feature/DC asgd (#12722)
* wip * add ref_by_trainer_id op * ready to test * fix ref inputs * refine rpc_op_handle * fix merge bugfix_recordio_link
Wu Yi
6 years ago
committed by
GitHub
parent
c3cbf0b8ef
commit
306236c2c0
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/* Copyright (c) 2016 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/ref_by_trainer_id_op.h"
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#include <string>
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namespace paddle {
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namespace operators {
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class RefByTrainerIdOp : public framework::OperatorWithKernel {
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public:
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RefByTrainerIdOp(const std::string &type,
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const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorWithKernel(type, inputs, outputs, attrs) {}
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInputs("X"),
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"Input(X) of RefByTrainerIdOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("TrainerId"),
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"Input(TrainerId) of RefByTrainerIdOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of RefByTrainerIdOp should not be null.");
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PADDLE_ENFORCE_EQ(ctx->GetInputDim("TrainerId").size(), 1,
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"TrainerId should be a scalar.");
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// Out's shape is determined at runtime.
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext &ctx) const override {
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return framework::OpKernelType(
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framework::ToDataType(
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ctx.MultiInput<framework::Tensor>("X")[0]->type()),
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ctx.GetPlace());
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}
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};
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class RefByTrainerIdOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "(Tensor) Input tensor list.").AsDuplicable();
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AddInput("TrainerId", "(Tensor) Scalar int, the trainer id runtime value.");
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AddOutput("Out", "(Tensor) Return one tensor reference of X[trainer_id]");
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AddComment(R"DOC(
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**RefByTrainerId operator**
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Return a reference of a tensor, using trainer_id as the index to find from the input.
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$$Out = X[TrainerId]$$
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)DOC");
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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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REGISTER_OP_WITHOUT_GRADIENT(ref_by_trainer_id, ops::RefByTrainerIdOp,
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ops::RefByTrainerIdOpMaker);
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REGISTER_OP_CPU_KERNEL(
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ref_by_trainer_id,
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ops::RefByTrainerIdKernel<paddle::platform::CPUDeviceContext, float>,
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ops::RefByTrainerIdKernel<paddle::platform::CPUDeviceContext, double>,
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ops::RefByTrainerIdKernel<paddle::platform::CPUDeviceContext, int>,
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ops::RefByTrainerIdKernel<paddle::platform::CPUDeviceContext, int64_t>);
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@ -0,0 +1,26 @@
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/* Copyright (c) 2016 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/ref_by_trainer_id_op.h"
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REGISTER_OP_CUDA_KERNEL(
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ref_by_trainer_id,
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paddle::operators::RefByTrainerIdKernel<paddle::platform::CUDADeviceContext,
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float>,
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paddle::operators::RefByTrainerIdKernel<paddle::platform::CUDADeviceContext,
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double>,
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paddle::operators::RefByTrainerIdKernel<paddle::platform::CUDADeviceContext,
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int>,
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paddle::operators::RefByTrainerIdKernel<paddle::platform::CUDADeviceContext,
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int64_t>);
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@ -0,0 +1,49 @@
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/* Copyright (c) 2016 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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#pragma once
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#include <stdio.h>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class RefByTrainerIdKernel : public framework::OpKernel<T> {
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public:
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virtual void Compute(const framework::ExecutionContext& context) const {
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auto* out = context.Output<framework::Tensor>("Out");
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auto in_list = context.MultiInput<framework::Tensor>("X");
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auto* trainer_id_t = context.Input<framework::Tensor>("TrainerId");
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int64_t trainer_id;
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auto* trainer_id_data = trainer_id_t->data<int64_t>();
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if (platform::is_gpu_place(context.GetPlace())) {
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#ifdef PADDLE_WITH_CUDA
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auto stream = context.cuda_device_context().stream();
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memory::Copy<>(platform::CPUPlace(), &trainer_id,
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boost::get<platform::CUDAPlace>(context.GetPlace()),
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trainer_id_data, sizeof(int64_t), stream);
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#endif
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} else {
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trainer_id = *trainer_id_data;
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}
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printf("after get trainer_id %lu\n", trainer_id);
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PADDLE_ENFORCE_LT(trainer_id, in_list.size());
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out->mutable_data<T>(context.GetPlace());
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out->ShareDataWith(*(in_list[trainer_id]));
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}
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};
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} // namespace operators
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} // namespace paddle
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