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108 lines
4.1 KiB
108 lines
4.1 KiB
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/set_value_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 SetValue : public framework::OperatorWithKernel {
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public:
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SetValue(const std::string &type, 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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OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "SetValue");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SetValue");
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auto in_dims = ctx->GetInputDim("Input");
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PADDLE_ENFORCE_LT(
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in_dims.size(), 7,
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platform::errors::InvalidArgument(
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"The rank of input should be less than 7, but received %d.",
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in_dims.size()));
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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 SetValueMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("Input", "(Tensor) Input tensor of set_value operator.");
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AddInput("ValueTensor", "(Tensor) Value tensor of set_value operator.")
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.AsDispensable();
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AddOutput("Out",
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"(Tensor) Output tensor of set_value operator. The output is the "
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"same Tensor as input");
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AddAttr<int>("dtype", "data type of input.")
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.InEnum(
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{framework::proto::VarType::BOOL, framework::proto::VarType::INT32,
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framework::proto::VarType::INT64, framework::proto::VarType::FP32,
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framework::proto::VarType::FP64})
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.SetDefault(framework::proto::VarType::FP32);
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AddAttr<std::vector<int64_t>>(
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"axes", "(list<int64_t>) Axes that `starts` and `ends` apply to.");
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AddAttr<std::vector<int64_t>>(
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"starts",
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"(list<int64_t>) Starting indices of corresponding axis in `axes`");
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AddAttr<std::vector<int64_t>>(
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"ends",
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"(list<int64_t>) Ending indices of corresponding axis in `axes`.");
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AddAttr<std::vector<int>>("bool_values", "store the bool values")
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.SetDefault({});
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AddAttr<std::vector<float>>("fp32_values", "store the float32 values")
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.SetDefault({});
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AddAttr<std::vector<int>>("int32_values", "store the int32 values")
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.SetDefault({});
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AddAttr<std::vector<int64_t>>("int64_values", "store the int64 values")
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.SetDefault({});
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AddAttr<std::vector<double>>("fp64_values", "store the float64 values")
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.SetDefault({});
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AddAttr<std::vector<int64_t>>("shape", "(vector<int64_t>) Shape of values.")
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.SetDefault({});
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AddComment(R"DOC(SetValue operator.
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Assignment to a Tensor in static mode.
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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_OPERATOR(
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set_value, ops::SetValue, ops::SetValueMaker,
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paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
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paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OP_CPU_KERNEL(
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set_value, ops::SetValueKernel<paddle::platform::CPUDeviceContext, int>,
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ops::SetValueKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::SetValueKernel<paddle::platform::CPUDeviceContext, float>,
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ops::SetValueKernel<paddle::platform::CPUDeviceContext, double>,
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ops::SetValueKernel<paddle::platform::CPUDeviceContext, bool>);
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