|9 | 4.04M/41.5M [01:41<20:11, 32.4kB/s]
- 10%|9 | 4.05M/41.5M [01:42<18:19, 35.7kB/s]
- 10%|9 | 4.05M/41.5M [01:42<18:03, 36.2kB/s]
- 10%|9 | 4.06M/41.5M [01:42<16:49, 38.9kB/s]
- 10%|9 | 4.07M/41.5M [01:42<14:55, 43.8kB/s]
- 10%|9 | 4.08M/41.5M [01:42<14:37, 44.7kB/s]
- 10%|9 | 4.09M/41.5M [01:43<18:36, 35.1kB/s]
- 10%|9 | 4.09M/41.5M [01:43<15:32, 42.1kB/s]
- 10%|9 | 4.11M/41.5M [01:43<16:05, 40.6kB/s]
- 10%|9 | 4.12M/41.5M [01:43<15:33, 42.0kB/s]
- 10%|9 | 4.12M/41.5M [01:44<18:46, 34.8kB/s]
- 10%|9 | 4.13M/41.5M [01:44<17:27, 37.4kB/s]
- 10%|9 | 4.14M/41.5M [01:44<16:27, 39.6kB/s]
- 10%|9 | 4.15M/41.5M [01:44<15:44, 41.5kB/s]
- 10%|# | 4.16M/41.5M [01:44<11:47, 55.3kB/s]
- 10%|# | 4.17M/41.5M [01:45<12:18, 53.0kB/s]
- 10%|# | 4.19M/41.5M [01:45<12:57, 50.3kB/s]
- 10%|# | 4.20M/41.5M [01:45<10:44, 60.7kB/s]
- 10%|# | 4.21M/41.5M [01:46<20:06, 32.4kB/s]
- 10%|# | 4.23M/41.5M [01:46<15:10, 42.9kB/s]
- 10%|# | 4.23M/41.5M [01:46<14:54, 43.7kB/s]
- 10%|# | 4.24M/41.5M [01:46<14:40, 44.4kB/s]
- 10%|# | 4.25M/41.5M [01:47<17:55, 36.3kB/s]
- 10%|# | 4.26M/41.5M [01:47<20:30, 31.7kB/s]
- 10%|# | 4.27M/41.5M [01:47<17:39, 36.8kB/s]
- 10%|# | 4.29M/41.5M [01:48<14:11, 45.8kB/s]
- 10%|# | 4.30M/41.5M [01:48<14:07, 46.0kB/s]
- 10%|# | 4.30M/41.5M [01:48<14:03, 46.2kB/s]
- 10%|# | 4.31M/41.5M [01:48<17:28, 37.2kB/s]
- 10%|# | 4.32M/41.5M [01:48<15:44, 41.2kB/s]
- 10%|# | 4.33M/41.5M [01:49<15:14, 42.6kB/s]
- 10%|# | 4.34M/41.5M [01:49<14:50, 43.7kB/s]
- 10%|# | 4.34M/41.5M [01:49<14:33, 44.6kB/s]
- 10%|# | 4.35M/41.5M [01:49<14:21, 45.2kB/s]
- 11%|# | 4.36M/41.5M [01:49<14:12, 45.7kB/s]
- 11%|# | 4.37M/41.5M [01:50<22:16, 29.1kB/s]
- 11%|# | 4.38M/41.5M [01:50<15:14, 42.5kB/s]
- 11%|# | 4.39M/41.5M [01:50<14:53, 43.5kB/s]
- 11%|# | 4.40M/41.5M [01:50<14:37, 44.3kB/s]
- 11%|# | 4.41M/41.5M [01:50<14:24, 45.0kB/s]
- 11%|# | 4.41M/41.5M [01:51<14:14, 45.5kB/s]
- 11%|# | 4.42M/41.5M [01:51<18:03, 35.9kB/s]
- 11%|# | 4.44M/41.5M [01:52<19:15, 33.6kB/s]
- 11%|# | 4.45M/41.5M [01:52<17:55, 36.1kB/s]
- 11%|# | 4.45M/41.5M [01:52<16:52, 38.4kB/s]
- 11%|# | 4.46M/41.5M [01:52<19:45, 32.8kB/s]
- 11%|# | 4.47M/41.5M [01:52<18:06, 35.7kB/s]
- 11%|# | 4.48M/41.5M [01:53<16:53, 38.3kB/s]
- 11%|# | 4.49M/41.5M [01:53<12:24, 52.1kB/s]
- 11%|# | 4.50M/41.5M [01:53<12:44, 50.7kB/s]
- 11%|# | 4.51M/41.5M [01:53<13:00, 49.7kB/s]
- 11%|# | 4.52M/41.5M [01:53<10:25, 62.0kB/s]
- 11%|# | 4.53M/41.5M [01:53<11:11, 57.7kB/s]
- 11%|# | 4.55M/41.5M [01:54<12:14, 52.7kB/s]
- 11%|# | 4.56M/41.5M [01:54<10:17, 62.7kB/s]
- 11%|#1 | 4.57M/41.5M [01:54<13:50, 46.6kB/s]
- 11%|#1 | 4.59M/41.5M [01:54<09:29, 67.9kB/s]
- 11%|#1 | 4.60M/41.5M [01:55<10:16, 62.7kB/s]
- 11%|#1 | 4.61M/41.5M [01:55<10:59, 58.6kB/s]
- 11%|#1 | 4.62M/41.5M [01:55<11:37, 55.5kB/s]
- 11%|#1 | 4.62M/41.5M [01:55<12:08, 53.1kB/s]
- 11%|#1 | 4.63M/41.5M [01:55<12:33, 51.3kB/s]
- 11%|#1 | 4.64M/41.5M [01:56<16:35, 38.8kB/s]
- 11%|#1 | 4.66M/41.5M [01:56<15:20, 41.9kB/s]
- 11%|#1 | 4.66M/41.5M [01:56<14:57, 43.0kB/s]
- 11%|#1 | 4.67M/41.5M [01:56<14:38, 43.9kB/s]
- 11%|#1 | 4.68M/41.5M [01:57<18:02, 35.6kB/s]
- 11%|#1 | 4.69M/41.5M [01:57<20:39, 31.1kB/s]
- 11%|#1 | 4.70M/41.5M [01:57<22:34, 28.5kB/s]
- 11%|#1 | 4.71M/41.5M [01:58<18:36, 34.5kB/s]
- 11%|#1 | 4.72M/41.5M [01:58<20:44, 31.0kB/s]
- 11%|#1 | 4.73M/41.5M [01:58<18:55, 33.9kB/s]
- 11%|#1 | 4.73M/41.5M [01:59<17:31, 36.7kB/s]
- 11%|#1 | 4.74M/41.5M [01:59<16:27, 39.0kB/s]
- 11%|#1 | 4.76M/41.5M [01:59<12:13, 52.5kB/s]
- 11%|#1 | 4.77M/41.5M [01:59<12:34, 51.1kB/s]
- 12%|#1 | 4.77M/41.5M [01:59<12:51, 49.9kB/s]
- 12%|#1 | 4.78M/41.5M [01:59<13:04, 49.1kB/s]
- 12%|#1 | 4.79M/41.5M [02:00<13:14, 48.5kB/s]
- 12%|#1 | 4.80M/41.5M [02:00<10:25, 61.5kB/s]
- 12%|#1 | 4.81M/41.5M [02:00<11:11, 57.3kB/s]
- 12%|#1 | 4.82M/41.5M [02:00<15:18, 41.9kB/s]
- 12%|#1 | 4.84M/41.5M [02:01<12:04, 53.1kB/s]
- 12%|#1 | 4.85M/41.5M [02:01<13:03, 49.0kB/s]
- 12%|#1 | 4.86M/41.5M [02:01<13:11, 48.5kB/s]
- 12%|#1 | 4.87M/41.5M [02:01<13:18, 48.1kB/s]
- 12%|#1 | 4.88M/41.5M [02:01<13:23, 47.8kB/s]
- 12%|#1 | 4.88M/41.5M [02:02<13:27, 47.5kB/s]
- 12%|#1 | 4.89M/41.5M [02:02<13:30, 47.3kB/s]
- 12%|#1 | 4.90M/41.5M [02:02<13:32, 47.2kB/s]
- 12%|#1 | 4.91M/41.5M [02:02<17:30, 36.5kB/s]
- 12%|#1 | 4.93M/41.5M [02:03<15:21, 41.6kB/s]
- 12%|#1 | 4.94M/41.5M [02:03<17:51, 35.8kB/s]
- 12%|#1 | 4.95M/41.5M [02:03<17:39, 36.2kB/s]
- 12%|#1 | 4.95M/41.5M [02:03<16:39, 38.3kB/s]
- 12%|#1 | 4.96M/41.5M [02:04<19:24, 32.9kB/s]
- 12%|#1 | 4.97M/41.5M [02:04<21:32, 29.6kB/s]
- 12%|#1 | 4.98M/41.5M [02:05<26:56, 23.7kB/s]
- 12%|#2 | 4.99M/41.5M [02:05<21:02, 30.3kB/s]
- 12%|#2 | 5.00M/41.5M [02:05<19:15, 33.1kB/s]
- 12%|#2 | 5.01M/41.5M [02:06<21:17, 30.0kB/s]
- 12%|#2 | 5.02M/41.5M [02:06<19:13, 33.2kB/s]
- 12%|#2 | 5.02M/41.5M [02:06<21:26, 29.7kB/s]
- 12%|#2 | 5.04M/41.5M [02:07<30:25, 20.9kB/s]
- 12%|#2 | 5.05M/41.5M [02:07<26:23, 24.1kB/s]
- 12%|#2 | 5.05M/41.5M [02:08<26:35, 24.0kB/s]
- 12%|#2 | 5.06M/41.5M [02:08<23:06, 27.5kB/s]
- 12%|#2 | 5.07M/41.5M [02:08<20:28, 31.1kB/s]
- 12%|#2 | 5.08M/41.5M [02:09<26:12, 24.3kB/s]
- 12%|#2 | 5.09M/41.5M [02:09<20:32, 31.0kB/s]
- 12%|#2 | 5.10M/41.5M [02:09<18:51, 33.7kB/s]
- 12%|#2 | 5.11M/41.5M [02:09<17:29, 36.3kB/s]
- 12%|#2 | 5.12M/41.5M [02:09<16:26, 38.7kB/s]
- 12%|#2 | 5.12M/41.5M [02:10<15:38, 40.6kB/s]
- 12%|#2 | 5.13M/41.5M [02:10<15:02, 42.2kB/s]
- 12%|#2 | 5.14M/41.5M [02:10<14:36, 43.5kB/s]
- 12%|#2 | 5.15M/41.5M [02:10<14:18, 44.4kB/s]
- 12%|#2 | 5.16M/41.5M [02:11<18:04, 35.1kB/s]
- 12%|#2 | 5.17M/41.5M [02:11<12:54, 49.2kB/s]
- 12%|#2 | 5.18M/41.5M [02:11<13:03, 48.6kB/s]
- 13%|#2 | 5.19M/41.5M [02:11<13:10, 48.1kB/s]
- 13%|#2 | 5.20M/41.5M [02:11<10:26, 60.7kB/s]
- 13%|#2 | 5.21M/41.5M [02:11<11:09, 56.8kB/s]
- 13%|#2 | 5.22M/41.5M [02:12<11:45, 53.9kB/s]
- 13%|#2 | 5.23M/41.5M [02:12<15:46, 40.2kB/s]
- 13%|#2 | 5.24M/41.5M [02:12<11:55, 53.2kB/s]
- 13%|#2 | 5.25M/41.5M [02:12<15:27, 41.0kB/s]
- 13%|#2 | 5.27M/41.5M [02:13<14:40, 43.1kB/s]
- 13%|#2 | 5.27M/41.5M [02:13<14:24, 43.9kB/s]
- 13%|#2 | 5.28M/41.5M [02:13<17:27, 36.3kB/s]
- 13%|#2 | 5.29M/41.5M [02:13<16:26, 38.5kB/s]
- 13%|#2 | 5.30M/41.5M [02:14<15:38, 40.4kB/s]
- 13%|#2 | 5.30M/41.5M [02:14<22:31, 28.1kB/s]
- 13%|#2 | 5.32M/41.5M [02:14<15:32, 40.7kB/s]
- 13%|#2 | 5.33M/41.5M [02:15<18:17, 34.6kB/s]
- 13%|#2 | 5.34M/41.5M [02:15<17:03, 37.0kB/s]
- 13%|#2 | 5.34M/41.5M [02:15<19:42, 32.1kB/s]
- 13%|#2 | 5.35M/41.5M [02:15<17:58, 35.1kB/s]
- 13%|#2 | 5.36M/41.5M [02:16<16:42, 37.8kB/s]
- 13%|#2 | 5.37M/41.5M [02:16<15:46, 40.0kB/s]
- 13%|#2 | 5.38M/41.5M [02:16<15:05, 41.8kB/s]
- 13%|#2 | 5.38M/41.5M [02:16<14:36, 43.2kB/s]
- 13%|#2 | 5.39M/41.5M [02:16<14:16, 44.2kB/s]
- 13%|#3 | 5.40M/41.5M [02:16<14:01, 45.0kB/s]
- 13%|#3 | 5.41M/41.5M [02:17<13:51, 45.5kB/s]
- 13%|#3 | 5.42M/41.5M [02:17<10:34, 59.6kB/s]
- 13%|#3 | 5.43M/41.5M [02:17<11:16, 55.9kB/s]
- 13%|#3 | 5.44M/41.5M [02:17<11:50, 53.2kB/s]
- 13%|#3 | 5.45M/41.5M [02:17<09:39, 65.3kB/s]
- 13%|#3 | 5.46M/41.5M [02:18<10:32, 59.8kB/s]
- 13%|#3 | 5.47M/41.5M [02:18<11:15, 55.9kB/s]
- 13%|#3 | 5.48M/41.5M [02:18<09:21, 67.2kB/s]
- 13%|#3 | 5.49M/41.5M [02:18<10:17, 61.1kB/s]
- 13%|#3 | 5.51M/41.5M [02:18<08:52, 70.9kB/s]
- 13%|#3 | 5.52M/41.5M [02:18<09:52, 63.7kB/s]
- 13%|#3 | 5.52M/41.5M [02:19<13:55, 45.1kB/s]
- 13%|#3 | 5.55M/41.5M [02:19<11:24, 55.1kB/s]
- 13%|#3 | 5.56M/41.5M [02:20<14:45, 42.5kB/s]
- 13%|#3 | 5.58M/41.5M [02:20<12:11, 51.5kB/s]
- 13%|#3 | 5.59M/41.5M [02:20<12:24, 50.5kB/s]
- 13%|#3 | 5.59M/41.5M [02:20<12:36, 49.7kB/s]
- 14%|#3 | 5.60M/41.5M [02:20<12:47, 49.0kB/s]
- 14%|#3 | 5.61M/41.5M [02:21<12:56, 48.5kB/s]
- 14%|#3 | 5.62M/41.5M [02:21<13:02, 48.0kB/s]
- 14%|#3 | 5.63M/41.5M [02:21<10:19, 60.7kB/s]
- 14%|#3 | 5.64M/41.5M [02:21<14:10, 44.2kB/s]
- 14%|#3 | 5.66M/41.5M [02:22<14:31, 43.1kB/s]
- 14%|#3 | 5.66M/41.5M [02:22<16:28, 38.0kB/s]
- 14%|#3 | 5.67M/41.5M [02:22<15:43, 39.8kB/s]
- 14%|#3 | 5.68M/41.5M [02:22<15:06, 41.4kB/s]
- 14%|#3 | 5.69M/41.5M [02:22<14:38, 42.7kB/s]
- 14%|#3 | 5.70M/41.5M [02:23<14:17, 43.8kB/s]
- 14%|#3 | 5.70M/41.5M [02:23<14:00, 44.6kB/s]
- 14%|#3 | 5.71M/41.5M [02:23<13:49, 45.2kB/s]
- 14%|#3 | 5.72M/41.5M [02:23<13:40, 45.7kB/s]
- 14%|#3 | 5.73M/41.5M [02:23<13:34, 46.0kB/s]
- 14%|#3 | 5.74M/41.5M [02:24<16:30, 37.9kB/s]
- 14%|#3 | 5.76M/41.5M [02:24<15:15, 40.9kB/s]
- 14%|#3 | 5.78M/41.5M [02:24<10:17, 60.6kB/s]
- 14%|#3 | 5.79M/41.5M [02:25<13:13, 47.2kB/s]
- 14%|#3 | 5.80M/41.5M [02:25<13:14, 47.1kB/s]
- 14%|#3 | 5.80M/41.5M [02:25<13:15, 47.1kB/s]
- 14%|#4 | 5.81M/41.5M [02:25<13:15, 47.0kB/s]
- 14%|#4 | 5.82M/41.5M [02:25<13:16, 47.0kB/s]
- 14%|#4 | 5.83M/41.5M [02:26<13:16, 46.9kB/s]
- 14%|#4 | 5.84M/41.5M [02:26<13:16, 46.9kB/s]
- 14%|#4 | 5.84M/41.5M [02:26<13:16, 46.9kB/s]
- 14%|#4 | 5.85M/41.5M [02:26<17:07, 36.4kB/s]
- 14%|#4 | 5.87M/41.5M [02:27<15:22, 40.5kB/s]
- 14%|#4 | 5.88M/41.5M [02:27<18:06, 34.4kB/s]
- 14%|#4 | 5.88M/41.5M [02:27<17:41, 35.2kB/s]
- 14%|#4 | 5.89M/41.5M [02:28<19:12, 32.4kB/s]
- 14%|#4 | 5.90M/41.5M [02:28<18:26, 33.7kB/s]
- 14%|#4 | 5.91M/41.5M [02:28<16:58, 36.6kB/s]
- 14%|#4 | 5.91M/41.5M [02:28<15:54, 39.1kB/s]
- 14%|#4 | 5.92M/41.5M [02:28<15:07, 41.1kB/s]
- 14%|#4 | 5.93M/41.5M [02:29<22:24, 27.7kB/s]
- 14%|#4 | 5.94M/41.5M [02:29<18:43, 33.2kB/s]
- 14%|#4 | 5.95M/41.5M [02:29<18:04, 34.4kB/s]
- 14%|#4 | 5.95M/41.5M [02:29<16:37, 37.3kB/s]
- 14%|#4 | 5.96M/41.5M [02:29<14:38, 42.4kB/s]
- 14%|#4 | 5.97M/41.5M [02:30<14:14, 43.6kB/s]
- 14%|#4 | 5.98M/41.5M [02:30<13:56, 44.5kB/s]
- 14%|#4 | 5.98M/41.5M [02:30<21:39, 28.6kB/s]
- 14%|#4 | 6.00M/41.5M [02:31<15:26, 40.2kB/s]
- 14%|#4 | 6.01M/41.5M [02:31<14:53, 41.6kB/s]
- 14%|#4 | 6.02M/41.5M [02:31<14:27, 42.9kB/s]
- 15%|#4 | 6.02M/41.5M [02:31<14:06, 43.9kB/s]
- 15%|#4 | 6.03M/41.5M [02:31<13:51, 44.7kB/s]
- 15%|#4 | 6.04M/41.5M [02:31<13:40, 45.3kB/s]
- 15%|#4 | 6.05M/41.5M [02:32<13:32, 45.7kB/s]
- 15%|#4 | 6.05M/41.5M [02:32<17:20, 35.7kB/s]
- 15%|#4 | 6.07M/41.5M [02:32<12:26, 49.7kB/s]
- 15%|#4 | 6.08M/41.5M [02:32<12:37, 49.0kB/s]
- 15%|#4 | 6.09M/41.5M [02:32<12:46, 48.4kB/s]
- 15%|#4 | 6.10M/41.5M [02:33<10:08, 60.9kB/s]
- 15%|#4 | 6.11M/41.5M [02:33<13:55, 44.4kB/s]
- 15%|#4 | 6.12M/41.5M [02:33<17:02, 36.3kB/s]
- 15%|#4 | 6.13M/41.5M [02:33<12:41, 48.7kB/s]
- 15%|#4 | 6.14M/41.5M [02:34<15:49, 39.1kB/s]
- 15%|#4 | 6.16M/41.5M [02:34<15:23, 40.1kB/s]
- 15%|#4 | 6.16M/41.5M [02:34<14:53, 41.4kB/s]
- 15%|#4 | 6.17M/41.5M [02:35<17:38, 35.0kB/s]
- 15%|#4 | 6.18M/41.5M [02:35<16:29, 37.4kB/s]
- 15%|#4 | 6.19M/41.5M [02:35<15:36, 39.5kB/s]
- 15%|#4 | 6.20M/41.5M [02:35<18:33, 33.2kB/s]
- 15%|#4 | 6.20M/41.5M [02:36<20:46, 29.7kB/s]
- 15%|#4 | 6.22M/41.5M [02:36<17:21, 35.5kB/s]
- 15%|#5 | 6.23M/41.5M [02:36<13:09, 46.8kB/s]
- 15%|#5 | 6.24M/41.5M [02:37<13:09, 46.8kB/s]
- 15%|#5 | 6.25M/41.5M [02:37<13:09, 46.8kB/s]
- 15%|#5 | 6.26M/41.5M [02:37<13:08, 46.8kB/s]
- 15%|#5 | 6.27M/41.5M [02:37<16:37, 37.0kB/s]
- 15%|#5 | 6.28M/41.5M [02:37<12:16, 50.1kB/s]
- 15%|#5 | 6.29M/41.5M [02:38<15:34, 39.5kB/s]
- 15%|#5 | 6.30M/41.5M [02:38<18:15, 33.7kB/s]
- 15%|#5 | 6.31M/41.5M [02:38<16:06, 38.2kB/s]
- 15%|#5 | 6.32M/41.5M [02:39<15:24, 39.9kB/s]
- 15%|#5 | 6.33M/41.5M [02:39<14:50, 41.4kB/s]
- 15%|#5 | 6.34M/41.5M [02:39<14:23, 42.7kB/s]
- 15%|#5 | 6.34M/41.5M [02:39<14:02, 43.8kB/s]
- 15%|#5 | 6.35M/41.5M [02:39<13:46, 44.6kB/s]
- 15%|#5 | 6.36M/41.5M [02:40<17:19, 35.4kB/s]
- 15%|#5 | 6.38M/41.5M [02:40<13:09, 46.6kB/s]
- 15%|#5 | 6.38M/41.5M [02:40<13:08, 46.7kB/s]
- 15%|#5 | 6.39M/41.5M [02:40<13:07, 46.7kB/s]
- 15%|#5 | 6.40M/41.5M [02:40<13:07, 46.8kB/s]
- 15%|#5 | 6.41M/41.5M [02:41<13:06, 46.8kB/s]
- 15%|#5 | 6.41M/41.5M [02:41<14:04, 43.6kB/s]
- 15%|#5 | 6.43M/41.5M [02:41<12:52, 47.6kB/s]
- 16%|#5 | 6.44M/41.5M [02:41<12:55, 47.4kB/s]
- 16%|#5 | 6.45M/41.5M [02:41<12:57, 47.3kB/s]
- 16%|#5 | 6.46M/41.5M [02:42<10:14, 59.8kB/s]
- 16%|#5 | 6.47M/41.5M [02:42<10:53, 56.2kB/s]
- 16%|#5 | 6.48M/41.5M [02:42<11:25, 53.6kB/s]
- 16%|#5 | 6.48M/41.5M [02:42<10:42, 57.1kB/s]
- 16%|#5 | 6.50M/41.5M [02:42<09:50, 62.1kB/s]
- 16%|#5 | 6.51M/41.5M [02:42<10:35, 57.7kB/s]
- 16%|#5 | 6.52M/41.5M [02:43<08:57, 68.2kB/s]
- 16%|#5 | 6.53M/41.5M [02:43<08:54, 68.6kB/s]
- 16%|#5 | 6.54M/41.5M [02:43<10:56, 55.8kB/s]
- 16%|#5 | 6.55M/41.5M [02:43<10:55, 55.9kB/s]
- 16%|#5 | 6.57M/41.5M [02:43<09:17, 65.7kB/s]
- 16%|#5 | 6.58M/41.5M [02:44<10:03, 60.6kB/s]
- 16%|#5 | 6.59M/41.5M [02:44<10:26, 58.5kB/s]
- 16%|#5 | 6.60M/41.5M [02:44<08:52, 68.7kB/s]
- 16%|#5 | 6.62M/41.5M [02:44<08:01, 76.0kB/s]
- 16%|#5 | 6.62M/41.5M [02:44<09:02, 67.4kB/s]
- 16%|#6 | 6.64M/41.5M [02:45<08:05, 75.2kB/s]
- 16%|#6 | 6.66M/41.5M [02:45<07:33, 80.6kB/s]
- 16%|#6 | 6.67M/41.5M [02:45<09:34, 63.6kB/s]
- 16%|#6 | 6.69M/41.5M [02:45<08:22, 72.6kB/s]
- 16%|#6 | 6.70M/41.5M [02:45<07:46, 78.2kB/s]
- 16%|#6 | 6.72M/41.5M [02:46<07:22, 82.4kB/s]
- 16%|#6 | 6.73M/41.5M [02:46<09:05, 66.8kB/s]
- 16%|#6 | 6.75M/41.5M [02:46<08:17, 73.2kB/s]
- 16%|#6 | 6.77M/41.5M [02:46<07:44, 78.4kB/s]
- 16%|#6 | 6.78M/41.5M [02:46<07:21, 82.5kB/s]
- 16%|#6 | 6.80M/41.5M [02:47<07:05, 85.6kB/s]
- 16%|#6 | 6.81M/41.5M [02:47<13:03, 46.4kB/s]
- 16%|#6 | 6.84M/41.5M [02:48<09:47, 61.8kB/s]
- 17%|#6 | 6.87M/41.5M [02:48<11:09, 54.2kB/s]
- 17%|#6 | 6.88M/41.5M [02:49<13:07, 46.1kB/s]
- 17%|#6 | 6.89M/41.5M [02:49<13:05, 46.2kB/s]
- 17%|#6 | 6.90M/41.5M [02:49<15:16, 39.6kB/s]
- 17%|#6 | 6.91M/41.5M [02:49<14:48, 40.8kB/s]
- 17%|#6 | 6.91M/41.5M [02:50<17:13, 35.1kB/s]
- 17%|#6 | 6.93M/41.5M [02:50<18:02, 33.5kB/s]
- 17%|#6 | 6.94M/41.5M [02:51<28:04, 21.5kB/s]
- 17%|#6 | 6.95M/41.5M [02:51<24:28, 24.7kB/s]
- 17%|#6 | 6.95M/41.5M [02:52<24:47, 24.3kB/s]
- 17%|#6 | 6.96M/41.5M [02:52<28:27, 21.2kB/s]
- 17%|#6 | 6.97M/41.5M [02:53<27:42, 21.8kB/s]
- 17%|#6 | 6.98M/41.5M [02:53<27:09, 22.2kB/s]
- 17%|#6 | 6.98M/41.5M [02:53<26:44, 22.6kB/s]
- 17%|#6 | 6.99M/41.5M [02:53<22:42, 26.6kB/s]
- 17%|#6 | 7.00M/41.5M [02:54<27:21, 22.0kB/s]
- 17%|#6 | 7.01M/41.5M [02:54<26:52, 22.4kB/s]
- 17%|#6 | 7.02M/41.5M [02:55<22:42, 26.5kB/s]
- 17%|#6 | 7.02M/41.5M [02:55<19:46, 30.5kB/s]
- 17%|#6 | 7.03M/41.5M [02:55<25:22, 23.7kB/s]
- 17%|#6 | 7.04M/41.5M [02:56<25:28, 23.6kB/s]
- 17%|#6 | 7.05M/41.5M [02:56<21:41, 27.7kB/s]
- 17%|#7 | 7.05M/41.5M [02:56<27:18, 22.0kB/s]
- 17%|#7 | 7.07M/41.5M [02:57<23:08, 26.0kB/s]
- 17%|#7 | 7.08M/41.5M [02:57<26:56, 22.3kB/s]
- 17%|#7 | 7.09M/41.5M [02:58<26:36, 22.6kB/s]
- 17%|#7 | 7.09M/41.5M [02:58<22:51, 26.3kB/s]
- 17%|#7 | 7.10M/41.5M [02:58<23:38, 25.4kB/s]
- 17%|#7 | 7.11M/41.5M [02:58<22:02, 27.3kB/s]
- 17%|#7 | 7.12M/41.5M [02:59<33:25, 18.0kB/s]
- 17%|#7 | 7.13M/41.5M [03:00<23:35, 25.5kB/s]
- 17%|#7 | 7.14M/41.5M [03:00<21:29, 27.9kB/s]
- 17%|#7 | 7.15M/41.5M [03:00<21:58, 27.3kB/s]
- 17%|#7 | 7.16M/41.5M [03:01<26:24, 22.7kB/s]
- 17%|#7 | 7.17M/41.5M [03:01<18:52, 31.8kB/s]
- 17%|#7 | 7.18M/41.5M [03:01<22:12, 27.0kB/s]
- 17%|#7 | 7.20M/41.5M [03:02<20:58, 28.6kB/s]
- 17%|#7 | 7.20M/41.5M [03:02<19:09, 31.3kB/s]
- 17%|#7 | 7.21M/41.5M [03:02<17:36, 34.0kB/s]
- 17%|#7 | 7.22M/41.5M [03:02<16:21, 36.6kB/s]
- 17%|#7 | 7.23M/41.5M [03:03<15:23, 38.9kB/s]
- 17%|#7 | 7.23M/41.5M [03:03<14:40, 40.8kB/s]
- 17%|#7 | 7.24M/41.5M [03:03<17:45, 33.7kB/s]
- 17%|#7 | 7.25M/41.5M [03:03<19:59, 29.9kB/s]
- 17%|#7 | 7.26M/41.5M [03:04<17:52, 33.5kB/s]
- 18%|#7 | 7.27M/41.5M [03:04<23:53, 25.0kB/s]
- 18%|#7 | 7.27M/41.5M [03:04<20:35, 29.0kB/s]
- 18%|#7 | 7.28M/41.5M [03:05<26:45, 22.3kB/s]
- 18%|#7 | 7.29M/41.5M [03:05<23:58, 24.9kB/s]
- 18%|#7 | 7.30M/41.5M [03:05<24:25, 24.5kB/s]
- 18%|#7 | 7.30M/41.5M [03:06<20:55, 28.5kB/s]
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- 24%|##3 | 9.88M/41.5M [04:08<09:45, 56.6kB/s]
- 24%|##3 | 9.90M/41.5M [04:08<07:39, 72.1kB/s]
- 24%|##3 | 9.91M/41.5M [04:09<09:18, 59.2kB/s]
- 24%|##3 | 9.93M/41.5M [04:09<07:45, 71.1kB/s]
- 24%|##3 | 9.95M/41.5M [04:09<08:51, 62.2kB/s]
- 24%|##4 | 9.96M/41.5M [04:10<10:04, 54.7kB/s]
- 24%|##4 | 9.97M/41.5M [04:10<09:53, 55.7kB/s]
- 24%|##4 | 9.98M/41.5M [04:10<12:31, 44.0kB/s]
- 24%|##4 | 9.98M/41.5M [04:10<14:53, 37.0kB/s]
- 24%|##4 | 10.0M/41.5M [04:11<13:41, 40.2kB/s]
- 24%|##4 | 10.0M/41.5M [04:12<21:12, 25.9kB/s]
- 24%|##4 | 10.0M/41.5M [04:12<14:31, 37.8kB/s]
- 24%|##4 | 10.0M/41.5M [04:12<14:00, 39.3kB/s]
- 24%|##4 | 10.0M/41.5M [04:12<13:31, 40.6kB/s]
- 24%|##4 | 10.1M/41.5M [04:12<13:06, 41.9kB/s]
- 24%|##4 | 10.1M/41.5M [04:13<15:39, 35.1kB/s]
- 24%|##4 | 10.1M/41.5M [04:13<17:41, 31.0kB/s]
- 24%|##4 | 10.1M/41.5M [04:13<15:07, 36.3kB/s]
- 24%|##4 | 10.1M/41.5M [04:14<14:19, 38.3kB/s]
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- 24%|##4 | 10.1M/41.5M [04:14<14:59, 36.6kB/s]
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- 24%|##4 | 10.1M/41.5M [04:15<12:53, 42.5kB/s]
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- 26%|##5 | 10.6M/41.5M [04:24<05:38, 95.7kB/s]
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- 26%|##5 | 10.6M/41.5M [04:24<04:57, 109kB/s]
- 26%|##5 | 10.7M/41.5M [04:25<05:10, 104kB/s]
- 26%|##5 | 10.7M/41.5M [04:25<04:42, 114kB/s]
- 26%|##5 | 10.7M/41.5M [04:25<03:55, 137kB/s]
- 26%|##5 | 10.7M/41.5M [04:25<05:03, 106kB/s]
- 26%|##5 | 10.8M/41.5M [04:26<04:43, 114kB/s]
- 26%|##5 | 10.8M/41.5M [04:26<04:56, 109kB/s]
- 26%|##6 | 10.8M/41.5M [04:26<05:07, 105kB/s]
- 26%|##6 | 10.8M/41.5M [04:26<05:16, 102kB/s]
- 26%|##6 | 10.8M/41.5M [04:26<05:23, 99.3kB/s]
- 26%|##6 | 10.8M/41.5M [04:26<05:28, 97.7kB/s]
- 26%|##6 | 10.9M/41.5M [04:27<05:32, 96.5kB/s]
- 26%|##6 | 10.9M/41.5M [04:27<05:35, 95.7kB/s]
- 26%|##6 | 10.9M/41.5M [04:27<05:37, 95.1kB/s]
- 26%|##6 | 10.9M/41.5M [04:27<05:38, 94.7kB/s]
- 26%|##6 | 10.9M/41.5M [04:27<05:39, 94.4kB/s]
- 26%|##6 | 10.9M/41.5M [04:27<05:40, 94.2kB/s]
- 26%|##6 | 11.0M/41.5M [04:28<07:22, 72.4kB/s]
- 26%|##6 | 11.0M/41.5M [04:28<08:05, 66.0kB/s]
- 26%|##6 | 11.0M/41.5M [04:28<08:44, 61.0kB/s]
- 26%|##6 | 11.0M/41.5M [04:28<07:37, 69.9kB/s]
- 26%|##6 | 11.0M/41.5M [04:29<08:24, 63.4kB/s]
- 27%|##6 | 11.0M/41.5M [04:29<09:04, 58.7kB/s]
- 27%|##6 | 11.0M/41.5M [04:29<07:44, 68.8kB/s]
- 27%|##6 | 11.0M/41.5M [04:29<08:31, 62.4kB/s]
- 27%|##6 | 11.0M/41.5M [04:29<09:12, 57.8kB/s]
- 27%|##6 | 11.0M/41.5M [04:30<10:04, 52.8kB/s]
- 27%|##6 | 11.1M/41.5M [04:30<07:08, 74.4kB/s]
- 27%|##6 | 11.1M/41.5M [04:30<07:54, 67.2kB/s]
- 27%|##6 | 11.1M/41.5M [04:30<08:36, 61.7kB/s]
- 27%|##6 | 11.1M/41.5M [04:30<09:36, 55.2kB/s]
- 27%|##6 | 11.1M/41.5M [04:31<07:32, 70.3kB/s]
- 27%|##6 | 11.1M/41.5M [04:31<07:35, 69.9kB/s]
- 27%|##6 | 11.1M/41.5M [04:31<07:31, 70.5kB/s]
- 27%|##6 | 11.2M/41.5M [04:31<07:34, 70.0kB/s]
- 27%|##6 | 11.2M/41.5M [04:31<06:56, 76.4kB/s]
- 27%|##6 | 11.2M/41.5M [04:31<06:59, 75.8kB/s]
- 27%|##6 | 11.2M/41.5M [04:32<06:30, 81.3kB/s]
- 27%|##7 | 11.2M/41.5M [04:32<06:54, 76.6kB/s]
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- 27%|##7 | 11.2M/41.5M [04:32<05:46, 91.7kB/s]
- 27%|##7 | 11.3M/41.5M [04:32<05:43, 92.3kB/s]
- 27%|##7 | 11.3M/41.5M [04:32<05:41, 92.8kB/s]
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- 27%|##7 | 11.4M/41.5M [04:35<08:49, 59.6kB/s]
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- 28%|##7 | 11.6M/41.5M [04:39<06:45, 77.2kB/s]
- 28%|##8 | 11.6M/41.5M [04:39<06:21, 82.1kB/s]
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- 30%|### | 12.5M/41.5M [04:54<05:22, 94.6kB/s]
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- 31%|### | 12.7M/41.5M [04:58<08:57, 56.3kB/s]
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- 31%|### | 12.8M/41.5M [05:03<11:54, 42.1kB/s]
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- 31%|###1 | 12.9M/41.5M [05:04<10:55, 45.8kB/s]
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- 33%|###3 | 13.7M/41.5M [05:23<09:59, 48.6kB/s]
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- 56%|#####5 | 23.1M/41.5M [08:59<12:26, 25.8kB/s]
- 56%|#####5 | 23.1M/41.5M [08:59<11:09, 28.8kB/s]
- 56%|#####5 | 23.1M/41.5M [08:59<11:47, 27.3kB/s]
- 56%|#####5 | 23.1M/41.5M [09:00<14:03, 22.8kB/s]
- 56%|#####5 | 23.1M/41.5M [09:00<12:26, 25.8kB/s]
- 56%|#####5 | 23.1M/41.5M [09:01<16:10, 19.8kB/s]
- 56%|#####5 | 23.1M/41.5M [09:01<13:50, 23.2kB/s]
- 56%|#####5 | 23.2M/41.5M [09:01<11:59, 26.7kB/s]
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- 56%|#####5 | 23.2M/41.5M [09:03<09:30, 33.6kB/s]
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- 56%|#####6 | 23.2M/41.5M [09:04<08:45, 36.4kB/s]
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