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109 lines
4.1 KiB
109 lines
4.1 KiB
/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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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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#include "paddle/fluid/operators/collective/c_scatter_op.h"
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#if defined(PADDLE_WITH_NCCL)
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#include "paddle/fluid/platform/collective_helper.h"
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#include "paddle/fluid/platform/nccl_helper.h"
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#endif
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namespace paddle {
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namespace operators {
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template <typename T>
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class CScatterOpCUDAKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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#if defined(PADDLE_WITH_NCCL)
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auto x = ctx.Input<framework::LoDTensor>("X");
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auto out = ctx.Output<framework::LoDTensor>("Out");
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int numel = x->numel();
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ncclDataType_t dtype = platform::ToNCCLDataType(x->type());
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int nranks = ctx.Attr<int>("nranks");
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int root_id = ctx.Attr<int>("root");
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int ring_id = ctx.Attr<int>("ring_id");
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auto place = ctx.GetPlace();
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auto comm = platform::NCCLCommContext::Instance().Get(ring_id, place);
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PADDLE_ENFORCE_EQ(nranks, comm->nranks(),
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platform::errors::InvalidArgument(
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"The number of ranks (%d) you set of must "
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"be equal to comm->nranks (%d).",
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nranks, comm->nranks()));
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PADDLE_ENFORCE_GE(
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root_id, 0,
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platform::errors::InvalidArgument(
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"The root_id (%d) for c_scatter_op must be non-negative.",
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root_id));
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PADDLE_ENFORCE_GE(
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ring_id, 0,
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platform::errors::InvalidArgument(
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"The ring_id (%d) for c_scatter_op must be non-negative.",
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ring_id));
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cudaStream_t stream = nullptr;
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if (ctx.Attr<bool>("use_calc_stream")) {
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auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
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stream = static_cast<platform::CUDADeviceContext*>(dev_ctx)->stream();
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} else {
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stream = comm->stream();
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}
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framework::DDim x_dims = x->dims();
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framework::DDim out_dims(x_dims);
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framework::Tensor temp;
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auto out_ptr = temp.mutable_data<T>(out_dims, place);
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if (root_id == comm->rank()) {
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PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
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reinterpret_cast<void*>(const_cast<T*>(x->data<T>())), numel, dtype,
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root_id, comm->comm(), stream));
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framework::TensorCopy(*static_cast<const framework::Tensor*>(x), place,
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*platform::DeviceContextPool::Instance().Get(place),
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static_cast<framework::Tensor*>(&temp));
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} else {
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PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
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out_ptr, numel, dtype, root_id, comm->comm(), stream));
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}
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out_dims[0] = out_dims[0] / nranks;
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auto start_index = out_dims[0] * comm->rank();
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auto end_index = start_index + out_dims[0];
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temp = temp.Slice(start_index, end_index);
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temp.Resize(out_dims);
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out->mutable_data<T>(out_dims, place);
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framework::TensorCopySync(*static_cast<const framework::Tensor*>(&temp),
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place, static_cast<framework::Tensor*>(out));
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out->Resize(out_dims);
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#else
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PADDLE_ENFORCE_EQ(
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true, false,
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platform::errors::Unavailable("PaddlePaddle should compile with GPU."));
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#endif
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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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namespace plat = paddle::platform;
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REGISTER_OP_CUDA_KERNEL(c_scatter, ops::CScatterOpCUDAKernel<float>,
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ops::CScatterOpCUDAKernel<double>,
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ops::CScatterOpCUDAKernel<int>,
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ops::CScatterOpCUDAKernel<int64_t>,
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ops::CScatterOpCUDAKernel<plat::float16>);
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