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Extract arguments to its own file and pass arguments to ios apps (#15413)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/15413 In order to pass arguments to the ios app, need to extarct the arguments to its own file. Also, in the ios app, do not use the benchmark.json, which parses the arguments. This is an incompatible change, needs to add hot fix to the tests. Reviewed By: llyfacebook Differential Revision: D13523240 fbshipit-source-id: b559cc7f52d8f50ee206a7ff8d7b59292d855197
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90
binaries/benchmark_args.h
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90
binaries/benchmark_args.h
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/**
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* Copyright (c) 2016-present, Facebook, Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include "c10/util/Flags.h"
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C10_DEFINE_string(
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backend,
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"builtin",
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"The backend to use when running the model. The allowed "
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"backend choices are: builtin, default, nnpack, eigen, mkl, cuda");
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C10_DEFINE_string(init_net, "", "The given net to initialize any parameters.");
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C10_DEFINE_string(
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input,
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"",
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"Input that is needed for running the network. If "
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"multiple input needed, use comma separated string.");
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C10_DEFINE_string(
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input_dims,
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"",
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"Alternate to input_files, if all inputs are simple "
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"float TensorCPUs, specify the dimension using comma "
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"separated numbers. If multiple input needed, use "
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"semicolon to separate the dimension of different "
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"tensors.");
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C10_DEFINE_string(
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input_file,
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"",
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"Input file that contain the serialized protobuf for "
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"the input blobs. If multiple input needed, use comma "
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"separated string. Must have the same number of items "
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"as input does.");
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C10_DEFINE_string(
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input_type,
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"float",
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"Input type when specifying the input dimension."
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"The supported types are float, uint8_t.");
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C10_DEFINE_int(iter, 10, "The number of iterations to run.");
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C10_DEFINE_string(net, "", "The given net to benchmark.");
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C10_DEFINE_string(
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output,
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"",
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"Output that should be dumped after the execution "
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"finishes. If multiple outputs are needed, use comma "
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"separated string. If you want to dump everything, pass "
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"'*' as the output value.");
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C10_DEFINE_string(
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output_folder,
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"",
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"The folder that the output should be written to. This "
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"folder must already exist in the file system.");
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C10_DEFINE_bool(
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run_individual,
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false,
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"Whether to benchmark individual operators.");
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C10_DEFINE_int(
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sleep_before_run,
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0,
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"The seconds to sleep before starting the benchmarking.");
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C10_DEFINE_int(
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sleep_between_iteration,
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0,
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"The seconds to sleep between the individual iterations.");
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C10_DEFINE_int(
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sleep_between_net_and_operator,
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0,
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"The seconds to sleep between net and operator runs.");
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C10_DEFINE_bool(
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text_output,
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false,
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"Whether to write out output in text format for regression purpose.");
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C10_DEFINE_int(warmup, 0, "The number of iterations to warm up.");
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C10_DEFINE_bool(
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wipe_cache,
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false,
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"Whether to evict the cache before running network.");
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@ -2,6 +2,7 @@
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#include <iterator>
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#include <string>
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#include "binaries/benchmark_args.h"
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#include "binaries/benchmark_helper.h"
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using std::make_shared;
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@ -9,78 +10,6 @@ using std::map;
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using std::string;
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using std::vector;
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C10_DEFINE_string(
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backend,
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"builtin",
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"The backend to use when running the model. The allowed "
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"backend choices are: builtin, default, nnpack, eigen, mkl, cuda");
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C10_DEFINE_string(init_net, "", "The given net to initialize any parameters.");
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C10_DEFINE_string(
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input,
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"",
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"Input that is needed for running the network. If "
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"multiple input needed, use comma separated string.");
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C10_DEFINE_string(
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input_dims,
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"",
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"Alternate to input_files, if all inputs are simple "
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"float TensorCPUs, specify the dimension using comma "
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"separated numbers. If multiple input needed, use "
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"semicolon to separate the dimension of different "
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"tensors.");
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C10_DEFINE_string(
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input_file,
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"",
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"Input file that contain the serialized protobuf for "
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"the input blobs. If multiple input needed, use comma "
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"separated string. Must have the same number of items "
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"as input does.");
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C10_DEFINE_string(
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input_type,
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"float",
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"Input type when specifying the input dimension."
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"The supported types are float, uint8_t.");
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C10_DEFINE_int(iter, 10, "The number of iterations to run.");
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C10_DEFINE_string(net, "", "The given net to benchmark.");
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C10_DEFINE_string(
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output,
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"",
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"Output that should be dumped after the execution "
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"finishes. If multiple outputs are needed, use comma "
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"separated string. If you want to dump everything, pass "
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"'*' as the output value.");
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C10_DEFINE_string(
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output_folder,
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"",
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"The folder that the output should be written to. This "
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"folder must already exist in the file system.");
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C10_DEFINE_bool(
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run_individual,
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false,
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"Whether to benchmark individual operators.");
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C10_DEFINE_int(
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sleep_before_run,
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0,
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"The seconds to sleep before starting the benchmarking.");
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C10_DEFINE_int(
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sleep_between_iteration,
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0,
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"The seconds to sleep between the individual iterations.");
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C10_DEFINE_int(
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sleep_between_net_and_operator,
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0,
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"The seconds to sleep between net and operator runs.");
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C10_DEFINE_bool(
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text_output,
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false,
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"Whether to write out output in text format for regression purpose.");
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C10_DEFINE_int(warmup, 0, "The number of iterations to warm up.");
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C10_DEFINE_bool(
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wipe_cache,
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false,
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"Whether to evict the cache before running network.");
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int main(int argc, char** argv) {
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caffe2::GlobalInit(&argc, &argv);
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benchmark(
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