prune.cc 13.0 KB
Newer Older
X
xiexionghang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
/* 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 <algorithm>
20
#include <memory>
X
xiexionghang 已提交
21 22 23
#include <set>
#include <string>
#include <unordered_map>
24
#include <unordered_set>
X
xiexionghang 已提交
25 26
#include <vector>

27 28 29 30 31
#include "paddle/fluid/framework/block_desc.h"
#include "paddle/fluid/framework/op_desc.h"
#include "paddle/fluid/framework/op_proto_maker.h"
#include "paddle/fluid/framework/program_desc.h"

X
xiexionghang 已提交
32 33 34 35 36 37
namespace paddle {
namespace framework {

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

38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57
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) {
X
xiexionghang 已提交
58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
  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;
}

75 76 77 78 79 80 81 82
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();
}

X
xiexionghang 已提交
83 84 85 86 87 88 89 90 91 92 93 94 95 96
int GetSubBlockIndex(const proto::OpDesc& op_desc) {
  for (auto& attr : op_desc.attrs()) {
    if (attr.type() == proto::AttrType::BLOCK) {
      PADDLE_ENFORCE(attr.has_block_idx());
      return attr.block_idx();
    }
  }
  return -1;
}

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

97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114
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);
    }
  }
}

X
xiexionghang 已提交
115 116 117 118 119 120 121
// 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,
122 123
                std::unordered_set<std::string>* dependent_vars,
                const std::set<std::string> feed_var_names) {
X
xiexionghang 已提交
124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
  auto& block = input.blocks(block_id);
  auto& ops = block.ops();

  bool expect_feed = true;
  for (auto& op_desc : ops) {
    PADDLE_ENFORCE(op_desc.type() != kFeedOpType || expect_feed,
                   "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(op_desc.type() != kFetchOpType || expect_fetch,
                   "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;
145
    if (IsTarget(op_desc) || HasDependentOutputVar(op_desc, *dependent_vars)) {
X
xiexionghang 已提交
146 147 148
      // insert its input to the dependency graph
      for (auto& var : op_desc.inputs()) {
        for (auto& argu : var.arguments()) {
149 150 151
          if (feed_var_names.count(argu) == 0) {
            dependent_vars->insert(argu);
          }
X
xiexionghang 已提交
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
        }
      }
      should_run.push_back(true);
    } else {
      should_run.push_back(false);
    }
  }

  // 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);

  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)) {
180
        VLOG(2) << "Pruning op which has sub block: " << op->type();
X
xiexionghang 已提交
181
        // create sub_block_dependent_vars here to help prune the sub block
182
        std::unordered_set<std::string> sub_block_dependent_vars;
X
xiexionghang 已提交
183 184
        for (auto& var : op->inputs()) {
          for (auto& argu : var.arguments()) {
185 186 187
            if (feed_var_names.count(argu) == 0) {
              sub_block_dependent_vars.insert(argu);
            }
X
xiexionghang 已提交
188 189 190 191
          }
        }
        for (auto& var : op->outputs()) {
          for (auto& argu : var.arguments()) {
192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208
            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);
                }
              }
            }
X
xiexionghang 已提交
209 210 211 212 213
          }
        }
        // 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,
214
                   &sub_block_dependent_vars, feed_var_names);
X
xiexionghang 已提交
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
      }
    }
  }

  // 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
254 255 256 257
void Prune(const proto::ProgramDesc& input,
           const std::set<std::string>& feed_var_names,
           proto::ProgramDesc* output) {
  std::unordered_set<std::string> dependent_vars;
X
xiexionghang 已提交
258
  output->clear_blocks();
259
  prune_impl(input, output, 0, -1, &dependent_vars, feed_var_names);
X
xiexionghang 已提交
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

void CloneWholeBlock(proto::ProgramDesc* input, proto::ProgramDesc* output,
                     int block_id, int parent_block_id) {
  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);
}

void PruneBackwardImpl(proto::ProgramDesc* input, proto::ProgramDesc* output,
                       int block_id, int parent_block_id) {
  // Step 1. Copy the current input block to output
  CloneWholeBlock(input, output, block_id, parent_block_id);
  int output_block_id = output->blocks_size() - 1;
  auto* output_block = output->mutable_blocks(output_block_id);

  // Step 2. Mark forward ops on main branch
  auto* ops = input->mutable_blocks(block_id)->mutable_ops();
  std::unordered_set<std::string> op_input_vars;
  std::unordered_set<std::string> op_output_vars;
  for (auto op_iter = ops->rbegin(); op_iter != ops->rend(); ++op_iter) {
    auto& op_desc = *op_iter;
    if (HasTrueTarget(op_desc) ||
        HasDependentOutputVar(op_desc, op_input_vars)) {
      op_desc.set_is_target(true);
      AppendOpInputVarNames(op_desc, &op_input_vars);
      AppendOpOutputVarNames(op_desc, &op_output_vars);
    }
  }

  // Step 3. Mark backward & optimize ops on main branch
  std::unordered_set<std::string> gradop_input_vars;
  std::unordered_set<std::string> gradop_output_vars;
  for (auto op_iter = ops->begin(); op_iter != ops->end(); ++op_iter) {
    auto& op_desc = *op_iter;
    if (HasFalseTarget(op_desc) ||
        HasDependentInputVar(op_desc, gradop_output_vars)) {
      op_desc.set_is_target(false);
      AppendOpInputVarNames(op_desc, &gradop_input_vars);
      AppendOpOutputVarNames(op_desc, &gradop_output_vars);
    }
  }

  // Step 4. Mark ops need to be reserved on sub-branch
  for (auto op_iter = ops->rbegin(); op_iter != ops->rend(); ++op_iter) {
    auto& op_desc = *op_iter;
    if (!op_desc.has_is_target()) {
      if (HasDependentOutputVar(op_desc, gradop_input_vars)) {
        op_desc.set_is_target(false);
        AppendOpInputVarNames(op_desc, &gradop_input_vars);
      } else {
        op_desc.set_is_target(true);
        AppendOpInputVarNames(op_desc, &op_input_vars);
        AppendOpOutputVarNames(op_desc, &op_output_vars);
      }
    }
  }

  // Step 5. Copy the forward ops to new ProgramDesc
  //   Note: The proto::ProgramDesc doesn't have interface
  //         to remove op and var
  auto* op_field = output_block->mutable_ops();
  op_field->Clear();
  for (auto op_iter = ops->begin(); op_iter != ops->end(); ++op_iter) {
    if (IsTarget(*op_iter)) {
      auto* op = op_field->Add();
      *op = *op_iter;
      if (HasSubBlock(*op)) {
        CloneWholeBlock(input, output, GetSubBlockIndex(*op), output_block_id);
      }
    }
  }

  // Step 6. Copy the forward vars to new ProgramDesc
  // construct all var's map before clear
  auto* var_field = output_block->mutable_vars();
  std::unordered_map<std::string, proto::VarDesc> var_map;
  for (const auto& var : *var_field) {
    var_map[var.name()] = var;
  }
  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());
  var_field->Clear();
  for (const auto& name : var_names) {
    *var_field->Add() = var_map[name];
  }
}

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

  // Step 1. Update loss op's role & set loss op to be target
  //   The loss op's op_role is (kForward | kLoss)
  //   The input ProgramDesc should have loss operator.
  auto ops = origin_clone.Block(0).AllOps();
  bool has_loss_op = false;
  for (auto op : ops) {
    int op_role =
        boost::get<int>(op->GetAttr(OpProtoAndCheckerMaker::OpRoleAttrName()));
    if (op_role == (static_cast<int>(OpRole::kForward) |
                    static_cast<int>(OpRole::kLoss))) {
      op->SetAttr(OpProtoAndCheckerMaker::OpRoleAttrName(),
                  static_cast<int>(OpRole::kForward));
      op->SetIsTarget(true);
      has_loss_op = true;
    } else if (op_role == (static_cast<int>(OpRole::kBackward) |
                           static_cast<int>(OpRole::kLoss))) {
      op->SetIsTarget(false);
      break;
    }
  }
  PADDLE_ENFORCE_EQ(has_loss_op, true,
                    "The Program need to be pruned its backward part"
                    "should have loss operator.");

  // Step 2. Prune backward
  proto::ProgramDesc pruned_desc;
  pruned_desc.clear_blocks();
  PruneBackwardImpl(origin_clone.Proto(), &pruned_desc, 0, -1);

  // Step 3. Contruct new framework::ProgramDesc
  return std::unique_ptr<framework::ProgramDesc>(
      new framework::ProgramDesc(pruned_desc));
}

X
xiexionghang 已提交
391 392
}  // namespace framework
}  // namespace paddle