recv_v2_op.cc 4.1 KB
Newer Older
L
lilong12 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
/* Copyright (c) 2020 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/collective/recv_v2_op.h"
#include <string>

namespace paddle {
namespace operators {

class RecvOpV2 : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

  void InferShape(framework::InferShapeContext* ctx) const override {
    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Recv_V2");
    int peer = ctx->Attrs().Get<int>("peer");
    int ring_id = ctx->Attrs().Get<int>("ring_id");
    PADDLE_ENFORCE_GE(
        peer, 0,
        platform::errors::InvalidArgument(
            "The peer (%d) for recv_v2 op must be non-negative.", peer));
    PADDLE_ENFORCE_GE(
        ring_id, 0,
        platform::errors::InvalidArgument(
            "The ring_id (%d) for recv_v2 op must be non-negative.", ring_id));
37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54

    if (ctx->GetOutputsVarType("Out").front() ==
        framework::proto::VarType::LOD_TENSOR) {
      auto out_shape = ctx->Attrs().Get<std::vector<int>>("out_shape");
      PADDLE_ENFORCE_GE(
          out_shape.size(), 1,
          platform::errors::InvalidArgument(
              "The size of the output shape must be greater than 0 "
              "but the value given is %d.",
              out_shape.size()));
      for (size_t i = 0; i < out_shape.size(); ++i) {
        PADDLE_ENFORCE_GE(out_shape[i], 1,
                          platform::errors::InvalidArgument(
                              "The shape attribute for recv_v2 must be set "
                              "explicitly, but the %dth element is %d which "
                              "is less than 1.",
                              i, out_shape[i]));
      }
55
      ctx->SetOutputDim("Out", phi::make_ddim(out_shape));
56
    }
L
lilong12 已提交
57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77
  }

 protected:
  framework::OpKernelType GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    int dtype = ctx.Attr<int>("dtype");
    framework::proto::VarType::Type type =
        framework::proto::VarType::Type(dtype);
    return framework::OpKernelType(type, ctx.GetPlace());
  }
};

class RecvOpV2Maker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() {
    AddOutput("Out", "(Tensor) tensor to receive.");
    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
        .SetDefault(0);
    AddAttr<int>("peer", "(int default 0) rank id for sender.").SetDefault(0);
    AddAttr<int>("dtype", "(int default 5('float32')) data type of tensor.")
        .SetDefault(5);
78 79 80 81 82 83
#if defined(PADDLE_WITH_ASCEND_CL)
    AddAttr<std::string>("tag", "(string default tag) tag for broadcasting.")
        .SetDefault("tag");
    AddAttr<int>("srTag", "(string default tag) tag for broadcasting.")
        .SetDefault(0);
#endif
L
lilong12 已提交
84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110
    AddAttr<std::vector<int>>("out_shape", "shape of the output tensor.")
        .SetDefault(std::vector<int>());
    AddAttr<bool>(
        "use_calc_stream",
        "(bool default false) eject CUDA operations to calculation stream.")
        .SetDefault(false);
    AddComment(R"DOC(
Recv Operator

Reference: https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/p2p.html#sendrecv
)DOC");
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
namespace plat = paddle::platform;

REGISTER_OP_WITHOUT_GRADIENT(recv_v2, ops::RecvOpV2, ops::RecvOpV2Maker);

REGISTER_OP_CPU_KERNEL(recv_v2, ops::RecvOpV2CPUKernel<float>,
                       ops::RecvOpV2CPUKernel<double>,
                       ops::RecvOpV2CPUKernel<int>,
                       ops::RecvOpV2CPUKernel<int64_t>,
                       ops::RecvOpV2CPUKernel<plat::float16>);