operator.cc

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

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. */

#include "paddle/framework/operator.h"
#include <algorithm>
#include <atomic>

namespace paddle {
namespace framework {

template <>
Eigen::DefaultDevice& ExecutionContext::GetEigenDevice<
    platform::CPUPlace, Eigen::DefaultDevice>() const {
  return *device_context_.GetEigenDevice<platform::CPUPlace>();
}

#ifdef PADDLE_WITH_CUDA
template <>
Eigen::GpuDevice&
ExecutionContext::GetEigenDevice<platform::GPUPlace, Eigen::GpuDevice>() const {
  return *device_context_.GetEigenDevice<platform::GPUPlace>();
}
#endif

const Tensor* GetTensorFromVar(const Variable* var) {
  if (var->IsType<LoDTensor>()) {
    return &var->Get<LoDTensor>();
  }
  PADDLE_ENFORCE(var->IsType<Tensor>(),
                 "The Input must be LoDTensor or Tensor.");
  return &var->Get<Tensor>();
}

Tensor* GetTensorFromVar(Variable* var) {
  if (var->IsType<LoDTensor>()) {
    return var->GetMutable<LoDTensor>();
  }
  PADDLE_ENFORCE(var->IsType<Tensor>(),
                 "The Input must be LoDTensor or Tensor.");
  return var->GetMutable<Tensor>();
}

std::string OperatorBase::Input(const std::string& name) const {
  auto& ins = Inputs(name);
  PADDLE_ENFORCE_LE(ins.size(), 1UL,
                    "Op %s input %s should contain only one variable", type_,
                    name);
  return ins.empty() ? kEmptyVarName : ins[0];
}

const std::vector<std::string>& OperatorBase::Inputs(
    const std::string& name) const {
  auto it = inputs_.find(name);
  PADDLE_ENFORCE(it != inputs_.end(), "Op %s do not have input %s", type_,
                 name);
  return it->second;
}

std::string OperatorBase::Output(const std::string& name) const {
  auto& outs = Outputs(name);
  PADDLE_ENFORCE_LE(outs.size(), 1UL,
                    "Op %s output %s should contain only one variable", type_,
                    name);
  return outs.empty() ? kEmptyVarName : outs[0];
}

const std::vector<std::string>& OperatorBase::Outputs(
    const std::string& name) const {
  auto it = outputs_.find(name);
  PADDLE_ENFORCE(it != outputs_.end(), "Op %s does not have output called %s",
                 type_, name);
  return it->second;
}

std::string OperatorBase::DebugString() const {
  std::stringstream ss;
  ss << "Op(" << type_ << "), inputs:{";
  for (auto it = inputs_.begin(); it != inputs_.end();) {
    auto& input = *it;
    ss << input.first << "[";
    for (size_t i = 0; i < input.second.size(); ++i) {
      ss << input.second[i];
      if (i != input.second.size() - 1) {
        ss << ", ";
      }
    }
    ss << "]";
    ++it;
    if (it != inputs_.end()) {
      ss << ", ";
    }
  }
  ss << "}, outputs:{";
  for (auto it = outputs_.begin(); it != outputs_.end();) {
    auto& output = *it;
    ss << output.first << "[";
    for (size_t i = 0; i < output.second.size(); ++i) {
      ss << output.second[i];
      if (i != output.second.size() - 1) {
        ss << ", ";
      }
    }
    ss << "]";
    ++it;
    if (it != outputs_.end()) {
      ss << ", ";
    }
  }
  ss << "}.";
  return ss.str();
}

void OperatorBase::Rename(const std::string& old_name,
                          const std::string& new_name) {
  for (auto& input : inputs_) {
    std::replace(input.second.begin(), input.second.end(), old_name, new_name);
  }
  for (auto& output : outputs_) {
    std::replace(output.second.begin(), output.second.end(), old_name,
                 new_name);
  }
}

OperatorBase::OperatorBase(const std::string& type,
                           const VariableNameMap& inputs,
                           const VariableNameMap& outputs,
                           const AttributeMap& attrs)
    : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs) {
  GenerateTemporaryNames();
  CheckAllInputOutputSet();
}

std::vector<std::string> OperatorBase::InputVars() const {
  std::vector<std::string> ret_val;
  for (auto& o : outputs_) {
    ret_val.reserve(ret_val.size() + o.second.size());
    ret_val.insert(ret_val.end(), o.second.begin(), o.second.end());
  }
  return ret_val;
}

std::vector<std::string> OperatorBase::OutputVars(bool has_intermediate) const {
  std::vector<std::string> ret_val;
  if (has_intermediate) {
    // push all outputs into ret_val
    for (auto& o : outputs_) {
      ret_val.reserve(ret_val.size() + o.second.size());
      ret_val.insert(ret_val.end(), o.second.begin(), o.second.end());
    }
    return ret_val;
  }
  auto& info = OpInfoMap::Instance().Get(Type());

  // get all OpProto::Var for outputs
  for (auto& o : info.Proto().outputs()) {
    // ignore all intermediate output
    if (o.intermediate()) continue;
    auto out = outputs_.find(o.name());
    if (out != outputs_.end()) {
      ret_val.reserve(ret_val.size() + out->second.size());
      ret_val.insert(ret_val.end(), out->second.begin(), out->second.end());
    }
  }
  return ret_val;
}

void OperatorBase::CheckAllInputOutputSet() const {
  auto& info_map = OpInfoMap::Instance();
  auto* op_info = info_map.GetNullable(Type());
  if (op_info == nullptr || op_info->proto_ == nullptr) return;

  for (auto& in : op_info->Proto().inputs()) {
    PADDLE_ENFORCE(inputs_.find(in.name()) != inputs_.end(),
                   "Type %s's input %s is not set", Type(), in.name());
  }

  for (auto& out : op_info->Proto().outputs()) {
    PADDLE_ENFORCE(outputs_.find(out.name()) != outputs_.end(),
                   "Type %s's output %s is not set", Type(), out.name());
  }
}

void OperatorBase::GenerateTemporaryNames() {
  static std::atomic<size_t> gUniqId(0UL);
  for (auto& output : outputs_) {
    for (auto& output_name : output.second) {
      if (output_name == kTempVarName) {
        output_name += type_;
        output_name += "@";
        output_name += std::to_string(gUniqId.fetch_add(1));
      }
    }
  }
}

template <>
const Tensor* ExecutionContext::Input<Tensor>(const std::string& name) const {
  auto* var = InputVar(name);
  return var == nullptr ? nullptr : GetTensorFromVar(var);
}

template <>
const std::vector<const Tensor*> ExecutionContext::MultiInput<Tensor>(
    const std::string& name) const {
  auto names = op().Inputs(name);
  std::vector<const Tensor*> res;
  res.reserve(names.size());
  std::transform(names.begin(), names.end(), std::back_inserter(res),
                 [&](const std::string& sub_name) {
                   auto var = scope_.FindVar(sub_name);
                   return var == nullptr ? nullptr : GetTensorFromVar(var);
                 });
  return res;
}

template <>
Tensor* ExecutionContext::Output<Tensor>(const std::string& name) const {
  auto var = OutputVar(name);
  return var == nullptr ? nullptr : var->GetMutable<LoDTensor>();
}

template <>
std::vector<Tensor*> ExecutionContext::MultiOutput<Tensor>(
    const std::string& name) const {
  auto names = op().Outputs(name);
  std::vector<Tensor*> res;
  res.reserve(names.size());
  std::transform(names.begin(), names.end(), std::back_inserter(res),
                 [&](const std::string& sub_name) {
                   auto var = scope_.FindVar(sub_name);
                   return var == nullptr ? nullptr
                                         : var->GetMutable<LoDTensor>();
                 });
  return res;
}

std::ostream& operator<<(std::ostream& os,
                         const OperatorWithKernel::OpKernelKey& kernel_key) {
  os << "place[" << kernel_key.place_ << "]:data_type[" << kernel_key.data_type_
     << "]";
  return os;
}

bool OpSupportGPU(const std::string& op_type) {
  auto& all_kernels = OperatorWithKernel::AllOpKernels();
  auto it = all_kernels.find(op_type);
  if (it == all_kernels.end()) {
    // All control operator must support GPU
    return true;
  }
  for (auto& kern_pair : it->second) {
    if (platform::is_gpu_place(kern_pair.first.place_)) {
      return true;
    }
  }
  return false;
}

}  // namespace framework
}  // namespace paddle