global_scatter_op.cc

/* Copyright (c) 2021 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/global_scatter_op.h"

namespace paddle {
namespace operators {

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

  void InferShape(framework::InferShapeContext* ctx) const override {
    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "GlobalScatter");
    OP_INOUT_CHECK(
        ctx->HasInput("local_count"), "Input", "local_count", "GlobalScatter");
    OP_INOUT_CHECK(ctx->HasInput("global_count"),
                   "Input",
                   "global_count",
                   "GlobalScatter");
    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "GlobalScatter");
    int ring_id = ctx->Attrs().Get<int>("ring_id");
    PADDLE_ENFORCE_GE(
        ring_id,
        0,
        platform::errors::InvalidArgument(
            "The ring_id (%d) for global scatter op must be non-negative.",
            ring_id));
    auto input_dims = ctx->GetInputDim("X");
    auto ndim_input = input_dims.size();
    // dim check
    PADDLE_ENFORCE_EQ(ndim_input,
                      2,
                      platform::errors::InvalidArgument(
                          "The input tensor's dimension must be 2. "
                          "But received input's dimension = %d.",
                          ndim_input));

    framework::DDim out_dims = phi::make_ddim({-1, -1});
    ctx->SetOutputDim("Out", out_dims);
  }

 protected:
  phi::KernelKey GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    return phi::KernelKey(OperatorWithKernel::IndicateVarDataType(ctx, "X"),
                          ctx.GetPlace());
  }
};

class GlobalScatterOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(Tensor) tensor send.");
    AddInput("local_count",
             "(Tensor) Tensor which has n_expert * world_size elements that "
             "indicates"
             "how many data needed to be sent to each expert.");
    AddInput("global_count",
             "(Tensor) Tensor which has n_expert * world_size elements that "
             "indicates"
             "how many data needed to be received from each expert.");
    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
        .SetDefault(0);
    AddAttr<bool>(
        "use_calc_stream",
        "(bool default false) eject CUDA operations to calculation stream.")
        .SetDefault(false);
    AddOutput("Out", "(Tensor) the result of global_scatter.");
    AddComment(R"DOC(
Global Scatter Operator
Scatter data in X which has been put together belong to one expert
to n_expert * world_size experts according to local_count
and receive tensors from n_expert * world_size experts according
to global_count.
)DOC");
  }
};

template <typename T>
class GlobalScatterOpGradMaker : public framework::SingleGradOpMaker<T> {
 public:
  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;

 protected:
  void Apply(GradOpPtr<T> retv) const override {
    retv->SetType("global_gather");
    retv->SetInput("X", this->OutputGrad("Out"));
    retv->SetInput("local_count", this->Input("local_count"));
    retv->SetInput("global_count", this->Input("global_count"));
    retv->SetOutput("Out", this->InputGrad("X"));
    retv->SetAttrMap(this->Attrs());
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OPERATOR(global_scatter,
                  ops::GlobalScatterOp,
                  ops::GlobalScatterOpMaker,
                  ops::GlobalScatterOpGradMaker<paddle::framework::OpDesc>,
                  ops::GlobalScatterOpGradMaker<paddle::imperative::OpBase>)

PD_REGISTER_STRUCT_KERNEL(global_scatter,
                          CPU,
                          ALL_LAYOUT,
                          ops::GlobalScatterOpCPUKernel,
                          float,
                          double,
                          int,
                          int64_t,
                          plat::float16) {}