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125 lines
4.4 KiB
125 lines
4.4 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/operators/multiplex_op.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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class MultiplexOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("Ids"), "Input(Ids) shouldn't be null.");
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PADDLE_ENFORCE(!ctx->Inputs("X").empty(),
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"MultiInput(X) shouldn't be empty.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) shouldn't be null.");
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auto ids_dim = ctx->GetInputDim("Ids");
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PADDLE_ENFORCE(
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ids_dim.size() == 2 && ids_dim[1] == 1,
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"The index tensor must be a vector with size batchSize x 1.");
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auto ins_dims = ctx->GetInputsDim("X");
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auto num_ins = ins_dims.size();
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PADDLE_ENFORCE(num_ins > 1,
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"multiplex operator should have more than "
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"one candidate input tensors.");
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auto in_dim = ins_dims[0];
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PADDLE_ENFORCE(in_dim.size() >= 2,
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"The rank of candidate tensors must be not less than 2.");
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for (size_t i = 1; i < num_ins; i++) {
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auto dim = ins_dims[i];
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PADDLE_ENFORCE(in_dim == dim,
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"All the candidate tensors must have the same size.");
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}
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ctx->SetOutputDim("Out", in_dim);
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}
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framework::DataType IndicateDataType(
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const framework::ExecutionContext& ctx) const override {
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return framework::ToDataType(ctx.MultiInput<Tensor>("X")[0]->type());
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}
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};
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class MultiplexOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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MultiplexOpMaker(framework::OpProto* proto,
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framework::OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("Ids", "The index tensor of multiplex operator.");
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AddInput("X", "The candidate tensors of multiplex operator.")
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.AsDuplicable();
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AddOutput("Out", "The output tensor of multiplex operator.");
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AddComment(R"DOC(Multiplex operator
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Multiplex multiple tensors according to the index provided by the index tensor.
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Ids: the index tensor.
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X[0 : N - 1]: the candidate tensors for output (N >= 2).
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For each index i from 0 to batchSize - 1, the output is the i-th row of the
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the (Ids[i])-th tensor.
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For i-th row of the output tensor:
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y[i] = x_{k}[i]
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where y is the output tensor. `x_{k}` is the k-th input tensor
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and `k = Ids[i]`.
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)DOC");
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}
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};
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class MultiplexGradOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase* ctx) const override {
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PADDLE_ENFORCE(!ctx->Inputs("X").empty(), "Input(X) should not be null.");
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PADDLE_ENFORCE(!ctx->Outputs(framework::GradVarName("X")).empty(),
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"Output(X@Grad) should not be null.");
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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"Input(Out@GRAD) should not be null.");
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std::vector<framework::DDim> d_ins;
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auto ins = ctx->GetInputsDim("X");
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// No need to compute gradient for Input(Ids)
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for (size_t i = 0; i < ins.size(); i++) {
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d_ins.push_back(ins[i]);
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}
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ctx->SetOutputsDim(framework::GradVarName("X"), d_ins);
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}
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framework::DataType IndicateDataType(
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const framework::ExecutionContext& ctx) const override {
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return framework::ToDataType(ctx.MultiInput<Tensor>("X")[0]->type());
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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(multiplex, ops::MultiplexOp, ops::MultiplexOpMaker, multiplex_grad,
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ops::MultiplexGradOp);
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REGISTER_OP_CPU_KERNEL(
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multiplex, ops::MultiplexCPUKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_CPU_KERNEL(
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multiplex_grad,
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ops::MultiplexGradCPUKernel<paddle::platform::CPUPlace, float>);
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