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116 lines
4.4 KiB
116 lines
4.4 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#include "paddle/fluid/operators/where_op.h"
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#include "paddle/fluid/platform/gpu_launch_config.h"
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namespace platform = paddle::platform;
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namespace paddle {
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namespace operators {
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template <typename T>
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__global__ void WhereCUDAKernel(const int N, const bool* cond, const T* x,
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const T* y, T* out) {
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int idx = blockDim.x * blockIdx.x + threadIdx.x;
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for (; idx < N; idx += blockDim.x * gridDim.x) {
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out[idx] = cond[idx] ? x[idx] : y[idx];
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}
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}
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template <typename T>
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__global__ void WhereGradCUDAKernel(const int N, const T* dout,
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const bool* cond, T* dx, T* dy) {
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int idx = blockDim.x * blockIdx.x + threadIdx.x;
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for (; idx < N; idx += blockDim.x * gridDim.x) {
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if (dx != nullptr) {
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dx[idx] = cond[idx] ? dout[idx] : 0.;
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}
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if (dy != nullptr) {
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dy[idx] = cond[idx] ? 0. : dout[idx];
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}
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}
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}
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template <typename T>
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class WhereKernel<platform::CUDADeviceContext, T>
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: public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* condition = context.Input<framework::Tensor>("Condition");
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auto* X = context.Input<framework::Tensor>("X");
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auto* Y = context.Input<framework::Tensor>("Y");
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auto* out = context.Output<framework::Tensor>("Out");
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auto numel = condition->numel();
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// TODO(GaaoWei8): Input of where can be broadcast
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const bool* cond_data = condition->data<bool>();
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const T* x_data = X->data<T>();
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const T* y_data = Y->data<T>();
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T* out_data = out->mutable_data<T>(context.GetPlace());
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auto stream = context.cuda_device_context().stream();
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auto& dev_ctx =
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context.template device_context<platform::CUDADeviceContext>();
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auto config = GetGpuLaunchConfig1D(dev_ctx, numel);
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WhereCUDAKernel<
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T><<<config.block_per_grid.x, config.thread_per_block.x, 0, stream>>>(
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numel, cond_data, x_data, y_data, out_data);
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}
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};
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template <typename T>
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class WhereGradKernel<platform::CUDADeviceContext, T>
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: public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* condition = context.Input<framework::Tensor>("Condition");
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const bool* cond_data = condition->data<bool>();
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auto numel = condition->numel();
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auto* dout_t =
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context.Input<framework::Tensor>(framework::GradVarName("Out"));
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auto* dx_t = context.Output<framework::Tensor>(framework::GradVarName("X"));
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auto* dy_t = context.Output<framework::Tensor>(framework::GradVarName("Y"));
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auto* dout = dout_t->data<T>();
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T* dx =
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(dx_t != nullptr) ? dx_t->mutable_data<T>(context.GetPlace()) : nullptr;
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T* dy =
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(dy_t != nullptr) ? dy_t->mutable_data<T>(context.GetPlace()) : nullptr;
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auto stream = context.cuda_device_context().stream();
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auto& dev_ctx =
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context.template device_context<platform::CUDADeviceContext>();
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auto config = GetGpuLaunchConfig1D(dev_ctx, condition->numel());
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WhereGradCUDAKernel<
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T><<<config.block_per_grid.x, config.thread_per_block.x, 0, stream>>>(
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numel, dout, cond_data, dx, dy);
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}
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};
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} // namespace operators
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} // namespace paddle
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REGISTER_OP_CUDA_KERNEL(
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where, paddle::operators::WhereKernel<platform::CUDADeviceContext, float>,
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paddle::operators::WhereKernel<platform::CUDADeviceContext, double>,
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paddle::operators::WhereKernel<platform::CUDADeviceContext, int>,
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paddle::operators::WhereKernel<platform::CUDADeviceContext, int64_t>);
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REGISTER_OP_CUDA_KERNEL(
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where_grad,
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paddle::operators::WhereGradKernel<platform::CUDADeviceContext, float>,
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paddle::operators::WhereGradKernel<platform::CUDADeviceContext, double>,
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paddle::operators::WhereGradKernel<platform::CUDADeviceContext, int>,
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paddle::operators::WhereGradKernel<platform::CUDADeviceContext, int64_t>);
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