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92 lines
3.4 KiB
92 lines
3.4 KiB
/* Copyright (c) 2019 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/eye_op.h"
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namespace paddle {
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namespace operators {
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class EyeOp : 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->HasOutput("Out"),
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"Output(Out) of EyeOP should not be null.");
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auto num_rows = ctx->Attrs().Get<int64_t>("num_rows");
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PADDLE_ENFORCE(num_rows >= 0,
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"The value of Input(num_rows) should be non-negative int.");
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auto num_columns = ctx->Attrs().Get<int64_t>("num_columns");
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if (num_columns == -1) num_columns = num_rows;
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PADDLE_ENFORCE(
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num_columns >= 0,
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"The value of Input(num_columns) should be non-negative int.");
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ctx->SetOutputDim("Out", {num_rows, num_columns});
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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::proto::VarType::Type(ctx.Attr<int>("dtype")),
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ctx.GetPlace());
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}
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};
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class EyeOpVarTypeInference : public framework::VarTypeInference {
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public:
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void operator()(framework::InferVarTypeContext* ctx) const override {
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auto data_type = static_cast<framework::proto::VarType::Type>(
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boost::get<int>(ctx->GetAttr("dtype")));
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auto& out_var_name = ctx->Output("Out").front();
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ctx->SetDataType(out_var_name, data_type);
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}
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};
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class EyeOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddAttr<int>("dtype",
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"(int, default 5 (FP32)) "
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"Output data type")
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.SetDefault(framework::proto::VarType::FP32);
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AddAttr<int64_t>("num_rows",
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"(int64_t) the number of rows in output tensor");
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AddAttr<int64_t>("num_columns",
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"(int64_t) the number of columns in output tensor."
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"Default -1 means that num_columns=num_rows")
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.SetDefault(-1);
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AddOutput("Out",
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"(Tensor) Construct an identity tensor with "
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"specified shape [num_rows, num_columns]");
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AddComment(R"DOC(
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Return an identity tensor whose shape is [num_rows, num_columns].
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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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using CPU = paddle::platform::CPUDeviceContext;
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using float16 = paddle::platform::float16;
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REGISTER_OPERATOR(eye, ops::EyeOp, ops::EyeOpMaker, ops::EyeOpVarTypeInference,
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paddle::framework::EmptyGradOpMaker);
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REGISTER_OP_CPU_KERNEL(eye, ops::EyeKernel<CPU, float>,
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ops::EyeKernel<CPU, double>,
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ops::EyeKernel<CPU, int64_t>, ops::EyeKernel<CPU, int>,
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ops::EyeKernel<CPU, float16>);
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