test_ActivationGrad.cpp 2.8 KB
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed 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. */

#include <gtest/gtest.h>
#include <string>
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Yu Yang 已提交
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#include <vector>
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#include "ModelConfig.pb.h"
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Xin Pan 已提交
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#include "paddle/legacy/gserver/layers/DataLayer.h"
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#include "LayerGradUtil.h"
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#include "paddle/testing/TestUtil.h"
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using namespace paddle;  // NOLINT
using namespace std;     // NOLINT

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DECLARE_bool(use_gpu);
DECLARE_bool(thread_local_rand_use_global_seed);
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void testActivation(const string& act) {
  LOG(INFO) << "test activation: " << act;
  size_t size = 10;
  TestConfig config;
  config.biasSize = 0;
  config.layerConfig.set_type("addto");
  config.layerConfig.set_size(size);
  config.layerConfig.set_active_type(act);
  config.inputDefs.push_back({INPUT_DATA, "layer_0", size, 0});
  config.layerConfig.add_inputs();
  for (auto useGpu : {false, true}) {
    testLayerGrad(config,
                  act + "_activation",
                  100,
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                  /* trans= */ false,
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                  useGpu,
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                  /* useWeight */ true);
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  }
}

TEST(Activation, activation) {
  auto types = ActivationFunction::getAllRegisteredTypes();
  std::set<string> excluded{"sequence_softmax"};
  for (auto type : types) {
    if (excluded.count(type)) continue;
    testActivation(type);
  }
}

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void testSequenceSoftmaxAct(bool hasSubseq) {
  LOG(INFO) << "test activation: sequence softmax";

  const size_t size = 1;
  TestConfig config;
  config.biasSize = 0;
  config.layerConfig.set_type("addto");
  config.layerConfig.set_size(size);
  config.layerConfig.set_active_type("sequence_softmax");
  config.inputDefs.push_back(
      {hasSubseq ? INPUT_HASSUB_SEQUENCE_DATA : INPUT_SEQUENCE_DATA,
       "layer_0",
       1,
       0});
  config.layerConfig.add_inputs();

  for (auto useGpu : {false, true}) {
    testLayerGrad(config,
                  "sequence_softmax",
                  100,
                  /* trans= */ false,
                  useGpu,
                  /* useWeight */ true);
  }
}

TEST(SequenceSoftmaxActivation, activation) {
  for (auto hasSubseq : {false, true}) {
    LOG(INFO) << "hasSubseq = " << hasSubseq;
    testSequenceSoftmaxAct(hasSubseq);
  }
}

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int main(int argc, char** argv) {
  testing::InitGoogleTest(&argc, argv);
  initMain(argc, argv);
  FLAGS_thread_local_rand_use_global_seed = true;
  srand(1);
  return RUN_ALL_TESTS();
}