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126 lines
4.8 KiB
126 lines
4.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "Im2Col.h"
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#include <gtest/gtest.h>
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#include "Function.h"
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#include "paddle/math/Matrix.h"
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#include "paddle/math/tests/TensorCheck.h"
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namespace paddle {
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template <DeviceType Device, class T>
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void TestIm2ColFunctor() {
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for (size_t channels : {1, 5, 32}) {
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for (size_t inputHeight : {5, 33, 100}) {
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for (size_t inputWidth : {5, 32, 96}) {
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for (size_t filterHeight : {1, 5}) {
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for (size_t filterWidth : {3, 7}) {
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for (size_t stride : {1, 2}) {
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for (size_t padding : {0, 1}) {
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if (inputHeight <= filterHeight || inputWidth <= filterWidth)
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break;
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if (padding >= filterHeight || padding >= filterWidth) break;
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size_t outputHeight =
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(inputHeight - filterHeight + 2 * padding + stride) /
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stride;
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size_t outputWidth =
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(inputWidth - filterWidth + 2 * padding + stride) / stride;
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TensorShape imShape =
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TensorShape({channels, inputHeight, inputWidth});
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TensorShape colShape1 = TensorShape({channels,
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filterHeight,
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filterWidth,
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outputHeight,
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outputWidth});
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TensorShape colShape2 = TensorShape({outputHeight,
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outputWidth,
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channels,
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filterHeight,
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filterWidth});
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size_t height = channels * filterHeight * filterWidth;
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size_t width = outputHeight * outputWidth;
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VectorPtr input1 = Vector::create(imShape.getElements(), false);
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VectorPtr input2 = Vector::create(imShape.getElements(), false);
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MatrixPtr output1 = Matrix::create(height, width, false, false);
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MatrixPtr output2 = Matrix::create(width, height, false, false);
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input1->uniform(0.001, 1);
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input2->copyFrom(*input1);
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Im2ColFunctor<kCFO, Device, T> im2Col1;
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Im2ColFunctor<kOCF, Device, T> im2Col2;
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im2Col1(input1->getData(),
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imShape,
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output1->getData(),
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colShape1,
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stride,
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stride,
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padding,
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padding);
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im2Col2(input2->getData(),
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imShape,
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output2->getData(),
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colShape2,
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stride,
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stride,
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padding,
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padding);
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// The transposition of the result of ColFormat == kCFO
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// is equal to the result of ColFormat == kOCF.
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MatrixPtr test;
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output2->transpose(test, true);
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autotest::TensorCheckErr(*output1, *test);
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Col2ImFunctor<kCFO, Device, T> col2Im1;
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Col2ImFunctor<kOCF, Device, T> col2Im2;
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col2Im1(input1->getData(),
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imShape,
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output1->getData(),
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colShape1,
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stride,
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stride,
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padding,
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padding);
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col2Im2(input2->getData(),
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imShape,
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output2->getData(),
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colShape2,
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stride,
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stride,
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padding,
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padding);
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autotest::TensorCheckErr(*input1, *input2);
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}
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}
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}
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}
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}
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}
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}
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}
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TEST(Im2ColFunctor, CPU) { TestIm2ColFunctor<DEVICE_TYPE_CPU, float>(); }
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#ifndef PADDLE_ONLY_CPU
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TEST(Im2ColFunctor, GPU) { TestIm2ColFunctor<DEVICE_TYPE_GPU, float>(); }
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#endif
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} // namespace paddle
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