op_desc.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/op_desc.h"
#include <functional>
#include <mutex>
#include <unordered_map>
#include "glog/logging.h"
#include "paddle/framework/block_desc.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/program_desc.h"
#include "paddle/framework/shape_inference.h"

namespace paddle {
namespace framework {

class OpDesc;
class BlockDesc;
class CompileTimeInferShapeContext : public InferShapeContext {
 public:
  CompileTimeInferShapeContext(const OpDesc &op, const BlockDesc &block);

  bool HasInput(const std::string &name) const override;

  bool HasOutput(const std::string &name) const override;

  bool HasInputs(const std::string &name) const override;

  bool HasOutputs(const std::string &name) const override;

  AttrReader Attrs() const override;

  const std::vector<std::string> &Inputs(
      const std::string &name) const override;

  const std::vector<std::string> &Outputs(
      const std::string &name) const override;

  void ShareLoD(const std::string &in, const std::string &out, size_t i = 0,
                size_t j = 0) const override {
    PADDLE_ENFORCE_LT(i, Inputs(in).size());
    PADDLE_ENFORCE_LT(j, Outputs(out).size());
    auto *in_var = block_.FindVarRecursive(Inputs(in)[i]);
    auto *out_var = block_.FindVarRecursive(Outputs(out)[j]);
    if (in_var->GetType() != proto::VarDesc::LOD_TENSOR) {
      VLOG(3) << "input " << in << " is not LodTensor";
      return;
    }
    PADDLE_ENFORCE_EQ(in_var->GetType(), proto::VarDesc::LOD_TENSOR,
                      "The %d-th output of Output(%s) must be LoDTensor.", j,
                      out);
    out_var->SetLoDLevel(in_var->GetLoDLevel());
  }

  bool IsRuntime() const override;

 protected:
  proto::VarDesc::VarType GetVarType(const std::string &name) const override;

  DDim GetDim(const std::string &name) const override;

  void SetDim(const std::string &name, const DDim &dim) override;

  const OpDesc &op_;
  const BlockDesc &block_;
};

OpDesc::OpDesc(const std::string &type, const VariableNameMap &inputs,
               const VariableNameMap &outputs, const AttributeMap &attrs) {
  desc_.set_type(type);
  inputs_ = inputs;
  outputs_ = outputs;
  attrs_ = attrs;
  need_update_ = true;
}

void OpDesc::CopyFrom(const OpDesc &op_desc) {
  desc_.set_type(op_desc.Type());
  inputs_ = op_desc.inputs_;
  outputs_ = op_desc.outputs_;
  attrs_ = op_desc.attrs_;
  need_update_ = true;
}

OpDesc::OpDesc(const proto::OpDesc &desc, ProgramDesc *prog, BlockDesc *block)
    : desc_(desc), need_update_(false) {
  // restore inputs_
  int input_size = desc_.inputs_size();
  for (int i = 0; i < input_size; ++i) {
    const proto::OpDesc::Var &var = desc_.inputs(i);
    std::vector<std::string> &args = inputs_[var.parameter()];
    int argu_size = var.arguments_size();
    args.reserve(argu_size);
    for (int j = 0; j < argu_size; ++j) {
      args.push_back(var.arguments(j));
    }
  }
  // restore outputs_
  int output_size = desc_.outputs_size();
  for (int i = 0; i < output_size; ++i) {
    const proto::OpDesc::Var &var = desc_.outputs(i);
    std::vector<std::string> &args = outputs_[var.parameter()];
    int argu_size = var.arguments_size();
    args.reserve(argu_size);
    for (int j = 0; j < argu_size; ++j) {
      args.push_back(var.arguments(j));
    }
  }
  // restore attrs_
  for (const proto::OpDesc::Attr &attr : desc_.attrs()) {
    std::string attr_name = attr.name();
    if (attr.type() != proto::AttrType::BLOCK) {
      attrs_[attr_name] = GetAttrValue(attr);
    } else {
      auto bid = attr.block_idx();
      attrs_[attr_name] = prog->MutableBlock(bid);
    }
  }
  this->block_ = block;
}

proto::OpDesc *OpDesc::Proto() {
  Flush();
  return &desc_;
}

const std::vector<std::string> &OpDesc::Input(const std::string &name) const {
  auto it = inputs_.find(name);
  PADDLE_ENFORCE(it != inputs_.end(), "Input %s cannot be found in Op %s", name,
                 Type());
  return it->second;
}

std::vector<std::string> OpDesc::InputArgumentNames() const {
  std::vector<std::string> retv;
  for (auto &ipt : this->inputs_) {
    retv.insert(retv.end(), ipt.second.begin(), ipt.second.end());
  }
  return retv;
}

void OpDesc::SetInput(const std::string &param_name,
                      const std::vector<std::string> &args) {
  need_update_ = true;
  inputs_[param_name] = args;
}

const std::vector<std::string> &OpDesc::Output(const std::string &name) const {
  auto it = outputs_.find(name);
  PADDLE_ENFORCE(it != outputs_.end(), "Output %s cannot be found in Op %s",
                 name, Type());
  return it->second;
}

std::vector<std::string> OpDesc::OutputArgumentNames() const {
  std::vector<std::string> retv;
  for (auto &ipt : this->outputs_) {
    retv.insert(retv.end(), ipt.second.begin(), ipt.second.end());
  }
  return retv;
}

void OpDesc::SetOutput(const std::string &param_name,
                       const std::vector<std::string> &args) {
  need_update_ = true;
  this->outputs_[param_name] = args;
}

proto::AttrType OpDesc::GetAttrType(const std::string &name) const {
  auto it = attrs_.find(name);
  PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
  return static_cast<proto::AttrType>(it->second.which() - 1);
}

std::vector<std::string> OpDesc::AttrNames() const {
  std::vector<std::string> retv;
  retv.reserve(attrs_.size());
  for (auto &attr : attrs_) {
    retv.push_back(attr.first);
  }
  return retv;
}

void OpDesc::SetAttr(const std::string &name, const Attribute &v) {
  this->attrs_[name] = v;
  need_update_ = true;
}

void OpDesc::SetBlockAttr(const std::string &name, BlockDesc &block) {
  this->attrs_[name] = &block;
  need_update_ = true;
}

void OpDesc::SetAttrMap(
    const std::unordered_map<std::string, Attribute> &attr_map) {
  attrs_ = attr_map;
  need_update_ = true;
}

Attribute OpDesc::GetAttr(const std::string &name) const {
  auto it = attrs_.find(name);
  PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
  return it->second;
}

int OpDesc::GetBlockAttr(const std::string &name) const {
  auto it = attrs_.find(name);
  PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
  return boost::get<BlockDesc *>(it->second)->ID();
}

const std::unordered_map<std::string, Attribute> &OpDesc::GetAttrMap() const {
  return attrs_;
}

void OpDesc::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);
  }
  need_update_ = true;
}

void OpDesc::RenameOutput(const std::string &old_name,
                          const std::string &new_name) {
  for (auto &output : outputs_) {
    std::replace(output.second.begin(), output.second.end(), old_name,
                 new_name);
  }
  need_update_ = true;
}

void OpDesc::RenameInput(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);
  }
  need_update_ = true;
}

struct SetAttrDescVisitor : public boost::static_visitor<void> {
  explicit SetAttrDescVisitor(proto::OpDesc::Attr *attr) : attr_(attr) {}
  mutable proto::OpDesc::Attr *attr_;
  void operator()(int v) const { attr_->set_i(v); }
  void operator()(float v) const { attr_->set_f(v); }
  void operator()(const std::string &v) const { attr_->set_s(v); }

  // Please refer to https://github.com/PaddlePaddle/Paddle/issues/7162
  template <class T,
            class = typename std::enable_if<std::is_same<bool, T>::value>::type>
  void operator()(T b) const {
    attr_->set_b(b);
  }

  void operator()(const std::vector<int> &v) const {
    VectorToRepeated(v, attr_->mutable_ints());
  }
  void operator()(const std::vector<float> &v) const {
    VectorToRepeated(v, attr_->mutable_floats());
  }
  void operator()(const std::vector<std::string> &v) const {
    VectorToRepeated(v, attr_->mutable_strings());
  }
  void operator()(const std::vector<bool> &v) const {
    VectorToRepeated(v, attr_->mutable_bools());
  }
  void operator()(BlockDesc *desc) const { attr_->set_block_idx(desc->ID()); }
  void operator()(int64_t v) const { attr_->set_l(v); }
  void operator()(boost::blank) const { PADDLE_THROW("Unexpected branch"); }
};

void OpDesc::Flush() {
  if (need_update_) {
    this->desc_.mutable_inputs()->Clear();
    for (auto &ipt : inputs_) {
      auto *input = desc_.add_inputs();
      input->set_parameter(ipt.first);
      VectorToRepeated(ipt.second, input->mutable_arguments());
    }

    this->desc_.mutable_outputs()->Clear();
    for (auto &opt : outputs_) {
      auto *output = desc_.add_outputs();
      output->set_parameter(opt.first);
      VectorToRepeated(opt.second, output->mutable_arguments());
    }

    this->desc_.mutable_attrs()->Clear();
    for (auto &attr : attrs_) {
      auto *attr_desc = desc_.add_attrs();
      attr_desc->set_name(attr.first);
      attr_desc->set_type(
          static_cast<proto::AttrType>(attr.second.which() - 1));
      SetAttrDescVisitor visitor(attr_desc);
      boost::apply_visitor(visitor, attr.second);
    }

    need_update_ = false;
  }
}

static std::once_flag init_infer_shape_funcs;

static void InitInferShapeFuncs() {
  std::call_once(init_infer_shape_funcs, [] {
    auto &map = OpInfoMap::Instance();
    auto &info_map = *map.mutable_map();

    for (auto &kern_pair : OperatorWithKernel::AllOpKernels()) {
      auto op_type = kern_pair.first;
      auto &op_info = info_map.at(op_type);
      auto op = static_cast<OperatorWithKernel *>(op_info.Creator()(
          "", VariableNameMap{}, VariableNameMap{}, AttributeMap{}));
      if (op_info.infer_shape_) {  // infer_shape has been registered.
        continue;
      }
      op_info.infer_shape_ = [op](InferShapeContext *ctx) {
        op->InferShape(ctx);
      };
    }
  });
}

void OpDesc::CheckAttrs() {
  PADDLE_ENFORCE(!Type().empty(),
                 "CheckAttr() can not be called before type is setted.");
  auto *checker = OpInfoMap::Instance().Get(Type()).Checker();
  if (checker == nullptr) {
    // checker is not configured. That operator could be generated by Paddle,
    // not by users.
    return;
  }
  checker->Check(attrs_);
}

void OpDesc::InferShape(const BlockDesc &block) const {
  VLOG(3) << "CompileTime infer shape on " << Type();
  InitInferShapeFuncs();
  auto &infer_shape = OpInfoMap::Instance().Get(this->Type()).infer_shape_;
  PADDLE_ENFORCE(static_cast<bool>(infer_shape),
                 "%s's infer_shape has not been registered", this->Type());
  CompileTimeInferShapeContext ctx(*this, block);
  if (VLOG_IS_ON(10)) {
    std::ostringstream sout;
    auto inames = this->InputArgumentNames();
    sout << " From [";
    std::copy(inames.begin(), inames.end(),
              std::ostream_iterator<std::string>(sout, ", "));
    sout << "] to [";
    auto onames = this->OutputArgumentNames();
    std::copy(onames.begin(), onames.end(),
              std::ostream_iterator<std::string>(sout, ", "));
    sout << "]";
    VLOG(10) << sout.str();
  }
  infer_shape(&ctx);
}

void OpDesc::InferVarType(BlockDesc *block) const {
  auto &info = OpInfoMap::Instance().Get(this->Type());
  if (info.infer_var_type_) {
    info.infer_var_type_(*this, block);
  } else {
    // all output type is LoDTensor by default
    VLOG(10) << this->Type()
             << " has not registered InferVarType. Set output variables to "
                "LOD_TENSOR";
    for (auto &out_pair : this->outputs_) {
      for (auto &out_var_name : out_pair.second) {
        block->FindRecursiveOrCreateVar(out_var_name)
            .SetType(proto::VarDesc::LOD_TENSOR);
      }
    }
  }
}

CompileTimeInferShapeContext::CompileTimeInferShapeContext(
    const OpDesc &op, const BlockDesc &block)
    : op_(op), block_(block) {}

bool CompileTimeInferShapeContext::HasInput(const std::string &name) const {
  const std::vector<std::string> &input_names = op_.Input(name);
  auto length = input_names.size();
  if (length == 0) {
    return false;
  }
  PADDLE_ENFORCE_EQ(length, 1UL,
                    "Input(%s) should have only one value, "
                    "but it have %d now",
                    name, length);
  return block_.HasVarRecursive(input_names[0]);
}

bool CompileTimeInferShapeContext::HasOutput(const std::string &name) const {
  const std::vector<std::string> &output_names = op_.Output(name);
  auto length = output_names.size();
  if (length == 0) {
    return false;
  }
  PADDLE_ENFORCE_EQ(length, 1UL,
                    "Output(%s) should have only one value, "
                    "but it have %d now",
                    name, length);
  return block_.HasVarRecursive(output_names[0]);
}

bool CompileTimeInferShapeContext::HasInputs(const std::string &name) const {
  const std::vector<std::string> &input_names = op_.Input(name);
  if (input_names.empty()) {
    return false;
  }
  for (auto &input : input_names) {
    if (!block_.HasVarRecursive(input)) return false;
  }
  return true;
}

bool CompileTimeInferShapeContext::HasOutputs(const std::string &name) const {
  const std::vector<std::string> &output_names = op_.Output(name);
  if (output_names.empty()) {
    return false;
  }
  for (auto &output : output_names) {
    if (!block_.HasVarRecursive(output)) return false;
  }
  return true;
}

AttrReader CompileTimeInferShapeContext::Attrs() const {
  return AttrReader(op_.GetAttrMap());
}

const std::vector<std::string> &CompileTimeInferShapeContext::Inputs(
    const std::string &name) const {
  return op_.Input(name);
}

const std::vector<std::string> &CompileTimeInferShapeContext::Outputs(
    const std::string &name) const {
  return op_.Output(name);
}

DDim CompileTimeInferShapeContext::GetDim(const std::string &name) const {
  auto var = block_.FindVarRecursive(name);
  PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
  try {
    auto shape = var->Shape();
    if (shape.empty()) {
      return framework::make_ddim({0UL});
    } else {
      return framework::make_ddim(var->Shape());
    }
  } catch (...) {
    VLOG(5) << "GetDim of variable " << name << " error";
    std::rethrow_exception(std::current_exception());
  }
}

void CompileTimeInferShapeContext::SetDim(const std::string &name,
                                          const DDim &dim) {
  block_.FindVarRecursive(name)->SetShape(framework::vectorize(dim));
}
bool CompileTimeInferShapeContext::IsRuntime() const { return false; }

proto::VarDesc::VarType CompileTimeInferShapeContext::GetVarType(
    const std::string &name) const {
  return block_.FindVarRecursive(name)->GetType();
}

}  // namespace framework
}  // namespace paddle