op_desc.cc 27.1 KB
Newer Older
T
tensor-tang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822
/* Copyright (c) 2016 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. */

#include "paddle/fluid/framework/op_desc.h"
#include <algorithm>
#include <functional>
#include <mutex>  // NOLINT
#include <string>
#include <unordered_map>
#include "glog/logging.h"
#include "paddle/fluid/framework/block_desc.h"
#include "paddle/fluid/framework/op_proto_maker.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/shape_inference.h"
#include "paddle/fluid/framework/var_type_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 ShareDim(const std::string &in, const std::string &out, size_t i = 0,
                size_t j = 0) override {
    PADDLE_ENFORCE_LT(i, Inputs(in).size());
    PADDLE_ENFORCE_LT(j, Outputs(out).size());
    const std::string &input_n = Inputs(in)[i];
    const std::string &output_n = Outputs(out)[j];

    PADDLE_ENFORCE(input_n != framework::kEmptyVarName, "The %s[%d] is @EMPTY@",
                   in, i);
    PADDLE_ENFORCE(output_n != framework::kEmptyVarName,
                   "The %s[%d] is @EMPTY@", out, j);

    auto *in_var = block_.FindVarRecursive(input_n);
    auto *out_var = block_.FindVarRecursive(output_n);

    PADDLE_ENFORCE(in_var->GetType() == out_var->GetType(),
                   "The type of %s and %s is not the same.", input_n, output_n);

    SetDim(output_n, GetDim(input_n));
  }

  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());
    PADDLE_ENFORCE(Inputs(in)[i] != framework::kEmptyVarName,
                   "The %s[%d] is @EMPTY@", in, i);
    PADDLE_ENFORCE(Outputs(out)[j] != framework::kEmptyVarName,
                   "The %s[%d] is @EMPTY@", out, j);
    auto *in_var = block_.FindVarRecursive(Inputs(in)[i]);
    auto *out_var = block_.FindVarRecursive(Outputs(out)[j]);
    if (in_var->GetType() != proto::VarType::LOD_TENSOR &&
        in_var->GetType() != proto::VarType::LOD_TENSOR_ARRAY) {
      VLOG(3) << "input " << in << " is not LodTensor or LodTensorArray.";
      return;
    }
    out_var->SetLoDLevel(in_var->GetLoDLevel());
  }

  void DecreaseLoDLevel(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());
    PADDLE_ENFORCE(Inputs(in)[i] != framework::kEmptyVarName,
                   "The %s[%d] is @EMPTY@", in, i);
    PADDLE_ENFORCE(Outputs(out)[j] != framework::kEmptyVarName,
                   "The %s[%d] is @EMPTY@", out, j);
    auto *in_var = block_.FindVarRecursive(Inputs(in)[i]);
    auto *out_var = block_.FindVarRecursive(Outputs(out)[j]);
    PADDLE_ENFORCE(out_var->GetType() == proto::VarType::LOD_TENSOR_ARRAY ||
                       out_var->GetType() == proto::VarType::LOD_TENSOR,
                   "The input %s should be LodTensorArray or LodTensor.",
                   out_var->Name());
    PADDLE_ENFORCE(in_var->GetType() == proto::VarType::LOD_TENSOR,
                   "The input %s should be LodTensor.", in_var->Name());
    if (in_var->GetLoDLevel() > 0) {
      out_var->SetLoDLevel(in_var->GetLoDLevel() - 1);
    }
  }

  std::vector<InferShapeVarPtr> GetInputVarPtrs(
      const std::string &name) override {
    const std::vector<std::string> arg_names = Inputs(name);
    std::vector<InferShapeVarPtr> res;
    res.reserve(arg_names.size());
    std::transform(arg_names.begin(), arg_names.end(), std::back_inserter(res),
                   [this](const std::string &name) {
                     return block_.FindVarRecursive(name);
                   });
    return res;
  }

  std::vector<InferShapeVarPtr> GetOutputVarPtrs(
      const std::string &name) override {
    const std::vector<std::string> arg_names = Outputs(name);
    std::vector<InferShapeVarPtr> res;
    res.reserve(arg_names.size());
    std::transform(arg_names.begin(), arg_names.end(), std::back_inserter(res),
                   [this](const std::string &name) {
                     return block_.FindVarRecursive(name);
                   });
    return res;
  }

  DDim GetInputDim(const std::string &name) const override {
    const std::vector<std::string> &arg_names = Inputs(name);
    PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
                      "Input(%s) should hold one element, but now it holds %d",
                      name, arg_names.size());
    return this->GetDim(arg_names[0]);
  }

  std::vector<DDim> GetInputsDim(const std::string &name) const override {
    const std::vector<std::string> &arg_names = Inputs(name);
    return GetDims(arg_names);
  }

  bool IsRuntime() const override;

  std::vector<proto::VarType::Type> GetInputsVarType(
      const std::string &name) const override {
    return GetVarTypes(Inputs(name));
  }

  std::vector<proto::VarType::Type> GetOutputsVarType(
      const std::string &name) const override {
    return GetVarTypes(Outputs(name));
  }

  void SetOutputDim(const std::string &name, const DDim &dim) override {
    auto &arg_names = Outputs(name);
    PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
                      "Output(%s) should hold one element, but now it holds %d",
                      name, arg_names.size());
    SetDim(arg_names[0], dim);
  }

  void SetOutputsDim(const std::string &name,
                     const std::vector<DDim> &dims) override {
    auto &names = Outputs(name);
    SetDims(names, dims);
  }

 protected:
  std::vector<proto::VarType::Type> GetVarTypes(
      const std::vector<std::string> &names) const {
    std::vector<proto::VarType::Type> retv;
    retv.resize(names.size());
    std::transform(
        names.begin(), names.end(), retv.begin(),
        std::bind(std::mem_fn(&CompileTimeInferShapeContext::GetVarType), this,
                  std::placeholders::_1));
    return retv;
  }

  proto::VarType::Type GetVarType(const std::string &name) const;

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

  std::vector<DDim> GetDims(const std::vector<std::string> &names) const {
    std::vector<DDim> ret;
    ret.reserve(names.size());
    std::transform(
        names.begin(), names.end(), std::back_inserter(ret),
        [this](const std::string &name) { return this->GetDim(name); });
    return ret;
  }

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

  void SetDims(const std::vector<std::string> &names,
               const std::vector<DDim> &dims) {
    size_t length = names.size();
    PADDLE_ENFORCE_EQ(length, dims.size());
    for (size_t i = 0; i < length; ++i) {
      if (names[i] == framework::kEmptyVarName) {
        continue;
      }
      SetDim(names[i], dims[i]);
    }
  }

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

  void SetRepeatedDims(const std::string &name,
                       const std::vector<DDim> &dims) 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;
  block_ = nullptr;
}

OpDesc::OpDesc(const OpDesc &other, BlockDesc *block) {
  CopyFrom(other);
  block_ = block;
  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, 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();
    // The sub_block referred to by the BLOCK attr hasn't been added
    // to ProgramDesc class yet, we skip setting BLOCK/BLOCKS attr here.
    if (attr.type() != proto::AttrType::BLOCK &&
        attr.type() != proto::AttrType::BLOCKS) {
      attrs_[attr_name] = GetAttrValue(attr);
    }
  }
  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;
}

bool OpDesc::HasProtoAttr(const std::string &name) const {
  auto &op_info = OpInfoMap::Instance();
  if (op_info.Has(desc_.type())) {
    auto op_info_ptr = op_info.Get(desc_.type());
    if (op_info_ptr.HasOpProtoAndChecker()) {
      const proto::OpProto &proto = op_info_ptr.Proto();
      for (int i = 0; i != proto.attrs_size(); ++i) {
        const proto::OpProto::Attr &attr = proto.attrs(i);
        if (attr.name() == name) {
          return true;
        }
      }
    }
  }
  return false;
}

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::RemoveAttr(const std::string &name) {
  attrs_.erase(name);
  need_update_ = true;
}

void OpDesc::SetAttr(const std::string &name, const Attribute &v) {
  // NOTICE(minqiyang): pybind11 will take the empty list in python as
  // the std::vector<int> type in C++; so we have to change the attr's type
  // here if we meet this issue
  proto::AttrType attr_type = static_cast<proto::AttrType>(v.which() - 1);
  if (attr_type == proto::AttrType::INTS &&
      boost::get<std::vector<int>>(v).size() == 0u) {
    // Find current attr via attr name and set the correct attribute value
    const proto::OpProto::Attr &attr = GetProtoAttr(name);
    switch (attr.type()) {
      case proto::AttrType::BOOLEANS: {
        VLOG(11) << "SetAttr: " << Type() << ", " << name
                 << " from INTS to BOOLEANS";
        this->attrs_[name] = std::vector<bool>();
        break;
      }
      case proto::AttrType::INTS: {
        VLOG(11) << "SetAttr: " << Type() << ", " << name
                 << " from INTS to INTS";
        this->attrs_[name] = std::vector<int>();
        break;
      }
      case proto::AttrType::LONGS: {
        VLOG(11) << "SetAttr: " << Type() << ", " << name
                 << " from LONGS to LONGS";
        this->attrs_[name] = std::vector<int64_t>();
        break;
      }
      case proto::AttrType::FLOATS: {
        VLOG(11) << "SetAttr: " << Type() << ", " << name
                 << " from INTS to FLOATS";
        this->attrs_[name] = std::vector<float>();
        break;
      }
      case proto::AttrType::STRINGS: {
        VLOG(11) << "SetAttr: " << Type() << ", " << name
                 << " from INTS to STRINGS";
        this->attrs_[name] = std::vector<std::string>();
        break;
      }
      case proto::AttrType::BLOCKS: {
        VLOG(11) << "SetAttr: " << Type() << ", " << name
                 << " from INTS to BLOCKS";
        this->SetBlocksAttr(name, std::vector<BlockDesc *>());
        return;
      }
      default:
        PADDLE_THROW("Wrong attr type %d", attr.type());
    }
    need_update_ = true;
    return;
  }

  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::SetBlocksAttr(const std::string &name,
                           std::vector<BlockDesc *> blocks) {
  this->attrs_[name] = blocks;
  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;
}

const proto::OpProto::Attr &OpDesc::GetProtoAttr(
    const std::string &name) const {
  const proto::OpProto &proto = OpInfoMap::Instance().Get(Type()).Proto();
  for (int i = 0; i != proto.attrs_size(); ++i) {
    const proto::OpProto::Attr &attr = proto.attrs(i);
    if (attr.name() == name) {
      return attr;
    }
  }

  PADDLE_THROW("Attribute %s is not found in proto %s", name, proto.type());
}

Attribute OpDesc::GetNullableAttr(const std::string &name) const {
  auto it = attrs_.find(name);
  if (it != attrs_.end()) {
    return it->second;
  } else {
    return Attribute();
  }
}

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

  std::vector<int> ids;
  for (auto n : blocks) {
    ids.push_back(n->ID());
  }

  return ids;
}

int OpDesc::GetBlockAttrId(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) {
  RenameInput(old_name, new_name);
  RenameOutput(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);
  }

  auto it = attrs_.find(framework::OpProtoAndCheckerMaker::OpRoleVarAttrName());
  if (it != attrs_.end()) {
    auto &op_vars = boost::get<std::vector<std::string>>(it->second);
    std::replace(op_vars.begin(), op_vars.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);
  }

  auto it = attrs_.find(framework::OpProtoAndCheckerMaker::OpRoleVarAttrName());
  if (it != attrs_.end()) {
    auto &op_vars = boost::get<std::vector<std::string>>(it->second);
    std::replace(op_vars.begin(), op_vars.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()(const std::vector<BlockDesc *> &v) const {
    std::vector<int> blocks_idx;
    for (auto blk : v) {
      blocks_idx.push_back(blk->ID());
    }
    VectorToRepeated(blocks_idx, attr_->mutable_blocks_idx());
  }

  void operator()(BlockDesc *desc) const { attr_->set_block_idx(desc->ID()); }

  void operator()(int64_t v) const { attr_->set_l(v); }

  void operator()(const std::vector<int64_t> &v) const {
    VectorToRepeated(v, attr_->mutable_longs());
  }

  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;

/**
 * NOTE(paddle-dev): Very tricky code here. Maybe we should find a
 * better way to register compile-time infershape method gentlely.
 *
 * Normally, we can register a class derived from InferShapeBase, so that
 * we can set the field of `infer_shape_` inside OpInfo when registering op.
 *
 * However, there is another way we can set the field of `infer_shape_` inside
 * OpInfo. Usually, we overload InferShape method of OperatorWithKernel. After
 * running the following method InitInferShapeFuncs, `infer_shape_` would be set
 * to be the InferShape method of OperatorWithKernel. That is to say, we borrow
 * the run-time InferShape method of OperatorWithKernel to be the compile-time
 * InferShape method.
 *
 * However, during compiling time, we may not know inputs, outputs and attrs of
 * run-time OperatorWithKernel. So the following code creates a fake
 * OperatorWithKernel object. That is why the field info_ of OperatorBase
 * would be null.
 */
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 it = info_map.find(op_type);
      PADDLE_ENFORCE(it != info_map.end(), "%s has not been registered",
                     op_type);
      auto &op_info = it->second;
      if (op_info.infer_shape_) {  // infer_shape has been registered.
        continue;
      }

      auto op = dynamic_cast<OperatorWithKernel *>(op_info.Creator()(
          "", VariableNameMap{}, VariableNameMap{}, AttributeMap{}));

      PADDLE_ENFORCE_NOT_NULL(
          op, "InferShapeBase is not registered to Operator %s", op_type);

      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;
  }
  VLOG(10) << "begin to check attribute of " << Type();
  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 {
  // There are a few places that var type can be set.
  // When VarDesc is created, default set to LOD_TENSOR.
  // When output variable is created, default is defaut set to LOD_TENSOR.
  // We limit here to be the only place that operator defines its customized
  // var type inference. Hence, we don't do any "default" setting here.
  auto &info = OpInfoMap::Instance().Get(this->Type());
  if (info.infer_var_type_) {
    InferVarTypeContext context(this, block);
    info.infer_var_type_(&context);
  }
}

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);
}

std::vector<DDim> CompileTimeInferShapeContext::GetRepeatedDims(
    const std::string &name) const {
  auto var = block_.FindVarRecursive(name);
  PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
  std::vector<DDim> res;
  try {
    auto shapes = var->GetShapes();
    for (const auto &s : shapes) {
      res.push_back(s.empty() ? make_ddim({0UL}) : make_ddim(s));
    }
  } catch (...) {
    VLOG(5) << "GetRepeatedDim of variable " << name << " error.";
    std::rethrow_exception(std::current_exception());
  }
  return res;
}

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

void CompileTimeInferShapeContext::SetRepeatedDims(
    const std::string &name, const std::vector<DDim> &dims) {
  auto var = block_.FindVarRecursive(name);
  PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
  std::vector<std::vector<int64_t>> dim_vec(dims.size());
  std::transform(dims.begin(), dims.end(), dim_vec.begin(), vectorize);
  var->SetShapes(dim_vec);
}

bool CompileTimeInferShapeContext::IsRuntime() const { return false; }

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

}  // namespace framework
}  // namespace paddle