wehub-resource-sync
125 lines
4.3 KiB
Plaintext
125 lines
4.3 KiB
Plaintext
// Copyright (c) 2024 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 <vector>
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#include "paddle/phi/api/include/tensor.h"
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#include "paddle/phi/backends/context_pool.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/c_concat_kernel.h"
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#include "paddle/phi/kernels/funcs/concat_and_split_functor.h"
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#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
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#include "paddle/phi/core/distributed/nccl_comm_context.h"
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#endif
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#if defined(PADDLE_WITH_FLAGCX)
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#include "paddle/phi/core/distributed/flagcx_comm_context.h"
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#endif
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namespace phi {
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template <typename T, typename Context>
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void CConcatKernel(const Context& dev_ctx,
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const DenseTensor& x_in,
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int rank,
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int nranks,
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int ring_id UNUSED,
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bool use_calc_stream UNUSED,
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bool use_model_parallel UNUSED,
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DenseTensor* out) {
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#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
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auto x = &x_in;
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PADDLE_ENFORCE_GE(rank,
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0,
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common::errors::PreconditionNotMet(
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"The value of rank (%d) for c_concat must be "
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"greater than or equal to 0.",
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rank));
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PADDLE_ENFORCE_GE(nranks,
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2,
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common::errors::PreconditionNotMet(
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"The value of nranks (%d) for c_concat must be "
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"greater than or equal to 2.",
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nranks));
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PADDLE_ENFORCE_LT(rank,
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nranks,
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common::errors::PreconditionNotMet(
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"The value of rank (%d) for c_concat must be "
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"less than that of nranks (%d).",
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rank,
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nranks));
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DenseTensor temp_out;
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DDim temp_out_dims = x->dims();
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temp_out_dims[0] *= nranks;
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temp_out.Resize(temp_out_dims);
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dev_ctx.template Alloc<T>(&temp_out);
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gpuStream_t stream = nullptr;
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#if defined(PADDLE_WITH_FLAGCX) && defined(PADDLE_KERNEL_WITH_FLAGCX)
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distributed::FlagcxCommContext* comm_ctx = nullptr;
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comm_ctx =
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static_cast<distributed::FlagcxCommContext*>(dev_ctx.GetCommContext());
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#else
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distributed::NCCLCommContext* comm_ctx = nullptr;
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comm_ctx =
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static_cast<distributed::NCCLCommContext*>(dev_ctx.GetCommContext());
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#endif
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PADDLE_ENFORCE_NE(comm_ctx,
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nullptr,
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common::errors::Unavailable(
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"NCCLCommContext is nullptr, collective op should "
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"has ring_id attr."));
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stream = dev_ctx.stream();
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#if defined(PADDLE_WITH_FLAGCX) && defined(PADDLE_KERNEL_WITH_FLAGCX)
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comm_ctx->AllGather(&temp_out, *x, reinterpret_cast<flagcxStream_t>(&stream));
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#else
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comm_ctx->AllGather(&temp_out, *x, stream);
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#endif
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std::vector<DenseTensor> inputs;
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int axis = x->dims().size() - 1;
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auto out_dims = x->dims();
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out_dims[out_dims.size() - 1] *= nranks;
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int64_t rows_per_tensor = x->dims()[0];
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int64_t offset = 0;
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for (int i = 0; i < nranks; i++) {
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DenseTensor temp = temp_out.Slice(offset, offset + rows_per_tensor);
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inputs.emplace_back(temp);
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offset += rows_per_tensor;
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}
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funcs::ConcatFunctor<GPUContext, T> functor;
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out->Resize(out_dims);
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dev_ctx.template Alloc<T>(out);
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functor(dev_ctx, inputs, axis, out);
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#else
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PADDLE_THROW(common::errors::PreconditionNotMet(
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"PaddlePaddle should compile with GPU."));
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#endif
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}
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} // namespace phi
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PD_REGISTER_KERNEL(c_concat,
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GPU,
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ALL_LAYOUT,
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phi::CConcatKernel,
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float,
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double,
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int,
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int64_t,
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phi::bfloat16,
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phi::float16) {}
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