amp_auto_cast.cc 5.8 KB
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// Copyright (c) 2020 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/imperative/amp_auto_cast.h"

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#include <algorithm>
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#include <memory>
#include <string>
#include <utility>

#include "paddle/fluid/imperative/tracer.h"

namespace paddle {
namespace imperative {

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class VarBase;

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AmpOperators::AmpOperators()
    : allow_ops_(new std::unordered_set<std::string>()),
      block_ops_(new std::unordered_set<std::string>()) {}
AmpOperators::~AmpOperators() {}

AmpOperators& AmpOperators::Instance() {
  static AmpOperators instance;
  return instance;
}

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std::shared_ptr<std::unordered_set<std::string>>
AmpOperators::GetMutableAllowOps() {
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  return allow_ops_;
}

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std::shared_ptr<std::unordered_set<std::string>>
AmpOperators::GetMutableBlockOps() {
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  return block_ops_;
}

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std::ostream& operator<<(std::ostream& os, AmpOperators& ops) {
  os << "allow ops: ";
  auto allow_ops = ops.GetMutableAllowOps();
  std::copy((*allow_ops).begin(), (*allow_ops).end(),
            std::ostream_iterator<std::string>(os, " "));
  os << "; ";
  os << "block ops: ";
  auto block_ops = ops.GetMutableBlockOps();
  std::copy((*block_ops).begin(), (*block_ops).end(),
            std::ostream_iterator<std::string>(os, " "));
  return os;
}

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inline std::string GetDtypeStr(
    const std::shared_ptr<imperative::VarBase>& var) {
  return framework::DataTypeToString(var->DataType());
}

inline bool NeedCast(const std::shared_ptr<VarBase>& var) {
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  if (platform::is_gpu_place(var->Place()) ||
      platform::is_cuda_pinned_place(var->Place())) {
    // CudaPinndePlace is added for varbase created by dataloader
    if (var->DataType() == framework::proto::VarType::FP32 ||
        var->DataType() == framework::proto::VarType::FP16) {
      return true;
    }
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  }
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  return false;
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}

// NOTE: Trace a cast op, so if a var is casted from fp32 to fp16, then the grad
// var will be cast back from fp16 to fp32 during backward phase.
static inline std::shared_ptr<imperative::VarBase> CastToType(
    const std::shared_ptr<VarBase>& var,
    const framework::proto::VarType::Type dst_type) {
  const auto& tracer = imperative::GetCurrentTracer();
  imperative::NameVarBaseMap ins = {{"X", {var}}};
  framework::AttributeMap attrs = {{"in_dtype", var->DataType()},
                                   {"out_dtype", dst_type}};
  auto out = std::shared_ptr<imperative::VarBase>(
      new imperative::VarBase(tracer->GenerateUniqueName()));
  imperative::NameVarBaseMap outs = {{"Out", {out}}};

  {
    AutoCastGuard guard(tracer, false);
    tracer->TraceOp("cast", ins, outs, std::move(attrs));
  }

  return out;
}

static inline std::shared_ptr<imperative::VarBase> CastToFP16(
    const std::shared_ptr<VarBase>& var) {
  auto dst_type = framework::proto::VarType::FP16;
  if (NeedCast(var) && (var->DataType() != dst_type)) {
    return CastToType(var, dst_type);
  }
  return var;
}

static inline std::shared_ptr<imperative::VarBase> CastToFP32(
    const std::shared_ptr<VarBase>& var) {
  auto dst_type = framework::proto::VarType::FP32;
  if (NeedCast(var) && (var->DataType() != dst_type)) {
    return CastToType(var, dst_type);
  }
  return var;
}

static inline framework::proto::VarType::Type GetPromoteType(
    const NameVarBaseMap& ins) {
  auto dst_type = framework::proto::VarType::FP16;
  for (const auto& pair : ins) {
    for (const auto& var : pair.second) {
      if (var->DataType() == framework::proto::VarType::FP32) {
        dst_type = var->DataType();
        break;
      }
    }
  }
  return dst_type;
}

NameVarBaseMap AutoCastInputs(const std::string& op_type,
                              const NameVarBaseMap& ins) {
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  NameVarBaseMap new_ins(ins);
  if (AmpOperators::Instance().GetMutableAllowOps()->count(op_type)) {
    for (auto& pair : new_ins) {
      // NOTE(zhiqiu): batch_norm and layer_norm support only input x is fp16.
      if ((op_type == "batch_norm" || op_type == "layer_norm") &&
          pair.first != "X") {
        continue;
      }

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      VLOG(5) << "Op(" << op_type << "): Cast " << pair.first << " from "
              << GetDtypeStr(*pair.second.cbegin()) << " to float16";
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      for (auto& var : pair.second) {
        var = CastToFP16(var);
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      }
    }
    return new_ins;
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  } else if (AmpOperators::Instance().GetMutableBlockOps()->count(op_type)) {
    for (auto& pair : new_ins) {
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      VLOG(5) << "Op(" << op_type << "): Cast " << pair.first << " from "
              << GetDtypeStr(*pair.second.cbegin()) << " to float";
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      for (auto& var : pair.second) {
        var = CastToFP32(var);
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      }
    }
    return new_ins;
  } else {
    auto dst_type = GetPromoteType(ins);
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    for (auto& pair : new_ins) {
      // NOTE(zhiqiu): batch_norm and layer_norm support only input x is fp16.
      if ((op_type == "batch_norm" || op_type == "layer_norm") &&
          pair.first == "X" && dst_type == framework::proto::VarType::FP32) {
        continue;
      }
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      VLOG(5) << "Op(" << op_type << "): Cast " << pair.first << " from "
              << GetDtypeStr(*pair.second.cbegin()) << " to "
              << framework::DataTypeToString(dst_type);
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      for (auto& var : pair.second) {
        var = (dst_type == framework::proto::VarType::FP32 ? CastToFP32(var)
                                                           : CastToFP16(var));
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      }
    }
    return new_ins;
  }
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  return new_ins;
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}

}  // namespace imperative
}  // namespace paddle