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Posted to commits@mxnet.apache.org by ta...@apache.org on 2020/04/22 03:18:15 UTC
[incubator-mxnet] branch v1.7.x updated: change error tolerance for
bf16 bn (#18110)
This is an automated email from the ASF dual-hosted git repository.
taolv pushed a commit to branch v1.7.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.7.x by this push:
new 6e956fd change error tolerance for bf16 bn (#18110)
6e956fd is described below
commit 6e956fd2b78fcd20e732a1f1d915da630ea1d999
Author: rongzha1 <ro...@intel.com>
AuthorDate: Wed Apr 22 11:17:17 2020 +0800
change error tolerance for bf16 bn (#18110)
---
tests/python/mkl/test_bf16_operator.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/tests/python/mkl/test_bf16_operator.py b/tests/python/mkl/test_bf16_operator.py
index e4f4a93..b275c96 100644
--- a/tests/python/mkl/test_bf16_operator.py
+++ b/tests/python/mkl/test_bf16_operator.py
@@ -126,8 +126,8 @@ def test_bf16_bn():
bn_fp32 = mx.sym.BatchNorm(data_sym_fp32, **bn_params)
bn_bf16 = mx.sym.BatchNorm(data_sym_bf16, **bn_params)
- check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28), bf16_use_fp32_params=True, etol=1e-3)
- check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(32, 16, 64, 64), bf16_use_fp32_params=True, etol=1e-3)
+ check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28), bf16_use_fp32_params=True, etol=1e-2)
+ check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(32, 16, 64, 64), bf16_use_fp32_params=True, etol=1e-2)
@with_seed()
def test_bf16_conv():
@@ -278,7 +278,7 @@ def test_bf16_fallback():
bn_params = {"eps": 2e-05, "fix_gamma": False, "use_global_stats": True, "name": "bn"}
bn_fp32 = mx.sym.BatchNorm(data_sym_fp32, **bn_params)
bn_bf16=mx.sym.BatchNorm(data_sym_bf16, **bn_params)
- check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28, 3), bf16_use_fp32_params=True, etol=1e-3)
+ check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28, 3), bf16_use_fp32_params=True, etol=1e-2)
conv_params = {"kernel": (3, 3, 3), "num_filter": 128, "pad": (1, 1, 1), "stride": (1, 1, 1), "no_bias": True, "name": "conv"}
conv_fp32 = mx.sym.Convolution(data_sym_fp32, **conv_params)