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112 lines
4.0 KiB
112 lines
4.0 KiB
6 years ago
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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 <algorithm>
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#include <memory>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/executor.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/var_type.h"
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namespace paddle {
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namespace operators {
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class ConditionalOp : public framework::OperatorBase {
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public:
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ConditionalOp(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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: OperatorBase(type, inputs, outputs, attrs) {}
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protected:
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std::vector<const framework::LoDTensor *> InputTensors(
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const framework::Scope &scope, const std::string &in_name) const {
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std::vector<const framework::LoDTensor *> retv;
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auto xs = Inputs(in_name);
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retv.resize(xs.size(), nullptr);
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std::transform(
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xs.begin(), xs.end(), retv.begin(),
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[&scope](const std::string &var_name) -> const framework::LoDTensor * {
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auto *var = scope.FindVar(var_name);
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PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", var_name);
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return &var->Get<framework::LoDTensor>();
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});
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return retv;
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}
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bool ScalarCondition(
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const std::vector<const framework::LoDTensor *> &ips) const {
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if (!(ips.size() == 1UL && ips[0]->IsInitialized())) {
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PADDLE_THROW("should have one initialized input as condition");
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}
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PADDLE_ENFORCE(ips[0]->type() == framework::proto::VarType::BOOL &&
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ips[0]->numel() == 1,
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"condition input's data type should be bool, "
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"numel should be 1, actual numel is %d",
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ips[0]->numel());
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bool res = false;
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if (platform::is_gpu_place(ips[0]->place())) {
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#ifdef PADDLE_WITH_CUDA
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framework::LoDTensor cpu_tensor;
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framework::TensorCopy(*ips[0], platform::CPUPlace(), &cpu_tensor);
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platform::DeviceContextPool::Instance().Get(ips[0]->place())->Wait();
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res = cpu_tensor.data<bool>()[0];
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#endif
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} else {
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res = ips[0]->data<bool>()[0];
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}
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return res;
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}
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};
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class ConditionalBlockOpProtoMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("Cond",
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"The conditional variable of this operator. If Cond is empty, the "
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"whole sub-block will not be executed.")
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.AsDuplicable();
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AddInput("Input", "The input variables of the sub-block.").AsDuplicable();
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AddOutput("Out", "The output variables of the sub-block.").AsDuplicable();
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AddOutput("Scope",
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"(std::vector<Scope*>) The step scope of conditional block. To "
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"unify the conditional block, rnn and while op, the type of "
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"scope is std::vector<Scope*>");
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AddAttr<framework::BlockDesc *>(
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"sub_block", "The step block of conditional block operator");
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AddAttr<bool>("is_scalar_condition",
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"The conditional variable (Cond) is used as scalar "
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"condition.")
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.SetDefault(false);
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AddComment(R"DOC(Conditional block operator
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If `is_scalar_condition` is True, the conditional variable (Cond) is a scalar,
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run the operators in sub-block if Cond is True.
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If `is_scalar_condition` is False, the conditional variable (Cond) is a vector or
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tensor, run the operators in sub-block if all of input variables are not empty.
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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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