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/*
* 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.
*/
/*!
* \file dropout_perf.cc
* \brief Perf/profile run of DropoutOp
* \author Chris Olivier
*/
#include <gtest/gtest.h>
#include <mxnet/tensor_blob.h>
#include "../include/test_op_runner.h"
#include "../include/test_core_op.h"
#include "../../src/operator/nn/dropout-inl.h"
using namespace mxnet;
typedef std::vector<std::pair<std::string, std::string> > kwargs_t;
const kwargs_t basic_dropout_args = {};
/*!
* \brief Generic bidirectional sanity test
*/
TEST(DROPOUT_PERF, ExecuteBidirectional) {
mxnet::TShape shape({5, 5});
kwargs_t kwargs = basic_dropout_args;
kwargs.push_back({"mode", "always"});
test::op::CoreOperatorRunner<float> runner;
kwargs = test::op::CoreOpExecutor<float>::ArgsWithOpName(kwargs, "Dropout", "_backward_Dropout");
runner.set_verbose(true);
runner.RunBidirectional(false, {shape}, kwargs, 1);
}
/*!
* \brief DropoutOp timing test for CPU
*/
TEST(DROPOUT_PERF, TimingCPU) {
kwargs_t kwargs = basic_dropout_args;
// Which math function is arbitrary since it will have roughly constant timing among approaches
kwargs.push_back({"mode", "always"});
mxnet::TShape shape({10, 10, 10, 10});
test::op::CoreOperatorRunner<float> runner;
kwargs = test::op::CoreOpExecutor<float>::ArgsWithOpName(kwargs, "Dropout", "_backward_Dropout");
runner.RunBidirectional(false, {shape}, kwargs, 1);
std::vector<mxnet::TShape> shapes;
if (test::performance_run) {
shapes = {{1, 1, 28, 28}, {1, 3, 28, 28}, {50, 1, 18, 32}, {50, 3, 18, 32}, {20, 3, 128, 128}};
} else {
shapes = {
{1, 1, 28, 28},
{50, 3, 18, 32},
};
}
for (const mxnet::TShape& shape : shapes) {
kwargs =
test::op::CoreOpExecutor<float>::ArgsWithOpName(kwargs, "Dropout", "_backward_Dropout");
runner.TimingTest("Dropout Operator CPU", false, false, kwargs, 2, 10, {shape}, false);
}
}
#if MXNET_USE_CUDA == 1
/*!
* \brief DropoutOp timing test for GPU
*/
TEST(DROPOUT_PERF, TimingGPU) {
kwargs_t kwargs = basic_dropout_args;
// Which math function is arbitrary since it will have roughly constant timing among approaches
kwargs.push_back({"mode", "always"});
mxnet::TShape shape({10, 10, 10, 10});
test::op::CoreOperatorRunner<float> runner;
kwargs = test::op::CoreOpExecutor<float>::ArgsWithOpName(kwargs, "Dropout", "_backward_Dropout");
runner.RunBidirectional(false, {shape}, kwargs, 1);
std::vector<mxnet::TShape> shapes = {
{1, 1, 28, 28}, {1, 3, 28, 28}, {50, 1, 18, 32}, {50, 3, 18, 32}, {20, 3, 128, 128}};
for (const mxnet::TShape& shape : shapes) {
kwargs =
test::op::CoreOpExecutor<float>::ArgsWithOpName(kwargs, "Dropout", "_backward_Dropout");
runner.TimingTest("Dropout Operator GPU", true, false, kwargs, 2, 10, {shape}, false);
}
}
#endif // MXNET_USE_CUDA == 1