// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "paddle/fluid/operators/shard_index_op.h" #include "paddle/fluid/platform/cuda_primitives.h" #include "paddle/fluid/platform/gpu_info.h" namespace paddle { namespace operators { using platform::PADDLE_CUDA_NUM_THREADS; template __global__ void ShardIndexInner(const T* in_data, T* out_data, const int64_t numel, const int index_num, const int nshards, const int shard_id, const int ignore_value) { int shard_size = index_num / nshards; int idx = blockIdx.x * blockDim.x + threadIdx.x; if (idx < numel) { assert(in_data[idx] >= 0 && in_data[idx] < index_num); if (in_data[idx] / shard_size == shard_id) { out_data[idx] = in_data[idx] % shard_size; } else { out_data[idx] = ignore_value; } } } using LoDTensor = framework::LoDTensor; template class ShardIndexCUDAKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* in = context.Input("X"); auto* out = context.Output("Out"); int index_num = context.Attr("index_num"); int nshards = context.Attr("nshards"); int shard_id = context.Attr("shard_id"); int ignore_value = context.Attr("ignore_value"); PADDLE_ENFORCE_GT(index_num, 0); PADDLE_ENFORCE_GT(nshards, 0); PADDLE_ENFORCE(shard_id >= 0 && shard_id < nshards, "shard_id(%d) is not in range [0, %d)", shard_id, nshards); out->Resize(in->dims()); out->set_lod(in->lod()); auto* in_data = in->data(); auto* out_data = out->mutable_data(context.GetPlace()); int64_t numel = in->numel(); auto stream = context.template device_context().stream(); ShardIndexInner<<<(numel + PADDLE_CUDA_NUM_THREADS - 1) / PADDLE_CUDA_NUM_THREADS, PADDLE_CUDA_NUM_THREADS, 0, stream>>>( in_data, out_data, numel, index_num, nshards, shard_id, ignore_value); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OP_CUDA_KERNEL(shard_index, ops::ShardIndexCUDAKernel, ops::ShardIndexCUDAKernel);