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73 lines
2.7 KiB
73 lines
2.7 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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 "FunctionTest.h"
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namespace paddle {
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TEST(ScaleSubRegion, real) {
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for (size_t numSamples : {5, 32}) {
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for (size_t channels : {5, 32}) {
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for (size_t imgSizeH : {5, 33}) {
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for (size_t imgSizeW : {5, 32}) {
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for (real value : {-0.5, 0.0, 0.5}) {
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for (bool firstHalf : {false, true}) {
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VLOG(3) << " numSamples=" << numSamples
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<< " channels=" << channels << " imgSizeH=" << imgSizeH
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<< " imgSizeW=" << imgSizeW;
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for (bool testGrad : {false, true}) {
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CpuGpuFuncCompare compare(
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testGrad ? "ScaleSubRegionGrad" : "ScaleSubRegion",
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FuncConfig().set<real>("value", value));
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TensorShape shape{numSamples, channels, imgSizeH, imgSizeW};
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TensorShape indicesShape{numSamples, 6};
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compare.addInputs(BufferArg(VALUE_TYPE_FLOAT, shape));
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compare.addInputs(BufferArg(VALUE_TYPE_FLOAT, indicesShape));
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compare.registerInitCallback([=](BufferArg& arg, size_t index) {
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if (index == 1) {
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real* data = (real*)arg.data();
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for (size_t i = 0; i < numSamples; ++i) {
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size_t offset = i * 6;
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data[offset] = firstHalf ? 1 : channels / 2;
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data[offset + 1] = firstHalf ? channels / 2 : channels;
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data[offset + 2] = firstHalf ? 1 : imgSizeH / 2;
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data[offset + 3] = firstHalf ? imgSizeH / 2 : imgSizeH;
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data[offset + 4] = firstHalf ? 1 : imgSizeW / 2;
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data[offset + 5] = firstHalf ? imgSizeW / 2 : imgSizeW;
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}
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}
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});
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compare.addOutputs(
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BufferArg(
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VALUE_TYPE_FLOAT, shape, testGrad ? ADD_TO : ASSIGN_TO),
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testGrad ? ADD_TO : ASSIGN_TO);
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compare.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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} // namespace paddle
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