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78 lines
2.9 KiB
78 lines
2.9 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/shard_index_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 T>
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__global__ void ShardIndexInner(const T* in_data, T* out_data,
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const int64_t numel, const int index_num,
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const int nshards, const int shard_id,
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const int ignore_value) {
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int shard_size = (index_num + nshards - 1) / nshards;
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int idx = blockIdx.x * blockDim.x + threadIdx.x;
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if (idx < numel) {
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assert(in_data[idx] >= 0 && in_data[idx] < index_num);
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if (in_data[idx] / shard_size == shard_id) {
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out_data[idx] = in_data[idx] % shard_size;
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} else {
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out_data[idx] = ignore_value;
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}
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}
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}
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using LoDTensor = framework::LoDTensor;
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template <typename T>
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class ShardIndexCUDAKernel : 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 index_num = context.Attr<int>("index_num");
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int nshards = context.Attr<int>("nshards");
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int shard_id = context.Attr<int>("shard_id");
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int ignore_value = context.Attr<int>("ignore_value");
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PADDLE_ENFORCE_GT(index_num, 0);
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PADDLE_ENFORCE_GT(nshards, 0);
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PADDLE_ENFORCE(shard_id >= 0 && shard_id < nshards,
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"shard_id(%d) is not in range [0, %d)", shard_id, nshards);
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out->Resize(in->dims());
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out->set_lod(in->lod());
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auto* in_data = in->data<T>();
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auto* out_data = out->mutable_data<T>(context.GetPlace());
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int64_t numel = in->numel();
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auto stream =
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context.template device_context<platform::CUDADeviceContext>().stream();
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ShardIndexInner<<<(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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in_data, out_data, numel, index_num, nshards, shard_id, ignore_value);
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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(shard_index, ops::ShardIndexCUDAKernel<int>,
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ops::ShardIndexCUDAKernel<int64_t>);
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