prune.cc

/* 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/prune.h"

#include <glog/logging.h>

#include <queue>
#include "paddle/fluid/framework/op_proto_maker.h"

namespace paddle {
namespace framework {

const char kFeedOpType[] = "feed";
const char kFetchOpType[] = "fetch";

const char kRecurrent[] = "recurrent";
const char kStates[] = "states";
const char kExStates[] = "ex_states";

bool HasDependentInputVar(
    const proto::OpDesc& op_desc,
    const std::unordered_set<std::string>& dependent_vars) {
  for (auto& var : op_desc.inputs()) {
    for (auto& argu : var.arguments()) {
      if (dependent_vars.count(argu) != 0) {
        return true;
      }
    }
  }
  return false;
}

bool HasDependentOutputVar(
    const proto::OpDesc& op_desc,
    const std::unordered_set<std::string>& dependent_vars) {
  for (auto& var : op_desc.outputs()) {
    for (auto& argu : var.arguments()) {
      if (dependent_vars.count(argu) != 0) {
        return true;
      }
    }
  }
  return false;
}

bool IsTarget(const proto::OpDesc& op_desc) {
  if (op_desc.has_is_target()) {
    return op_desc.is_target();
  }
  return false;
}

bool HasTrueTarget(const proto::OpDesc& op_desc) {
  return op_desc.has_is_target() && op_desc.is_target();
}

bool HasFalseTarget(const proto::OpDesc& op_desc) {
  return op_desc.has_is_target() && !op_desc.is_target();
}

int GetSubBlockIndex(const proto::OpDesc& op_desc) {
  // The block index >= 0, so -1 is used to indicate "NotFound".
  for (auto& attr : op_desc.attrs()) {
    if (attr.type() == proto::AttrType::BLOCK) {
      PADDLE_ENFORCE_EQ(attr.has_block_idx(), true,
                        platform::errors::NotFound(
                            "Attribute sub_block is not found in operator %s",
                            op_desc.type()));
      return attr.block_idx();
    }
  }
  return -1;
}

void SetSubBlockIndex(proto::OpDesc* op_desc, int sub_idx) {
  for (auto& attr : *op_desc->mutable_attrs()) {
    if (attr.type() == proto::AttrType::BLOCK) {
      PADDLE_ENFORCE_EQ(attr.has_block_idx(), true,
                        platform::errors::NotFound(
                            "Attribute sub_block is not found in operator %s",
                            op_desc->type()));
      attr.set_block_idx(sub_idx);
    }
  }
}

bool HasSubBlock(const proto::OpDesc& op_desc) {
  return GetSubBlockIndex(op_desc) > 0;
}

int GetOpRole(const proto::OpDesc& op_desc) {
  for (auto& attr : op_desc.attrs()) {
    if (attr.name() == OpProtoAndCheckerMaker::OpRoleAttrName()) {
      PADDLE_ENFORCE_EQ(
          attr.has_i(), true,
          platform::errors::NotFound("Attribute %s is empty in operator %s",
                                     OpProtoAndCheckerMaker::OpRoleAttrName(),
                                     op_desc.type()));
      return attr.i();
    }
  }
  // If attr op_role is not found, it may be operator created in c++ test, like
  // prune_test.cc. In that case, the op_role should be defaut value, which is
  // kNotSpecified.
  return static_cast<int>(OpRole::kNotSpecified);
}

void AppendOpInputVarNames(const proto::OpDesc& op_desc,
                           std::unordered_set<std::string>* vars_set) {
  for (auto& var : op_desc.inputs()) {
    for (auto& arg : var.arguments()) {
      vars_set->emplace(arg);
    }
  }
}

void AppendOpOutputVarNames(const proto::OpDesc& op_desc,
                            std::unordered_set<std::string>* vars_set) {
  for (auto& var : op_desc.outputs()) {
    for (auto& arg : var.arguments()) {
      vars_set->emplace(arg);
    }
  }
}

int FindMapByValue(const std::map<int, int>& m, int val) {
  // The content in map should be >= 0, so -1 is used to indicate "NotFound".
  for (auto& pair : m) {
    if (pair.second == val) {
      return pair.first;
    }
  }
  return -1;
}

// block_id is the idx of the current block in the input desc
// parent_block_id is the idx of the parent of the current block
// in the output desc, -1 means the current block is global block
// dependent_vars is passed recursively from the parent block to
// the child block to help pruning
void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
                int block_id, int parent_block_id,
                std::unordered_set<std::string>* dependent_vars,
                const std::set<std::string> feed_var_names,
                std::map<int, int>* pruned_origin_block_id_map) {
  auto& block = input.blocks(block_id);
  auto& ops = block.ops();

  bool expect_feed = true;
  for (auto& op_desc : ops) {
    PADDLE_ENFORCE_EQ(
        op_desc.type() != kFeedOpType || expect_feed, true,
        platform::errors::PreconditionNotMet(
            "All FeedOps are at the beginning of the ProgramDesc"));
    expect_feed = (op_desc.type() == kFeedOpType);
  }

  bool expect_fetch = true;
  for (auto op_iter = ops.rbegin(); op_iter != ops.rend(); ++op_iter) {
    auto& op_desc = *op_iter;
    PADDLE_ENFORCE_EQ(op_desc.type() != kFetchOpType || expect_fetch, true,
                      platform::errors::PreconditionNotMet(
                          "All FetchOps must at the end of the ProgramDesc"));
    expect_fetch = (op_desc.type() == kFetchOpType);
  }

  std::vector<bool> should_run;
  for (auto op_iter = ops.rbegin(); op_iter != ops.rend(); ++op_iter) {
    auto& op_desc = *op_iter;

    // TODO(wanghaipeng03) reconstruct the follwing if/else block
    //                     to extract common code
    //
    // bool should_run_flag = false;
    // if (IsTarget........) {
    //   should_run_flag = true;
    // } else {
    //   if (parent......) {
    //     for (....) {
    //       for (.....) {
    //         if (.....) {
    //           should_run_flag = true;
    //         }
    //       }
    //     }
    //   }
    // }
    //
    // should_run.push_back(should_run_flag);
    // if (should_run_flag) {
    //   for (auto & var: op_desc.iputs()) {
    //     for (....) {
    //       if (.....) {
    //         dependent_vars->insert(argu);
    //       }
    //     }
    //   }
    // }

    if (IsTarget(op_desc) ||
        (HasDependentOutputVar(op_desc, *dependent_vars) &&
         (GetOpRole(op_desc) & static_cast<int>(OpRole::kOptimize)) == 0)) {
      // NOTE(zhiqiu): since optimize op takes the trainable parameters as
      // inputs and output, it may introduce wrong dependency graph.
      // For train mode, the optimize op should be in targets, so is not need
      // and not right to mark optimize op by its outputs.
      // For eval / infer mode, there is no optimize op in program.
      for (auto& var : op_desc.inputs()) {
        for (auto& argu : var.arguments()) {
          if (feed_var_names.count(argu) == 0) {
            dependent_vars->insert(argu);
          }
        }
      }
      should_run.push_back(true);
    } else {
      should_run.push_back(false);
      // If the output of an op modifies feed vars, the op should not clip.
      // For example, in the transformer structure, the third parameter returned
      // by beam_search op is generally assigned to a feed var. Cutting the
      // assign op will cause an error.
      if (parent_block_id != -1) {
        bool flag = false;
        for (auto& var : op_desc.outputs()) {
          for (auto& argu : var.arguments()) {
            if (feed_var_names.count(argu)) {
              flag = true;
            }
          }
        }
        if (flag) {
          should_run.back() = true;

          // If any op should run, then there inputs are dependent_vars
          for (auto& var : op_desc.inputs()) {
            for (auto& argu : var.arguments()) {
              dependent_vars->insert(argu);
            }
          }
        }
      }
    }
  }

  // since we are traversing the ProgramDesc in reverse order
  // we reverse the should_run vector
  std::reverse(should_run.begin(), should_run.end());

  // copy the current block from input to output
  auto* block_field = output->mutable_blocks();
  *block_field->Add() = input.blocks(block_id);

  int output_block_id = output->blocks_size() - 1;
  auto* output_block = output->mutable_blocks(output_block_id);
  output_block->set_idx(output_block_id);
  output_block->set_parent_idx(parent_block_id);

  (*pruned_origin_block_id_map)[output_block_id] = block_id;

  auto* op_field = output_block->mutable_ops();
  op_field->Clear();
  for (size_t i = 0; i < should_run.size(); ++i) {
    if (should_run[i]) {
      auto* op = op_field->Add();
      *op = input.blocks(block_id).ops(i);
      if (HasSubBlock(*op)) {
        VLOG(2) << "Pruning op which has sub block: " << op->type();
        // create sub_block_dependent_vars here to help prune the sub block
        std::unordered_set<std::string> sub_block_dependent_vars;
        for (auto& var : op->inputs()) {
          for (auto& argu : var.arguments()) {
            if (feed_var_names.count(argu) == 0) {
              sub_block_dependent_vars.insert(argu);
            }
          }
        }
        for (auto& var : op->outputs()) {
          for (auto& argu : var.arguments()) {
            if (feed_var_names.count(argu) == 0) {
              sub_block_dependent_vars.insert(argu);
            }
          }
        }

        // Recurrent op's states are also dependent vars
        if (op->type() == kRecurrent) {
          auto& attributes = op->attrs();
          for (auto& attr : attributes) {
            if (attr.name() == kStates || attr.name() == kExStates) {
              for (auto& argu : attr.strings()) {
                if (feed_var_names.count(argu) == 0) {
                  sub_block_dependent_vars.insert(argu);
                }
              }
            }
          }
        }
        // GetSubBlockIndex(*op) is the idx of the sub_block in the input desc
        // output_block_id is the idx of the current block in the output desc
        prune_impl(input, output, GetSubBlockIndex(*op), output_block_id,
                   &sub_block_dependent_vars, feed_var_names,
                   pruned_origin_block_id_map);
      }
    }
  }

  // remove the VarDescs in BlockDesc that are not referenced in
  // the pruned OpDescs
  std::unordered_map<std::string, proto::VarDesc> var_map;
  auto* var_field = output->mutable_blocks(output_block_id)->mutable_vars();
  for (const auto& var : *var_field) {
    var_map[var.name()] = var;
  }

  std::set<std::string> var_names;
  for (const auto& op : *op_field) {
    auto& input_field = op.inputs();
    for (auto& input_var : input_field) {
      for (auto& arg : input_var.arguments()) {
        if (var_map.count(arg) != 0) {
          var_names.insert(arg);
        }
      }
    }
    auto& output_field = op.outputs();
    for (auto& output_var : output_field) {
      for (auto& arg : output_var.arguments()) {
        if (var_map.count(arg) != 0) {
          var_names.insert(arg);
        }
      }
    }
  }

  var_field->Clear();
  for (const auto& name : var_names) {
    *var_field->Add() = var_map[name];
  }
}

// TODO(fengjiayi): Prune() could be inplaced to avoid unnecessary copies
std::map<int, int> Prune(const proto::ProgramDesc& input,
                         const std::set<std::string>& feed_var_names,
                         proto::ProgramDesc* output) {
  std::unordered_set<std::string> dependent_vars;
  output->clear_blocks();
  std::map<int, int> pruned_origin_block_id_map;
  prune_impl(input, output, 0, -1, &dependent_vars, feed_var_names,
             &pruned_origin_block_id_map);
  // update subblock idx
  for (int i = 0; i < output->blocks_size(); i++) {
    auto* pruned = output->mutable_blocks(i);
    auto* ops = pruned->mutable_ops();
    for (auto op_iter = ops->rbegin(); op_iter != ops->rend(); ++op_iter) {
      auto& op_desc = *op_iter;
      if (HasSubBlock(op_desc)) {
        int origin_sub_idx = GetSubBlockIndex(op_desc);
        auto sub_idx =
            FindMapByValue(pruned_origin_block_id_map, origin_sub_idx);
        PADDLE_ENFORCE_NE(sub_idx, -1,
                          platform::errors::NotFound(
                              "The origin sub block id should be found in "
                              "pruned_progin_block_id_map"));
        SetSubBlockIndex(&op_desc, sub_idx);
      }
    }
  }
  return pruned_origin_block_id_map;
}

void PruneBackwardImpl(proto::BlockDesc* origin, proto::BlockDesc* pruned) {
  std::unordered_set<std::string> op_input_vars;
  std::unordered_set<std::string> op_output_vars;

  // Step 1. Mark backward, optimize and lrsched ops in the block
  auto* ops = origin->mutable_ops();
  for (auto op_iter = ops->begin(); op_iter != ops->end(); ++op_iter) {
    auto& op_desc = *op_iter;
    auto op_role = GetOpRole(op_desc);
    if (op_role & static_cast<int>(OpRole::kOptimize) ||
        op_role & static_cast<int>(OpRole::kBackward) ||
        op_role & static_cast<int>(OpRole::kLRSched)) {
      op_desc.set_is_target(false);
    }
  }

  // Step 2. Copy the forward ops which have not been set false target to new
  // ProgramDesc
  // Note: The proto::ProgramDesc doesn't have interface
  //       to remove op and var
  auto* op_field = pruned->mutable_ops();
  op_field->Clear();
  for (auto op_iter = ops->begin(); op_iter != ops->end(); ++op_iter) {
    if (!HasFalseTarget(*op_iter)) {
      auto* op = op_field->Add();
      AppendOpInputVarNames(*op_iter, &op_input_vars);
      AppendOpOutputVarNames(*op_iter, &op_output_vars);
      *op = *op_iter;
    }
  }

  // Step 3. Copy the forward vars to new ProgramDesc,
  // construct all var's map before clear
  auto* origin_vars = origin->mutable_vars();
  auto* pruned_vars = pruned->mutable_vars();
  std::unordered_map<std::string, proto::VarDesc> var_map;
  for (const auto& var : *origin_vars) {
    var_map[var.name()] = var;
  }
  pruned_vars->Clear();

  std::unordered_set<std::string> var_names;
  var_names.insert(op_input_vars.begin(), op_input_vars.end());
  var_names.insert(op_output_vars.begin(), op_output_vars.end());
  for (const auto& name : var_names) {
    if (var_map.count(name)) {
      // NOTE(zhiqiu): For operator in a conditional block, the related vars
      // may not exist in current block, but in its futher block.
      *pruned_vars->Add() = var_map[name];
    }
  }
}  // namespace framework

std::tuple<framework::ProgramDesc, std::map<int, int>> PruneBackward(
    const framework::ProgramDesc& origin) {
  // Copy original ProgramDesc, origin can't be change
  framework::ProgramDesc origin_clone(origin);

  // Step 1. check if the program contains grad loss operator.
  // If not, the program need no pruning.
  bool has_loss_grad_op = false;
  std::queue<int> block_contains_loss;
  std::queue<int> block_contains_loss_grad;
  for (size_t i = 0; i < origin_clone.Size(); i++) {
    auto block_ops = origin_clone.Block(i).AllOps();
    for (auto op : block_ops) {
      int op_role = BOOST_GET_MUTABLE(
          int, op->GetAttr(OpProtoAndCheckerMaker::OpRoleAttrName()));
      if (op_role == (static_cast<int>(OpRole::kBackward) |
                      static_cast<int>(OpRole::kLoss))) {
        op->SetIsTarget(false);
        has_loss_grad_op = true;
        break;
      }
    }
  }

  std::map<int, int> pruned_progin_block_id_map;
  if (!has_loss_grad_op) {
    // No pruning, fast return a copy of the origin ProgramDesc with an empty
    // map, means default mapped, i.e.{0:0, 1:1, ..., n:n}.
    return std::make_tuple(framework::ProgramDesc(origin_clone),
                           pruned_progin_block_id_map);
  }

  proto::ProgramDesc pruned_desc;
  pruned_desc.clear_blocks();

  // Step 2. Prune backward for each block.
  for (size_t i = 0; i < origin_clone.Size(); i++) {
    auto pruned = proto::BlockDesc();
    auto origin = origin_clone.Proto()->mutable_blocks(i);

    PruneBackwardImpl(origin, &pruned);
    // If pruned block contains no operator, it means the block is a
    // backward block and should be pruned.
    // Else, add the block to pruned_desc and update its id & parent_id.
    if (pruned.ops_size() > 0) {
      auto* block_field = pruned_desc.mutable_blocks();
      *block_field->Add() = pruned;

      auto pruned_block_id = pruned_desc.blocks_size() - 1;
      pruned_progin_block_id_map[pruned_block_id] = origin->idx();
      auto* pruned_block = pruned_desc.mutable_blocks(pruned_block_id);
      pruned_block->set_idx(pruned_block_id);

      if (origin->parent_idx() == -1) {
        pruned_block->set_parent_idx(-1);
      } else {
        auto parent_idx =
            FindMapByValue(pruned_progin_block_id_map, origin->parent_idx());
        PADDLE_ENFORCE_NE(parent_idx, -1,
                          platform::errors::NotFound(
                              "The origin parent block id is not found in "
                              "pruned_progin_block_id_map"));
        pruned_block->set_parent_idx(parent_idx);
      }
    }
  }

  // Step 3. Update subblock attribute for conditional operator.
  // This should be performed after all blocks pruned.
  for (int i = 0; i < pruned_desc.blocks_size(); i++) {
    auto* pruned = pruned_desc.mutable_blocks(i);
    auto* ops = pruned->mutable_ops();
    for (auto op_iter = ops->begin(); op_iter != ops->end(); ++op_iter) {
      auto& op_desc = *op_iter;
      if (HasSubBlock(op_desc)) {
        int origin_sub_idx = GetSubBlockIndex(op_desc);
        auto sub_idx =
            FindMapByValue(pruned_progin_block_id_map, origin_sub_idx);
        PADDLE_ENFORCE_NE(sub_idx, -1,
                          platform::errors::NotFound(
                              "The origin sub block id is not found in "
                              "pruned_progin_block_id_map"));
        SetSubBlockIndex(&op_desc, sub_idx);
      }
    }
  }

  // Step 4. Return a tuple
  return std::make_tuple(framework::ProgramDesc(pruned_desc),
                         pruned_progin_block_id_map);
}  // namespace framework

}  // namespace framework
}  // namespace paddle