// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #pragma once #include #include #include #include #include // NOLINT #include // NOLINT #include // NOLINT #include #include // NOLINT #include // NOLINT #include #include #include "paddle/fluid/framework/op_desc.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/shape_inference.h" #include "paddle/fluid/framework/type_defs.h" #include "paddle/fluid/framework/var_desc.h" #include "paddle/fluid/framework/var_type.h" #include "paddle/fluid/framework/var_type_inference.h" #include "paddle/fluid/framework/variable.h" #include "paddle/fluid/imperative/flags.h" #include "paddle/fluid/imperative/type_defs.h" #include "paddle/fluid/platform/enforce.h" #include "paddle/fluid/platform/macros.h" namespace paddle { namespace imperative { class OpBase; class ThreadSafeNameSet { public: void Insert(const std::string& name); void Remove(const std::string& name); std::vector Names() const; private: std::multiset set_; mutable std::mutex mtx_; }; class VarBase { DISABLE_COPY_AND_ASSIGN(VarBase); public: static std::vector AliveVarNames(); explicit VarBase(bool has_grad, const std::string& name) : name_(name), grad_var_(has_grad ? new VarBase(false, GradVarName()) : nullptr) { if (IsDebugEnabled()) { VLOG(10) << "Construct VarBase: " << name; name_set_.Insert(name_); } } explicit VarBase(const std::string& name) : VarBase(true, name) {} ~VarBase() { VLOG(10) << "Destruct VarBase: " << name_; if (IsDebugEnabled()) { name_set_.Remove(name_); } } const framework::Variable& Var() const { return var_; } framework::Variable* MutableVar() { return &var_; } bool HasGradVar() const { return grad_var_ != nullptr; } const std::shared_ptr& GradVarBase() const { return grad_var_; } const framework::Variable& GradVar() const { PADDLE_ENFORCE_NOT_NULL(grad_var_, "Gradient of %s does not exist", name_); return grad_var_->var_; } framework::Variable* MutableGradVar() { PADDLE_ENFORCE_NOT_NULL(grad_var_, "Gradient of %s does not exist", name_); return &(grad_var_->var_); } // This is used for python api void SetOverridedStopGradient(bool stop_gradient) { if (stop_gradient) { overrided_stop_gradient_ = 1; } else { overrided_stop_gradient_ = 0; } if (grad_var_) { grad_var_->SetOverridedStopGradient(stop_gradient); } } // This is used for python api bool OverridedStopGradient() const { if (overrided_stop_gradient_ == 0) { return false; } else { return true; } } // This is used inside C++ int InnerOverridedStopGradient() const { return overrided_stop_gradient_; } bool GradGenerated() const { return grad_generated_; } void SetGradGenerated(bool generated) { grad_generated_ = generated; } // This is used inside C++ void InnerSetOverridedStopGradient(bool stop_gradient) { if (overrided_stop_gradient_ == -1) { overrided_stop_gradient_ = static_cast(stop_gradient); if (grad_var_) { grad_var_->InnerSetOverridedStopGradient(stop_gradient); } } else { VLOG(6) << "Ignore Stop gradient conversion for Var: " << Name() << "Set value is: " << overrided_stop_gradient_; } } void SetPersistable(bool persistable) { persistable_ = persistable; } bool Persistable() const { return persistable_; } void AddGradOps(const std::weak_ptr& op); std::vector GradOps() { std::vector rlt; // TODO(jiabin): use better data structure to remove nullptr when we find it for (const auto& wk_ptr : grad_ops_) { OpBase* tmp_op = wk_ptr.lock().get(); if (tmp_op) rlt.emplace_back(tmp_op); } return rlt; } void ClearGradOps() { grad_ops_.clear(); } const std::string& Name() const { return name_; } void SetName(const std::string& name) { name_ = name; if (grad_var_) { grad_var_->SetName(GradVarName()); } } std::string GradVarName() { return framework::GradVarName(name_); } void SetType(framework::proto::VarType::Type type) { type_ = type; } framework::proto::VarType::Type Type() const { return type_; } void SetDataType(framework::proto::VarType::Type data_type) { data_type_ = data_type; if (grad_var_) { grad_var_->SetDataType(data_type_); } } framework::proto::VarType::Type DataType() const { return data_type_; } void ClearGradient(); std::shared_ptr NewVarBase(const platform::Place& dst_place, const bool blocking) const; private: framework::Variable var_; std::string name_; std::shared_ptr grad_var_; mutable size_t copied_counter_ = 0; // grad_op indicates which grad_op will this var be used as input std::vector> grad_ops_; // add this property for users may set stop_gradient themselves and this // should override the // frameworks setting (-1) unset, (1) true, (0) false int overrided_stop_gradient_{-1}; bool grad_generated_{false}; bool persistable_{false}; framework::proto::VarType::Type type_{framework::proto::VarType::LOD_TENSOR}; framework::proto::VarType::Type data_type_{framework::proto::VarType::FP32}; static ThreadSafeNameSet name_set_; }; class Layer { public: virtual ~Layer() {} virtual std::vector> Forward( const std::vector>& inputs) { return {}; } }; class DygraphExecutionContext : public framework::ExecutionContext { using Variable = framework::Variable; public: DygraphExecutionContext(const framework::OperatorBase& op, const framework::Scope& scope, const platform::DeviceContext& device_context, const framework::RuntimeContext& ctx, std::vector* configs, const NameVarBaseMap& var_base_map_in, const NameVarBaseMap& var_base_map_out, const framework::AttributeMap* attrs) : ExecutionContext(op, scope, device_context, ctx, configs), var_base_map_in_(var_base_map_in), var_base_map_out_(var_base_map_out), attrs_(attrs) {} std::string InputName(const std::string& name) const { auto it = var_base_map_in_.find(name); PADDLE_ENFORCE_NE(it, var_base_map_in_.end(), platform::errors::PreconditionNotMet( "Can not find [%s] in Input", name)); return it->second[0]->Name(); } std::vector InputNames(const std::string& name) const { auto it = var_base_map_in_.find(name); PADDLE_ENFORCE_NE( it, var_base_map_in_.end(), platform::errors::NotFound("Can not find [%s] in Input", name)); std::vector vec_res; vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.push_back(it->second[i]->Name()); } return vec_res; } std::string OuputName(const std::string& name) const { auto it = var_base_map_out_.find(name); PADDLE_ENFORCE_NE( it, var_base_map_out_.end(), platform::errors::NotFound("Can not find [%s] in Output", name)); return it->second[0]->Name(); } std::vector OutputNames(const std::string& name) const { auto it = var_base_map_out_.find(name); PADDLE_ENFORCE_NE( it, var_base_map_out_.end(), platform::errors::NotFound("Can not find [%s] in Output", name)); std::vector vec_res; vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.push_back(it->second[i]->Name()); } return vec_res; } bool HasAttr(const std::string& name) const { return attrs_->count(name); } const framework::AttributeMap& Attrs() const { return *attrs_; } const framework::Attribute& GetAttr(const std::string& name) const { auto it = attrs_->find(name); PADDLE_ENFORCE_NE( it, attrs_->end(), platform::errors::NotFound("can not find [%s] in attrs", name)); return it->second; } std::vector InNameList() const { std::vector vec_temp; vec_temp.reserve(var_base_map_in_.size()); for (auto& v : var_base_map_in_) { vec_temp.push_back(v.first); } return vec_temp; } bool HasInput(const std::string& name) const { auto it = var_base_map_in_.find(name); return (it != var_base_map_in_.end() && it->second.size() > 0); } virtual bool HasOutput(const std::string& name) const { auto it = var_base_map_out_.find(name); return (it != var_base_map_out_.end() && it->second.size() > 0); } size_t InputSize(const std::string& name) const { return InputNames(name).size(); } size_t OutputSize(const std::string& name) const { return OutputNames(name).size(); } const Variable* InputVar(const std::string& name) const override { auto it = var_base_map_in_.find(name); if (it == var_base_map_in_.end()) { return nullptr; } return it->second.empty() ? nullptr : it->second[0]->MutableVar(); } Variable* OutputVar(const std::string& name) const { auto it = var_base_map_out_.find(name); if (it == var_base_map_out_.end()) { return nullptr; } return it->second.empty() ? nullptr : it->second[0]->MutableVar(); } const std::vector MultiInputVar( const std::string& name) const override { auto it = var_base_map_in_.find(name); if (it == var_base_map_in_.end()) { return {}; } std::vector vec_res; vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.push_back(it->second[i]->MutableVar()); } return vec_res; } std::vector MultiOutputVar( const std::string& name) const override { auto it = var_base_map_out_.find(name); if (it == var_base_map_out_.end()) { return {}; } std::vector vec_res; vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.push_back(it->second[i]->MutableVar()); } return vec_res; } private: const NameVarBaseMap& var_base_map_in_; const NameVarBaseMap& var_base_map_out_; const framework::AttributeMap* attrs_; }; // infer var type context for imperative mode class RuntimeInferVarTypeContext : public framework::InferVarTypeContext { public: RuntimeInferVarTypeContext(const NameVarBaseMap& inputs, const NameVarBaseMap* outputs, const framework::AttributeMap& attrs_map) : InferVarTypeContext(nullptr, nullptr), inputs_(inputs), outputs_(outputs), attrs_(attrs_map), input_names_(), output_names_(), var_set_() { input_names_.reserve(inputs_.size()); for (auto& it : inputs_) { for (auto& var : it.second) { input_names_[it.first].emplace_back(var->Name()); var_set_[var->Name()] = var.get(); } } output_names_.reserve(outputs_->size()); for (auto& it : *outputs_) { for (auto& var : it.second) { output_names_[it.first].emplace_back(var->Name()); var_set_[var->Name()] = var.get(); } } } virtual ~RuntimeInferVarTypeContext() {} framework::Attribute GetAttr(const std::string& name) const override { auto iter = attrs_.find(name); PADDLE_ENFORCE_EQ(iter != attrs_.end(), true, "Cannot find attribute %s", name); return iter->second; } bool HasVar(const std::string& name) const override { return var_set_.count(name) > 0; } bool HasInput(const std::string& name) const override { auto it = inputs_.find(name); return (it != inputs_.end() && it->second.size() > 0); } bool HasOutput(const std::string& name) const override { PADDLE_ENFORCE_NOT_NULL(outputs_); auto it = outputs_->find(name); return (it != outputs_->end() && it->second.size() > 0); } const std::vector& Input( const std::string& name) const override { auto iter = input_names_.find(name); PADDLE_ENFORCE_EQ(iter != input_names_.end(), true, "Cannot find input %s", name); return iter->second; } const std::vector& Output( const std::string& name) const override { auto iter = output_names_.find(name); PADDLE_ENFORCE_EQ(iter != output_names_.end(), true, "Cannot find output %s", name); return iter->second; } framework::proto::VarType::Type GetType( const std::string& name) const override { auto iter = var_set_.find(name); PADDLE_ENFORCE_EQ(iter != var_set_.end(), true, "Cannot find var %s in GetType", name); return iter->second->Type(); } void SetType(const std::string& name, framework::proto::VarType::Type type) override { if (name == "kLookupTablePath") { VLOG(2) << "SUPER UGLY FIX, remove this when move imperative mode in C++"; } else { var_set_[name]->SetType(type); } } framework::proto::VarType::Type GetDataType( const std::string& name) const override { auto iter = var_set_.find(name); PADDLE_ENFORCE_EQ(iter != var_set_.end(), true, "Cannot find var %s in GetDataType", name); return iter->second->DataType(); } void SetDataType(const std::string& name, framework::proto::VarType::Type type) override { var_set_[name]->SetDataType(type); } std::vector GetDataTypes( const std::string& name) const override { PADDLE_THROW("GetDataTypes is not supported in runtime InferVarType"); } void SetDataTypes(const std::string& name, const std::vector& multiple_data_type) override { PADDLE_THROW("SetDataTypes is not supported in runtime InferVarType"); } std::vector GetShape(const std::string& name) const override { PADDLE_THROW("Do not handle Shape in runtime InferVarType"); } void SetShape(const std::string& name, const std::vector& dims) override { PADDLE_THROW("Do not handle Shape in runtime InferVarType"); } int32_t GetLoDLevel(const std::string& name) const override { PADDLE_THROW("Do not handle LoDLevel in runtime InferVarType"); } void SetLoDLevel(const std::string& name, int32_t lod_level) override { PADDLE_THROW("Do not handle LoDLevel in runtime InferVarType"); } private: const NameVarBaseMap& inputs_; const NameVarBaseMap* outputs_; const framework::AttributeMap& attrs_; std::unordered_map> input_names_; std::unordered_map> output_names_; std::unordered_map var_set_; }; // TODO(zjl): to support py_func layer class OpBase : public std::enable_shared_from_this { DISABLE_COPY_AND_ASSIGN(OpBase); public: ~OpBase() { VLOG(3) << "Destruct Op: " << Type() << std::endl; } // Developer should not rely on this method to create OpBase. // OpBase should be created in Tracer and managed by Tracer totally. template static std::shared_ptr Create(Args&&... args) { return std::shared_ptr(new OpBase(std::forward(args)...)); } size_t id() const { return id_; } const std::string& Type() const { return op_->Type(); } void Run(const NameVarBaseMap& ins, const NameVarBaseMap& outs); const framework::VariableNameMap& InputNameMap() const { return op_->Inputs(); } const framework::VariableNameMap& OutputNameMap() const { return op_->Outputs(); } const framework::AttributeMap& Attrs() const { return attrs_; } const framework::OpInfo& Info() const { return op_->Info(); } void ClearBackwardTrace(); const std::vector& GradPendingOps() const { return grad_pending_ops_; } void SetGradPendingOps(std::vector vec_temp) { grad_pending_ops_.swap(vec_temp); } void InsertGradPendingOps(OpBase* op) { grad_pending_ops_.emplace_back(op); } void SortGradPendingOps() { std::sort(grad_pending_ops_.begin(), grad_pending_ops_.end(), [](OpBase* op1, OpBase* op2) { return op1->id() > op2->id(); }); } NameVarBaseMap* GetMutableOutsMap() { return &outs_; } NameVarBaseMap* GetMutableInsMap() { return &ins_; } const NameVarBaseMap& GetInsMap() { return ins_; } const NameVarBaseMap& GetOutsMap() { return outs_; } const platform::Place& place() const { return place_; } // TODO(jiabin) prepare for backward hook void RegisterBackwardHooks(const std::function& func) { backward_hooks_.emplace_back(func); } void InvokeBackwardHooks() { for (const auto& func : backward_hooks_) { func(); VLOG(5) << "Invoke Backward Hook for: " << Type() << std::endl; } } private: OpBase(size_t id, const std::string& type, const NameVarBaseMap& ins, const NameVarBaseMap& outs, const framework::AttributeMap& attrs, const platform::Place& place); public: OpBase() {} void SetType(const std::string& type) { type_ = type; } void SetInput(const std::string& name, std::vector> vec_var_base) { ins_[name] = std::move(vec_var_base); } void SetOutput(const std::string& name, std::vector> vec_var_base) { outs_[name] = std::move(vec_var_base); } void SetAttrMap(const framework::AttributeMap& attrs) { attrs_ = attrs; } void SetAttr(const std::string& name, const framework::Attribute& v) { attrs_[name] = v; } void SetBlockAttr(const std::string& name, framework::BlockDesc* block) { PADDLE_THROW("SetBlockAttr is not support in dygraph OpBase"); } const framework::AttributeMap& Attrs() { return attrs_; } void CreateOperatorBase(); void SetId(size_t id) { id_ = id; } void SetPlace(platform::Place place) { place_ = place; } bool HasAttr(const std::string& name) const { return attrs_.find(name) != attrs_.end(); } const framework::Attribute& GetAttr(const std::string& name) const { auto it = attrs_.find(name); PADDLE_ENFORCE(it != attrs_.end(), "can not find attribute [%s]", name); return it->second; } template inline const T& Attr(const std::string& name) const { return boost::get(GetAttr(name)); } private: size_t id_; std::unique_ptr op_; std::vector> backward_hooks_; platform::Place place_; // Not need to be std::weak_ptr, because op is binded to a certain Tracer, // and would not be used by a Tracer that does not create itself. std::vector grad_pending_ops_; // This part is only used for backward NameVarBaseMap ins_; NameVarBaseMap outs_; std::string type_; framework::AttributeMap attrs_; }; class DygraphInferShapeContext : public framework::InferShapeContext { using DDim = framework::DDim; public: DygraphInferShapeContext(const NameVarBaseMap* in, const NameVarBaseMap* out, const framework::AttributeMap* attr) : var_base_map_in_(in), var_base_map_out_(out), attrs_(attr) {} bool HasInput(const std::string& name) const override { // has only one input auto it = var_base_map_in_->find(name); if (it == var_base_map_in_->end()) { return false; } const auto& in = it->second; if (in.size() == 0) return false; PADDLE_ENFORCE_EQ( in.size(), 1UL, platform::errors::PreconditionNotMet( "Input %s should not have more than one inputs", name)); return in[0] != nullptr; } bool HasOutput(const std::string& name) const override { // has only one output auto it = var_base_map_out_->find(name); if (it == var_base_map_out_->end()) { return false; } const auto& out = it->second; if (out.size() == 0) { return false; } PADDLE_ENFORCE_EQ( out.size(), 1UL, platform::errors::PreconditionNotMet( "Output %s should not have more than one outputs", name)); return out[0] != nullptr; } bool HasInputs(const std::string& name) const override { auto it = var_base_map_in_->find(name); if (it == var_base_map_in_->end() || it->second.empty()) { return false; } for (auto& input : it->second) { if (input == nullptr) { return false; } } return true; } bool HasOutputs(const std::string& name) const override { auto it = var_base_map_out_->find(name); if (it == var_base_map_out_->end() || it->second.empty()) { return false; } for (auto& output : it->second) { if (output == nullptr) { return false; } } return true; } framework::AttrReader Attrs() const override { return framework::AttrReader(*attrs_); } std::vector Inputs(const std::string& name) const override { // return op_.Inputs(name); std::vector vec_res; auto it = var_base_map_in_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_in_->end(), platform::errors::NotFound("can not find [%s] in input", name)); vec_res.reserve(it->second.size()); for (auto& var : it->second) { vec_res.push_back(var->Name()); } return vec_res; } std::vector Outputs(const std::string& name) const override { std::vector vec_res; auto it = var_base_map_out_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_out_->end(), platform::errors::NotFound("can not find [%s] in output", name)); vec_res.reserve(it->second.size()); for (auto& var : it->second) { vec_res.push_back(var->Name()); } return vec_res; } void ShareDim(const std::string& in, const std::string& out, size_t i = 0, size_t j = 0) override { auto in_it = var_base_map_in_->find(in); auto out_it = var_base_map_out_->find(out); PADDLE_ENFORCE_NE( in_it, var_base_map_in_->end(), platform::errors::NotFound("can not found [%s] in input", in)); PADDLE_ENFORCE_GT(in_it->second.size(), i, platform::errors::PreconditionNotMet( "Inputs %s should have %llu argument", in, i)); PADDLE_ENFORCE_NE( out_it, var_base_map_out_->end(), platform::errors::NotFound("can not found [%s] in input", in)); PADDLE_ENFORCE_GT(out_it->second.size(), j, platform::errors::PreconditionNotMet( "Outputs %s should have %llu argument", out, j)); framework::Variable* in_var = in_it->second[i]->MutableVar(); framework::Variable* out_var = out_it->second[j]->MutableVar(); PADDLE_ENFORCE_EQ(in_var->Type(), out_var->Type(), platform::errors::PreconditionNotMet( "The type of %s and %s is not the same.", in, out)); auto& in_lod_tensor = in_var->Get(); auto* out_lod_tensor = out_var->GetMutable(); out_lod_tensor->Resize(in_lod_tensor.dims()); } void ShareAllLoD(const std::string& in, const std::string& out) const override { // do nothing } void ShareLoD(const std::string& in, const std::string& out, size_t i = 0, size_t j = 0) const override { // do nothing } bool IsRuntime() const override { return true; } // TODO(paddle-dev): Can this be template? std::vector GetInputVarPtrs( const std::string& name) override { PADDLE_THROW(platform::errors::PermissionDenied( "GetInputVarPtrs not support in dygraph runtime context")); } std::vector GetOutputVarPtrs( const std::string& name) override { PADDLE_THROW(platform::errors::PermissionDenied( "GetOutputVarPtrs not support in dygraph runtime context")); } DDim GetInputDim(const std::string& name) const override { auto it = var_base_map_in_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_in_->end(), platform::errors::NotFound("can not find [%s] in input", name)); PADDLE_ENFORCE_EQ( it->second.size(), 1UL, platform::errors::PreconditionNotMet( "Input(%s) should hold one element, but now it holds %d", name, it->second.size())); return this->GetDim(it->second[0]->MutableVar()); } std::vector GetInputsDim(const std::string& name) const override { // const std::vector& vars = InputVars(name); std::vector vec_res; auto it = var_base_map_in_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_in_->end(), platform::errors::NotFound("can not find [%s] in output", name)); vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.emplace_back(GetDim(it->second[i]->MutableVar())); } return vec_res; } std::vector GetInputsVarType( const std::string& name) const override { std::vector vec_res; auto it = var_base_map_in_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_in_->end(), platform::errors::NotFound("can not find [%s] in input", name)); vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.emplace_back( framework::ToVarType(it->second[i]->MutableVar()->Type())); } return vec_res; } std::vector GetOutputsVarType( const std::string& name) const override { std::vector vec_res; auto it = var_base_map_out_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_out_->end(), platform::errors::NotFound("can not find [%s] in output", name)); vec_res.reserve(it->second.size()); for (size_t i = 0; i < it->second.size(); ++i) { vec_res.emplace_back( framework::ToVarType(it->second[i]->MutableVar()->Type())); } return vec_res; } void SetOutputDim(const std::string& name, const DDim& dim) override { auto it = var_base_map_out_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_out_->end(), platform::errors::NotFound("can not find [%s] in output", name)); SetDim(it->second[0]->MutableVar(), dim); } void SetOutputsDim(const std::string& name, const std::vector& dims) override { // auto& vars = OutputVars(name); // SetDims(vars, dims); auto it = var_base_map_out_->find(name); PADDLE_ENFORCE_NE( it, var_base_map_out_->end(), platform::errors::NotFound("can not find [%s] in output", name)); PADDLE_ENFORCE_EQ(it->second.size(), dims.size(), platform::errors::PreconditionNotMet( "dim size [%d] is not match output var number [%d]", dims.size(), it->second.size())); for (size_t i = 0; i < dims.size(); ++i) { SetDim(it->second[i]->MutableVar(), dims[i]); } } int32_t GetLoDLevel(const std::string& in, size_t i = 0) const override { PADDLE_THROW(platform::errors::PermissionDenied( "GetLoDLevel function not support in dygraph mode")); } void SetLoDLevel(const std::string& out, int32_t lod_level, size_t j = 0) const override { PADDLE_THROW(platform::errors::PermissionDenied( "SetLoDLevel function not support in dygraph mode")); } protected: DDim GetDim(framework::Variable* var) const { PADDLE_ENFORCE_NOT_NULL(var, platform::errors::PreconditionNotMet( "Input variable should not be null")); if (var->IsType()) { return var->Get().dims(); } else if (var->IsType()) { return var->Get().GetCompleteDims(); } else { PADDLE_THROW(platform::errors::PermissionDenied( "Only LoDTensor/SelectedRows support 'GetDim', but Variables " "type_id is xx.")); } } std::vector GetRepeatedDims(const std::string& name) const override { PADDLE_THROW(platform::errors::PermissionDenied( "GetRepeatedDims not support in dygraph runtime")); } void SetDim(framework::Variable* var, const DDim& dim) { if (var->IsType()) { var->GetMutable()->Resize(dim); } else if (var->IsType()) { var->GetMutable()->set_height(dim[0]); } else { PADDLE_THROW(platform::errors::PermissionDenied( "Variable type_id %s, expect LoDTensor/SelectedRows.")); } } void SetDims(const std::vector& vars, const std::vector& dims) { size_t length = vars.size(); PADDLE_ENFORCE_EQ( length, dims.size(), platform::errors::PreconditionNotMet( "Vars number [%d] should be equal with dims number [%d]", length, dims.size())); for (size_t i = 0; i < length; ++i) { if (vars[i] == nullptr) { continue; } SetDim(vars[i], dims[i]); } } void SetRepeatedDims(const std::string& name, const std::vector& dims) override { PADDLE_THROW(platform::errors::PermissionDenied( "SetRepeatedDims not support in dygraph runtime")); } private: const NameVarBaseMap* var_base_map_in_; const NameVarBaseMap* var_base_map_out_; std::string type_; const framework::AttributeMap* attrs_; }; } // namespace imperative } // namespace paddle