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107 lines
3.3 KiB
107 lines
3.3 KiB
/* 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/gather_op.h"
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#include "paddle/fluid/framework/ddim.h"
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namespace paddle {
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namespace operators {
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class GatherOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of GatherOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Index"),
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"Input(Index) of GatherOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of GatherOp should not be null.");
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auto index_dims = ctx->GetInputDim("Index");
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PADDLE_ENFORCE(index_dims.size() == 1);
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int batch_size = ctx->GetInputDim("Index")[0];
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PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0");
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framework::DDim output_dims(ctx->GetInputDim("X"));
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output_dims[0] = batch_size;
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ctx->SetOutputDim("Out", output_dims);
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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(ctx.Input<Tensor>("X")->type()),
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ctx.device_context());
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}
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};
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class GatherGradOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
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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(ctx.Input<Tensor>("X")->type()),
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ctx.device_context());
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}
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};
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class GatherOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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GatherOpMaker(OpProto* proto, OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The source input of gather op");
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AddInput("Index", "The index input of gather op");
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AddOutput("Out", "The output of gather op");
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AddComment(R"DOC(
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Gather Operator.
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$Out = X[Index]$
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Out is obtained by gathering entries of the outer-most dimension
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of X indexed by Index and concatenate them together.
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Example:
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X = [[1, 2],
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[3, 4],
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[5, 6]]
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Index = [[1, 2]]
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Then:
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Out = [[3, 4],
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[5, 6]]
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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(gather, ops::GatherOp, ops::GatherOpMaker, gather_grad,
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ops::GatherGradOp);
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REGISTER_OP_CPU_KERNEL(gather, ops::GatherOpKernel<float>);
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REGISTER_OP_CPU_KERNEL(gather_grad, ops::GatherGradientOpKernel<float>);
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