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100 lines
3.5 KiB
100 lines
3.5 KiB
// Copyright (c) 2019 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/one_hot_v2_op.h"
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#include "paddle/fluid/platform/cuda_primitives.h"
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#include "paddle/fluid/platform/gpu_info.h"
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namespace paddle {
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namespace operators {
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using platform::PADDLE_CUDA_NUM_THREADS;
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template <typename InT, typename OutT>
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__global__ void FillOutputKernel(const InT* p_in_data, OutT* p_out_data,
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const int64_t numel, const int depth) {
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int idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < numel && p_in_data[idx] >= 0 && p_in_data[idx] < depth) {
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*(p_out_data + (idx * depth) + p_in_data[idx]) = 1.0;
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}
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}
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template <typename DeviceContext, typename InT>
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struct OneHotV2OpCUDAFunctor {
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const framework::LoDTensor* in_;
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framework::LoDTensor* out_;
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const DeviceContext& ctx_;
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int depth_;
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OneHotV2OpCUDAFunctor(const framework::LoDTensor* in,
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framework::LoDTensor* out, int depth,
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const DeviceContext& ctx)
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: in_(in), out_(out), depth_(depth), ctx_(ctx) {}
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template <typename OutT>
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void apply() const {
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auto* p_in_data = in_->data<InT>();
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auto numel = in_->numel();
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auto* p_out_data = out_->mutable_data<OutT>(ctx_.GetPlace());
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auto stream = ctx_.stream();
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math::set_constant(ctx_, out_, 0.0);
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FillOutputKernel<<<(numel + PADDLE_CUDA_NUM_THREADS - 1) /
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PADDLE_CUDA_NUM_THREADS,
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PADDLE_CUDA_NUM_THREADS, 0, stream>>>(
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p_in_data, p_out_data, numel, depth_);
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}
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};
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using LoDTensor = framework::LoDTensor;
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template <typename DeviceContext, typename T>
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class OneHotV2CUDAKernel : 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* in = context.Input<LoDTensor>("X");
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auto* out = context.Output<LoDTensor>("Out");
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int depth = -1;
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if (context.HasInput("depth_tensor")) {
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auto* depth_tensor = context.Input<framework::Tensor>("depth_tensor");
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if (platform::is_gpu_place(depth_tensor->place())) {
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framework::Tensor temp;
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TensorCopySync(*depth_tensor, platform::CPUPlace(), &temp);
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depth = *temp.data<int32_t>();
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} else {
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depth = *depth_tensor->data<int32_t>();
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}
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auto out_dims = out->dims();
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out_dims[out_dims.size() - 1] = depth;
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out->Resize(out_dims);
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} else {
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depth = context.Attr<int>("depth");
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}
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framework::VisitDataType(
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static_cast<framework::proto::VarType::Type>(
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context.Attr<int>("dtype")),
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OneHotV2OpCUDAFunctor<DeviceContext, T>(
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in, out, depth, context.template device_context<DeviceContext>()));
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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_CUDA_KERNEL(
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one_hot_v2,
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ops::OneHotV2CUDAKernel<paddle::platform::CUDADeviceContext, int>,
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ops::OneHotV2CUDAKernel<paddle::platform::CUDADeviceContext, int64_t>);
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