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100 lines
4.1 KiB
100 lines
4.1 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 <gtest/gtest.h>
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#include "paddle/function/Function.h"
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#include "paddle/function/FunctionTest.h"
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DEFINE_string(algo,
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"auto",
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"The algorithm (auto, ft8x8, ft16x16, wt8x8, "
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"implicit-gemm, or direct) for computing convolution of NNPACK.");
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namespace paddle {
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#define IS_NNPACK_SUPPORT(algo, filterSize, stride) \
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if (algo == "direct" && filterSize != 1) continue; \
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if (algo == "direct" && batchSize != 1) continue; \
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if (algo == "wt8x8" && filterSize != 3) continue; \
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if (algo == "implicit-gemm" && batchSize != 1) continue; \
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if (algo != "auto" && algo != "implicit-gemm" && stride > 1) continue;
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class ConvolutionTest {
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public:
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ConvolutionTest(const std::string& conv1,
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const std::string& conv2,
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std::string algo = "auto") {
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for (size_t batchSize : {1, 32}) {
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for (size_t inputSize : {7, 14, 54}) {
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for (size_t filterSize : {1, 3, 5}) {
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for (size_t inputChannels : {3, 64}) {
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for (size_t outputChannels : {3, 64, 128}) {
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if (inputChannels < outputChannels) break;
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for (size_t stride : {1, 2}) {
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// if batchSize > 1 NNPACKConv only supports stride = 1
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if (batchSize > 1 && stride > 1) break;
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for (size_t padding : {0, 1}) {
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if (padding >= filterSize) break;
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size_t outputSize =
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(inputSize - filterSize + 2 * padding + stride) / stride;
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IS_NNPACK_SUPPORT(algo, filterSize, stride);
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LOG(INFO) << " batchSize=" << batchSize
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<< " inputChannels=" << inputChannels
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<< " inputHeight=" << inputSize
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<< " inputWidth=" << inputSize
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<< " outputChannels=" << outputChannels
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<< " filterHeight=" << filterSize
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<< " filterWidth=" << filterSize
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<< " outputHeight=" << outputSize
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<< " outputWidth=" << outputSize
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<< " stride=" << stride << " padding=" << padding;
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std::vector<size_t> paddings = {padding, padding};
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std::vector<size_t> strides = {stride, stride};
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Compare2Function<DEVICE_TYPE_CPU, DEVICE_TYPE_CPU> test(
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conv1,
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conv2,
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FuncConfig()
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.set("paddings", paddings)
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.set("strides", strides)
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.set("groups", (size_t)1)
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.set("algo", algo));
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TensorShape shape0{
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batchSize, inputChannels, inputSize, inputSize};
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TensorShape shape1{
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outputChannels, inputChannels, filterSize, filterSize};
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TensorShape shape2{
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batchSize, outputChannels, outputSize, outputSize};
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test.addInputs(BufferArg(VALUE_TYPE_FLOAT, shape0));
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test.addInputs(BufferArg(VALUE_TYPE_FLOAT, shape1));
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test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, shape2));
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test.run();
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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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};
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TEST(Convolution, NNPACK) {
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// NNPACK only supports stride = 1
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ConvolutionTest test("GemmConv-CPU", "NNPACKConv-CPU", FLAGS_algo);
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}
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} // namespace paddle
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