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117 lines
4.1 KiB
117 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 "ScaleSubRegionOp.h"
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#include "hl_base.h"
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namespace paddle {
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__global__ void KeScaleSubRegion(real* outputs,
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const real* inputs,
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const real* indices,
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real value,
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int channel,
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int height,
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int width,
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int nthreads) {
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const int idx = threadIdx.x + blockIdx.x * blockDim.x;
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if (idx < nthreads) {
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const int w = idx % width;
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const int h = (idx / width) % height;
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const int c = (idx / width / height) % channel;
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const int n = idx / width / height / channel;
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const int offset = n * 6;
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if (c >= (indices[offset] - 1) && c <= (indices[offset + 1] - 1) &&
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h >= (indices[offset + 2] - 1) && h <= (indices[offset + 3] - 1) &&
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w >= (indices[offset + 4] - 1) && w <= (indices[offset + 5] - 1)) {
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outputs[idx] = inputs[idx] * value;
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} else {
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outputs[idx] = inputs[idx];
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}
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}
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}
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template <>
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void ScaleSubRegion<DEVICE_TYPE_GPU>(real* outputs,
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const real* inputs,
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const real* indices,
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const TensorShape shape,
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const FuncConfig& conf) {
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real value = conf.get<real>("value");
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int number = shape[0];
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int channel = shape[1];
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int height = shape[2];
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int width = shape[3];
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size_t nth = number * channel * height * width;
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int blockSize = 1024;
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int gridSize = (nth + blockSize - 1) / blockSize;
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KeScaleSubRegion<<<gridSize, blockSize, 0, STREAM_DEFAULT>>>(
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outputs, inputs, indices, value, channel, height, width, nth);
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CHECK_SYNC("ScaleSubRegion");
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}
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__global__ void KeScaleSubRegionDiff(const real* inGrad,
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real* outGrad,
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const real* indices,
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real value,
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int channel,
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int height,
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int width,
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int nthreads) {
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const int idx = threadIdx.x + blockIdx.x * blockDim.x;
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if (idx < nthreads) {
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const int w = idx % width;
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const int h = (idx / width) % height;
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const int c = (idx / width / height) % channel;
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const int n = idx / width / height / channel;
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const int offset = n * 6;
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if (c >= (indices[offset] - 1) && c <= (indices[offset + 1] - 1) &&
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h >= (indices[offset + 2] - 1) && h <= (indices[offset + 3] - 1) &&
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w >= (indices[offset + 4] - 1) && w <= (indices[offset + 5] - 1)) {
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outGrad[idx] += inGrad[idx] * value;
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} else {
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outGrad[idx] += inGrad[idx];
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}
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}
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}
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template <>
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void ScaleSubRegionGrad<DEVICE_TYPE_GPU>(const real* inGrad,
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real* outGrad,
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const real* indices,
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const TensorShape shape,
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const FuncConfig& conf) {
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real value = conf.get<real>("value");
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int number = shape[0];
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int channel = shape[1];
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int height = shape[2];
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int width = shape[3];
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size_t nth = number * channel * height * width;
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int blockSize = 1024;
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int gridSize = (nth + blockSize - 1) / blockSize;
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KeScaleSubRegionDiff<<<gridSize, blockSize, 0, STREAM_DEFAULT>>>(
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inGrad, outGrad, indices, value, channel, height, width, nth);
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CHECK_SYNC("ScaleSubRegionGrad");
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}
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} // namespace paddle
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