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68 lines
2.3 KiB
68 lines
2.3 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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#define EIGEN_USE_GPU
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#include "paddle/operators/clip_op.h"
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#define CUDA_1D_KERNEL_LOOP(i, n) \
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for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \
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i += blockDim.x * gridDim.x)
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename T>
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__global__ void ClipGradientKernel(const int N, const T min, const T max,
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const T* Y, const T* dY, T* dX) {
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CUDA_1D_KERNEL_LOOP(i, N) { dX[i] = dY[i] * (Y[i] > min && Y[i] < max); }
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}
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template <typename T>
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class ClipGradientOpCUDAKernel : public framework::OpKernel {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto max = context.op().Attr<float>("max");
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auto min = context.op().Attr<float>("min");
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auto* d_out = context.Input<Tensor>(framework::GradVarName("Out"));
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auto* d_x = context.Output<Tensor>(framework::GradVarName("X"));
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auto* x = context.Output<Tensor>("X");
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auto dims = d_x->dims();
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size_t count = 1;
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for (int i = 0; i < dims.size(); ++i) {
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count *= dims[i];
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}
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auto d_x_data = d_x->mutable_data<T>(context.GetPlace());
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auto d_out_data = d_out->data<T>();
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auto x_data = x->data<T>();
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int N = d_x->dims()[0];
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int D = d_x->dims()[1];
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int block = 512;
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int grid = (N * D + block - 1) / block;
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ClipGradientKernel<T><<<grid, block>>>(count, min, max, x_data, d_out_data,
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d_x_data);
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}
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};
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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_GPU_KERNEL(clip,
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ops::ClipKernel<paddle::platform::GPUPlace, float>);
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REGISTER_OP_GPU_KERNEL(clip_grad, ops::ClipGradientOpCUDAKernel<float>);
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