clean code

paddle/fluid/operators/distributed_ops/lookup_remote_table_op.cc

@@ -1,114 +0,0 @@
-/* Copyright (c) 2016 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/distributed_ops/lookup_remote_table_op.h"
-#include "paddle/fluid/framework/var_type_inference.h"
-
-namespace paddle {
-namespace operators {
-
-class LookupRemoteTableOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
-  void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("W"),
-                   "Input(W) of LookupRemoteTableOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Ids"),
-                   "Input(Ids) of LookupRemoteTableOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output(Out) of LookupRemoteTableOp should not be null.");
-
-    auto table_dims = ctx->GetInputDim("W");
-    auto ids_dims = ctx->GetInputDim("Ids");
-    int ids_rank = ids_dims.size();
-
-    PADDLE_ENFORCE_EQ(table_dims.size(), 2);
-    PADDLE_ENFORCE_EQ(ids_dims[ids_rank - 1], 1,
-                      "The last dimension of the 'Ids' tensor must be 1.");
-
-    auto output_dims =
-        framework::vectorize(framework::slice_ddim(ids_dims, 0, ids_rank - 1));
-    output_dims.push_back(table_dims[1]);
-    ctx->SetOutputDim("Out", framework::make_ddim(output_dims));
-
-    if (ctx->GetOutputsVarType("Out")[0] ==
-        framework::proto::VarType::LOD_TENSOR) {
-      ctx->ShareLoD("Ids", /*->*/ "Out");
-    }
-  }
-
- protected:
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    auto data_type = framework::GetDataTypeOfVar(ctx.InputVar("W"));
-    return framework::OpKernelType(data_type, ctx.device_context());
-  }
-};
-
-class LookupRemoteTableOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("W",
-             "(Tensor) The input represents embedding tensors, "
-             "which is a learnable parameter.");
-    AddInput("Ids",
-             "An input with type int32 or int64 "
-             "contains the ids to be looked up in W. "
-             "The last dimension size must be 1.");
-    AddOutput("Out", "The lookup results, which have the same type as W.");
-    AddAttr<std::vector<int64_t>>("height_sections",
-                                  "Height for each output SelectedRows.")
-        .SetDefault(std::vector<int64_t>({}));
-    AddAttr<int>("trainer_id", "trainer id from 0 ~ worker_num.").SetDefault(0);
-    AddAttr<std::vector<std::string>>(
-        "epmap",
-        "(string vector, default 127.0.0.1:6164)"
-        "Server endpoints in the order of input variables for mapping")
-        .SetDefault({"127.0.0.1:6164"});
-    AddAttr<int64_t>("padding_idx",
-                     "(int64, default -1) "
-                     "If the value is -1, it makes no effect to lookup. "
-                     "Otherwise the given value indicates padding the output "
-                     "with zeros whenever lookup encounters it in Ids.")
-        .SetDefault(kNoPadding);
-    // NOTE(minqiyang): grad_inplace is an temporal attribute,
-    // please do NOT set this attribute in python layer.
-    AddAttr<bool>("grad_inplace",
-                  "(boolean, default false) "
-                  "If the grad op reuse the input's variable.")
-        .SetDefault(false);
-    AddComment(R"DOC(
-Lookup Remote Table Operator.
-
-This operator is used to perform lookups on the parameter W,
-then concatenated into a dense tensor.
-
-The input Ids can carry the LoD (Level of Details) information,
-or not. And the output only shares the LoD information with input Ids.
-
-)DOC");
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-namespace ops = paddle::operators;
-REGISTER_OPERATOR(lookup_remote_table, ops::LookupRemoteTableOp,
-                  paddle::framework::EmptyGradOpMaker,
-                  ops::LookupRemoteTableOpMaker);
-
-REGISTER_OP_CPU_KERNEL(lookup_remote_table, ops::LookupRemoteTableKernel<float>,
-                       ops::LookupRemoteTableKernel<double>);

paddle/fluid/operators/lookup_table_op.cc

@@ -98,7 +98,7 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
         "epmap",
         "(string vector, default 127.0.0.1:6164)"
         "Server endpoints in the order of input variables for mapping")
-        .SetDefault({"127.0.0.1:6164"});
+        .SetDefault({});
 
     AddComment(R"DOC(
 Lookup Table Operator.

paddle/fluid/operators/lookup_table_op.h

@@ -51,10 +51,11 @@ class LookupTableKernel : public framework::OpKernel<T> {
     auto out_name = context.Outputs("Out").front();
     auto table_name = context.Inputs("W").front();
     auto epmap = context.Attr<std::vector<std::string>>("epmap");
+    auto remote_prefetch = context.Attr<bool>("remote_prefetch");
     auto height_sections =
         context.Attr<std::vector<int64_t>>("height_sections");
 
-    if (!epmap.empty()) {
+    if (remote_prefetch) {
 // if emap is not empty, then the paramter will be fetched from remote parameter
 // server
 #ifdef PADDLE_WITH_DISTRIBUTE