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64 lines
2.3 KiB
64 lines
2.3 KiB
/* Copyright (c) 2018 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 "paddle/fluid/operators/detection/target_assign_op.h"
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namespace paddle {
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namespace operators {
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template <typename T, typename WT>
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__global__ void NegTargetAssignKernel(const int* neg_indices, const size_t* lod,
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const int N, const int M, const int K,
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const int mismatch_value, T* out,
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WT* out_wt) {
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int bidx = blockIdx.x;
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int st = lod[bidx];
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int ed = lod[bidx + 1];
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int row_start = bidx * M;
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for (int i = st + threadIdx.x; i < ed; i += blockDim.x) {
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int id = row_start + neg_indices[i];
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for (int k = 0; k < K; ++k) {
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out[id * K + k] = T(mismatch_value);
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out_wt[id * K + k] = WT(1.);
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}
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}
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}
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template <typename T, typename WT>
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struct NegTargetAssignFunctor<platform::CUDADeviceContext, T, WT> {
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void operator()(const platform::CUDADeviceContext& ctx,
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const int* neg_indices, const size_t* lod, const int N,
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const int M, const int K, const int mismatch_value, T* out,
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WT* out_wt) {
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const int block_size = 256;
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const int grid_size = N;
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NegTargetAssignKernel<T, WT><<<grid_size, block_size, 0, ctx.stream()>>>(
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neg_indices, lod, N, M, K, mismatch_value, out, out_wt);
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}
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};
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template struct NegTargetAssignFunctor<platform::CUDADeviceContext, int, float>;
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template struct NegTargetAssignFunctor<platform::CUDADeviceContext, float,
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float>;
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(
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target_assign,
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ops::TargetAssignKernel<paddle::platform::CUDADeviceContext, int, float>,
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ops::TargetAssignKernel<paddle::platform::CUDADeviceContext, float, float>);
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