mirror of
https://github.com/saymrwulf/pytorch.git
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112 lines
2.7 KiB
Text
112 lines
2.7 KiB
Text
/**
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* Copyright (c) 2016-present, Facebook, Inc.
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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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*/
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#include "batch_permutation_op.h"
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#include "caffe2/core/context_gpu.h"
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namespace caffe2 {
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namespace {
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template <bool forward>
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__global__ void BatchPermutationKernel(
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int N,
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int C,
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int H,
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int W,
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const float* src,
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const int* indices,
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float* dst) {
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CUDA_1D_KERNEL_LOOP(index, N * C * H * W) {
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int w = index % W;
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int h = (index / W) % H;
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int c = (index / W / H) % C;
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int n = (index / W / H / C);
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int idx = indices[n];
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if (forward) {
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dst[n * C * H * W + c * H * W + h * W + w] =
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src[idx * C * H * W + c * H * W + h * W + w];
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} else {
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dst[idx * C * H * W + c * H * W + h * W + w] =
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src[n * C * H * W + c * H * W + h * W + w];
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}
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}
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}
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}
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template <>
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bool BatchPermutationOp<float, CUDAContext>::RunOnDevice() {
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auto& X = Input(0);
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auto& indices = Input(1);
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auto* Y = Output(0);
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CAFFE_ENFORCE(indices.ndim() == 1, "indices must be 1-d");
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CAFFE_ENFORCE(
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X.dim32(0) == indices.dim32(0),
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"X.dim32(0) must be equal to indices.dim32(0)",
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"(",
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X.dim32(0),
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" vs. ",
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indices.dim32(0),
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")");
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Y->ResizeLike(X);
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BatchPermutationKernel<true><<<
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CAFFE_GET_BLOCKS(X.size()),
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CAFFE_CUDA_NUM_THREADS,
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0,
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context_.cuda_stream()>>>(
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X.dim32(0),
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X.dim32(1),
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X.dim32(2),
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X.dim32(3),
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X.data<float>(),
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indices.data<int>(),
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Y->mutable_data<float>());
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return true;
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}
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template <>
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bool BatchPermutationGradientOp<float, CUDAContext>::RunOnDevice() {
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auto& indices = Input(0);
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auto& dY = Input(1);
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auto* dX = Output(0);
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dX->ResizeLike(dY);
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BatchPermutationKernel<false><<<
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CAFFE_GET_BLOCKS(dY.size()),
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CAFFE_CUDA_NUM_THREADS,
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0,
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context_.cuda_stream()>>>(
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dY.dim32(0),
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dY.dim32(1),
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dY.dim32(2),
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dY.dim32(3),
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dY.data<float>(),
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indices.data<int>(),
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dX->mutable_data<float>());
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return true;
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}
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REGISTER_CUDA_OPERATOR(
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BatchPermutation,
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BatchPermutationOp<float, CUDAContext>);
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REGISTER_CUDA_OPERATOR(
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BatchPermutationGradient,
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BatchPermutationGradientOp<float, CUDAContext>);
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} // namespace caffe2
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