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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2022/09/02 17:50:05 UTC
[GitHub] [tvm] comaniac commented on a diff in pull request #12685: [AutoTVM][Testing] Add `tune_relay` scripts
comaniac commented on code in PR #12685:
URL: https://github.com/apache/tvm/pull/12685#discussion_r961892837
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python/tvm/autotvm/testing/tune_relay.py:
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@@ -0,0 +1,245 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=missing-docstring
+import argparse
+import json
+import os
+from distutils.util import strtobool
+
+import tvm
+from tvm import autotvm
+from tvm import meta_schedule as ms
+from tvm import relay
+from tvm.autotvm.graph_tuner import DPTuner
+from tvm.autotvm.tuner import XGBTuner
+from tvm.meta_schedule.testing.custom_builder_runner import run_module_via_rpc
+from tvm.meta_schedule.testing.relay_workload import get_network
+from tvm.meta_schedule.testing.tune_utils import create_timer, generate_input_data
+from tvm.support import describe
+
+
+def _parse_args():
+ args = argparse.ArgumentParser()
Review Comment:
I feel most arguments could have a default value to at least give people some senses. For example, I have no idea about what to put to `workload` and `input-shape` in terms of options and format.
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python/tvm/autotvm/testing/tune_relay.py:
##########
@@ -0,0 +1,245 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=missing-docstring
+import argparse
+import json
+import os
+from distutils.util import strtobool
+
+import tvm
+from tvm import autotvm
+from tvm import meta_schedule as ms
+from tvm import relay
+from tvm.autotvm.graph_tuner import DPTuner
+from tvm.autotvm.tuner import XGBTuner
+from tvm.meta_schedule.testing.custom_builder_runner import run_module_via_rpc
+from tvm.meta_schedule.testing.relay_workload import get_network
+from tvm.meta_schedule.testing.tune_utils import create_timer, generate_input_data
+from tvm.support import describe
+
+
+def _parse_args():
+ args = argparse.ArgumentParser()
+ args.add_argument(
+ "--workload",
+ type=str,
+ required=True,
+ )
+ args.add_argument(
+ "--input-shape",
+ type=str,
+ required=True,
+ )
+ args.add_argument(
+ "--target",
+ type=str,
+ required=True,
+ )
+ args.add_argument(
+ "--num-trials",
+ type=int,
+ required=True,
+ )
+ args.add_argument(
+ "--rpc-host",
+ type=str,
+ required=True,
+ )
+ args.add_argument(
+ "--rpc-port",
+ type=int,
+ required=True,
+ )
+ args.add_argument(
+ "--rpc-key",
+ type=str,
+ required=True,
+ )
+ args.add_argument(
+ "--work-dir",
+ type=str,
+ required=True,
+ )
+ args.add_argument(
+ "--layout",
+ type=str,
+ default=None,
+ )
+ args.add_argument(
+ "--cache-dir",
+ type=str,
+ default=None,
+ )
+ args.add_argument(
+ "--number",
+ type=int,
+ default=3,
+ )
+ args.add_argument(
+ "--repeat",
+ type=int,
+ default=1,
+ )
+ args.add_argument(
+ "--min-repeat-ms",
+ type=int,
+ default=100,
+ )
+ args.add_argument(
+ "--cpu-flush",
+ type=lambda x: bool(strtobool(x)),
+ help="example: True / False",
+ required=True,
+ )
+ args.add_argument(
+ "--graph-tuner",
+ type=lambda x: bool(strtobool(x)),
+ help="example: True / False",
+ required=True,
+ )
+ args.add_argument(
+ "--backend",
+ type=str,
+ choices=["graph", "vm"],
+ help="example: graph / vm",
+ required=True,
+ )
+ parsed = args.parse_args()
+ parsed.target = tvm.target.Target(parsed.target)
+ parsed.input_shape = json.loads(parsed.input_shape)
+ parsed.rpc_config = ms.runner.RPCConfig(
+ tracker_host=parsed.rpc_host,
+ tracker_port=parsed.rpc_port,
+ tracker_key=parsed.rpc_key,
+ session_timeout_sec=600,
+ )
+ return parsed
+
+
+ARGS = _parse_args()
+
+
+def main():
+ log_file = os.path.join(ARGS.work_dir, f"{ARGS.workload}.json")
+ graph_opt_sch_file = os.path.join(ARGS.work_dir, f"{ARGS.workload}_graph_opt.log")
+ measure_option = autotvm.measure_option(
+ builder=autotvm.LocalBuilder(),
+ runner=autotvm.RPCRunner(
+ key=ARGS.rpc_key,
+ host=ARGS.rpc_host,
+ port=ARGS.rpc_port,
+ number=ARGS.number,
+ repeat=ARGS.repeat,
+ min_repeat_ms=ARGS.min_repeat_ms,
+ enable_cpu_cache_flush=ARGS.cpu_flush,
+ ),
+ )
+ describe()
+ print(f"Workload: {ARGS.workload}")
+ mod, params, (input_name, input_shape, input_dtype) = get_network(
+ ARGS.workload,
+ ARGS.input_shape,
+ layout=ARGS.layout,
+ cache_dir=ARGS.cache_dir,
+ )
+ input_info = [
+ {
+ "name": input_name,
+ "shape": input_shape,
+ "dtype": input_dtype,
+ },
+ ]
+ input_data = {
+ item["name"]: generate_input_data(item["shape"], item["dtype"]) for item in input_info
+ }
+ for item in input_info:
+ print(f" input_name : {item['name']}")
+ print(f" input_shape: {item['shape']}")
+ print(f" input_dtype: {item['dtype']}")
+
+ with ms.Profiler() as profiler:
+ with ms.Profiler.timeit("TaskExtraction"):
+ # extract workloads from relay program
+ tasks = autotvm.task.extract_from_program(
+ mod["main"],
+ target=ARGS.target,
+ params=params,
+ ops=(
+ relay.op.get("nn.conv2d"),
+ relay.op.get("nn.conv3d"),
+ relay.op.get("nn.conv2d_transpose"),
+ relay.op.get("nn.dense"),
+ relay.op.get("nn.batch_matmul"),
+ ),
+ )
+ for i, task in enumerate(tasks):
+ print(f"Task {i} {task.name}: {task}")
+
+ with ms.Profiler.timeit("Tuning"):
+ if ARGS.num_trials > 0:
+ for i, task in enumerate(tasks):
+ prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
+ tuner_obj = XGBTuner(task, loss_type="rank")
+ n_trial = min(len(task.config_space), ARGS.num_trials)
+ tuner_obj.tune(
+ n_trial=n_trial,
+ early_stopping=800,
+ measure_option=measure_option,
+ callbacks=[
+ autotvm.callback.progress_bar(n_trial, prefix=prefix),
+ autotvm.callback.log_to_file(log_file),
+ ],
+ )
+ if ARGS.graph_tuner:
Review Comment:
Also need to check `target`, since only CPU needs graph tuner.
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