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| * Licensed to the Apache Software Foundation (ASF) under one |
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| * distributed with this work for additional information |
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| * to you under the Apache License, Version 2.0 (the |
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| * http://www.apache.org/licenses/LICENSE-2.0 |
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| * software distributed under the License is distributed on an |
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| *************************************************************/ |
| |
| #include "../src/model/layer/dropout.h" |
| #include "gtest/gtest.h" |
| |
| using singa::Dropout; |
| using singa::Shape; |
| TEST(Dropout, Setup) { |
| Dropout drop; |
| // EXPECT_EQ("Dropout", drop.layer_type()); |
| |
| singa::LayerConf conf; |
| singa::DropoutConf* dropconf = conf.mutable_dropout_conf(); |
| dropconf->set_dropout_ratio(0.8f); |
| |
| drop.Setup(Shape{3}, conf); |
| EXPECT_EQ(0.8f, drop.dropout_ratio()); |
| } |
| |
| TEST(Dropout, Forward) { |
| const float x[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f}; |
| size_t n = sizeof(x) / sizeof(float); |
| singa::Tensor in(singa::Shape{n}); |
| in.CopyDataFromHostPtr(x, n); |
| |
| float pdrop = 0.5; |
| Dropout drop; |
| singa::LayerConf conf; |
| singa::DropoutConf* dropconf = conf.mutable_dropout_conf(); |
| dropconf->set_dropout_ratio(pdrop); |
| drop.Setup(Shape{1}, conf); |
| float scale = 1.0f / (1.0f - pdrop); |
| |
| singa::Tensor out1 = drop.Forward(singa::kTrain, in); |
| |
| const float* mptr = drop.mask().data<float>(); |
| for (size_t i = 0; i < n; i++) |
| EXPECT_FLOAT_EQ(0, mptr[i] * (mptr[i] - scale)); |
| |
| const float* outptr1 = out1.data<float>(); |
| EXPECT_EQ(n, out1.Size()); |
| // the output value should be 0 or the same as the input |
| EXPECT_EQ(0.f, outptr1[0] * (outptr1[0] - scale * x[0])); |
| EXPECT_EQ(0.f, outptr1[1] * (outptr1[1] - scale * x[1])); |
| EXPECT_EQ(0.f, outptr1[7] * (outptr1[7] - scale * x[7])); |
| |
| singa::Tensor out2 = drop.Forward(singa::kEval, in); |
| EXPECT_EQ(n, out2.Size()); |
| const float* outptr2 = out2.data<float>(); |
| // the output value should be the same as the input |
| EXPECT_EQ(x[0], outptr2[0]); |
| EXPECT_EQ(x[1], outptr2[1]); |
| EXPECT_EQ(x[7], outptr2[7]); |
| } |
| |
| TEST(Dropout, Backward) { |
| const float x[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f}; |
| size_t n = sizeof(x) / sizeof(float); |
| singa::Tensor in(singa::Shape{n}); |
| in.CopyDataFromHostPtr(x, n); |
| |
| float pdrop = 0.5; |
| float scale = 1.0f / (1.0f - pdrop); |
| |
| Dropout drop; |
| singa::LayerConf conf; |
| singa::DropoutConf* dropconf = conf.mutable_dropout_conf(); |
| dropconf->set_dropout_ratio(pdrop); |
| drop.Setup(Shape{1}, conf); |
| singa::Tensor out1 = drop.Forward(singa::kTrain, in); |
| |
| const float dy[] = {4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 1.0f, 2.0f, 3.0f}; |
| singa::Tensor grad(singa::Shape{n}); |
| grad.CopyDataFromHostPtr(dy, n); |
| |
| const float* mptr = drop.mask().data<float>(); |
| const auto ret = drop.Backward(singa::kTrain, grad); |
| const float* dx = ret.first.data<float>(); |
| EXPECT_FLOAT_EQ(dx[0], dy[0] * (mptr[0] > 0 ? 1.0f : 0.0f) * scale); |
| EXPECT_FLOAT_EQ(dx[1], dy[1] * (mptr[1] > 0) * scale); |
| EXPECT_FLOAT_EQ(dx[7], dy[7] * (mptr[7] > 0) * scale); |
| } |