diff --git a/paddle/function/CMakeLists.txt b/paddle/function/CMakeLists.txt index 790e342fb9bb9caa59f6d05c167668d43f4b1561..7dfb6f61c50959f7269725a00dbc4f9c27474bdf 100644 --- a/paddle/function/CMakeLists.txt +++ b/paddle/function/CMakeLists.txt @@ -41,7 +41,6 @@ if(WITH_GPU) add_simple_unittest(DepthwiseConvOpTest) endif() -add_simple_unittest(ConvOpTest) add_simple_unittest(Im2ColTest) add_simple_unittest(GemmConvOpTest) endif() diff --git a/paddle/function/ConvOpTest.cpp b/paddle/function/ConvOpTest.cpp deleted file mode 100644 index 7f32c734791853a8cd0287a80a7955dbd1bd7571..0000000000000000000000000000000000000000 --- a/paddle/function/ConvOpTest.cpp +++ /dev/null @@ -1,306 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - -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 -#include -#include "Function.h" -#include "FunctionTest.h" - -namespace paddle { - -enum TestType { - kForwardTest = 0, - kBackwardInputTest = 1, - kBackwardFilterTest = 2, -}; - -template -class ConvolutionTest { -public: - ConvolutionTest(const std::string& conv1, - const std::string& conv2, - TestType type, - bool useGroups = true, - std::string algo = "auto") { - for (size_t batchSize : {1, 32}) { - for (size_t inputSize : {7, 14, 54}) { - for (size_t filterSize : {1, 3, 5}) { - for (size_t inputChannels : {3, 64}) { - for (size_t outputChannels : {3, 64}) { - if (inputChannels > outputChannels) break; - size_t groups; - if (!useGroups) { - groups = 1; - } else { - if (outputChannels % inputChannels != 0) continue; - groups = inputChannels; - } - - for (size_t stride : {1, 2}) { - for (size_t padding : {0, 1}) { - if (padding >= filterSize) break; - size_t outputSize = - (inputSize - filterSize + 2 * padding + stride) / stride; - VLOG(3) << " batchSize=" << batchSize - << " inputChannels=" << inputChannels - << " inputHeight=" << inputSize - << " inputWidth=" << inputSize - << " outputChannels=" << outputChannels - << " filterHeight=" << filterSize - << " filterWidth=" << filterSize - << " outputHeight=" << outputSize - << " outputWidth=" << outputSize - << " stride=" << stride << " padding=" << padding; - - std::vector paddings = {padding, padding}; - std::vector strides = {stride, stride}; - Compare2Function test( - conv1, - conv2, - FuncConfig() - .set("paddings", paddings) - .set("strides", strides) - .set("groups", groups) - .set("algo", algo)); - - TensorShape input{ - batchSize, inputChannels, inputSize, inputSize}; - - TensorShape filter; - if (groups > 1) - filter = TensorShape({groups, - outputChannels / groups, - inputChannels / groups, - filterSize, - filterSize}); - else - filter = TensorShape({outputChannels, - inputChannels, - filterSize, - filterSize}); - TensorShape output{ - batchSize, outputChannels, outputSize, outputSize}; - - if (type == kForwardTest) { - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, input)); - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, filter)); - test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, output)); - test.run(); - } else if (type == kBackwardInputTest) { - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, output)); - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, filter)); - test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, input), ADD_TO); - test.run(); - } else if (type == kBackwardFilterTest) { - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, output)); - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, input)); - test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, filter), - ADD_TO); - test.run(); - } - } - } - } - } - } - } - } - } -}; - -// Mainly used to test cases where the height and width (input, filter) -// are not equal. -template -class ConvolutionTest2 { -public: - ConvolutionTest2(const std::string& conv1, - const std::string& conv2, - TestType type, - bool useGroups = true, - std::string algo = "auto") { - for (size_t batchSize : {16}) { - for (size_t inputHeight : {7, 31}) { - for (size_t inputWidth : {10, 54}) { - for (size_t filterHeight : {1, 5}) { - for (size_t filterWidth : {3, 7}) { - for (size_t inputChannels : {7}) { - for (size_t outputChannels : {7}) { - size_t groups; - if (!useGroups) { - groups = 1; - } else { - if (outputChannels % inputChannels != 0) continue; - groups = inputChannels; - } - - size_t stride = 1; - size_t padding = 0; - size_t outputHeight = - (inputHeight - filterHeight + 2 * padding + stride) / - stride; - size_t outputWidth = - (inputWidth - filterWidth + 2 * padding + stride) / - stride; - VLOG(3) << " batchSize=" << batchSize - << " inputChannels=" << inputChannels - << " inputHeight=" << inputHeight - << " inputWidth=" << inputWidth - << " outputChannels=" << outputChannels - << " filterHeight=" << filterHeight - << " filterWidth=" << filterWidth - << " outputHeight=" << outputHeight - << " outputWidth=" << outputWidth - << " stride=" << stride << " padding=" << padding; - - std::vector paddings = {padding, padding}; - std::vector strides = {stride, stride}; - Compare2Function test( - conv1, - conv2, - FuncConfig() - .set("paddings", paddings) - .set("strides", strides) - .set("groups", groups) - .set("algo", algo)); - - TensorShape input{ - batchSize, inputChannels, inputHeight, inputWidth}; - - TensorShape filter; - if (groups > 1) - filter = TensorShape({groups, - outputChannels / groups, - inputChannels / groups, - filterHeight, - filterWidth}); - else - filter = TensorShape({outputChannels, - inputChannels, - filterHeight, - filterWidth}); - TensorShape output{ - batchSize, outputChannels, outputHeight, outputWidth}; - - if (type == kForwardTest) { - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, input)); - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, filter)); - test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, output)); - test.run(); - } else if (type == kBackwardInputTest) { - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, output)); - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, filter)); - test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, input), ADD_TO); - test.run(); - } else if (type == kBackwardFilterTest) { - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, output)); - test.addInputs(BufferArg(VALUE_TYPE_FLOAT, input)); - test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, filter), - ADD_TO); - test.run(); - } - } - } - } - } - } - } - } - } -}; - -// ======Start Convolution TEST====== - -TEST(Forward, GEMM) { - ConvolutionTest test( - "NaiveConv-CPU", "GemmConv-CPU", kForwardTest, false); - ConvolutionTest2 test2( - "NaiveConv-CPU", "GemmConv-CPU", kForwardTest, false); -} - -#ifndef PADDLE_ONLY_CPU -TEST(Forward, GEMM2) { - ConvolutionTest test( - "GemmConv-CPU", "GemmConv-GPU", kForwardTest, false); - ConvolutionTest2 test2( - "GemmConv-CPU", "GemmConv-GPU", kForwardTest, false); -} - -TEST(BackwardInput, GEMM) { - ConvolutionTest test( - "GemmConvGradInput-CPU", - "GemmConvGradInput-GPU", - kBackwardInputTest, - false); - ConvolutionTest2 test2( - "GemmConvGradInput-CPU", - "GemmConvGradInput-GPU", - kBackwardInputTest, - false); -} - -TEST(BackwardFilter, GEMM) { - ConvolutionTest test( - "GemmConvGradFilter-CPU", - "GemmConvGradFilter-GPU", - kBackwardFilterTest, - false); - ConvolutionTest2 test2( - "GemmConvGradFilter-CPU", - "GemmConvGradFilter-GPU", - kBackwardFilterTest, - false); -} -#endif -// ======End Convolution TEST====== - -// ======Start DepthwiseConvolution TEST====== - -// TODO(zhaolong) The depthwise convolution cpu test will be added when the cpu -// version of depthwiseConv is implemented. - -#ifndef PADDLE_ONLY_CPU - -TEST(DepthwiseConvForward, GEMM2) { - ConvolutionTest test( - "GemmConv-CPU", "DepthwiseConv-GPU", kForwardTest); - ConvolutionTest2 test2( - "GemmConv-CPU", "DepthwiseConv-GPU", kForwardTest); -} - -TEST(DepthwiseConvBackwardInput, GEMM) { - ConvolutionTest test( - "GemmConvGradInput-CPU", - "DepthwiseConvGradInput-GPU", - kBackwardInputTest); - ConvolutionTest2 test2( - "GemmConvGradInput-CPU", - "DepthwiseConvGradInput-GPU", - kBackwardInputTest); -} - -TEST(DepthwiseConvBackwardFilter, GEMM) { - ConvolutionTest test( - "GemmConvGradFilter-CPU", - "DepthwiseConvGradFilter-GPU", - kBackwardFilterTest); - ConvolutionTest2 test2( - "GemmConvGradFilter-CPU", - "DepthwiseConvGradFilter-GPU", - kBackwardFilterTest); -} - -#endif -// ======End DepthwiseConvolution TEST====== - -} // namespace paddle