enforce.h 6.5 KB
Newer Older
F
fwenguang 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
/* Copyright (c) 2021 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. */

#pragma once

#include "paddle/fluid/platform/enforce.h"
#ifdef PADDLE_WITH_MLU
#include "paddle/fluid/platform/device/mlu/mlu_info.h"
#endif  // PADDLE_WITH_MLU

#ifdef PADDLE_WITH_MLU
DECLARE_int64(gpu_allocator_retry_time);
#endif

namespace paddle {
namespace platform {

#ifdef PADDLE_WITH_MLU
namespace details {
template <typename T>
struct MLUStatusType {};

#define DEFINE_MLU_STATUS_TYPE(type, success_value, proto_type) \
  template <>                                                   \
  struct MLUStatusType<type> {                                  \
    using Type = type;                                          \
    static constexpr Type kSuccess = success_value;             \
    static constexpr const char* kTypeString = #proto_type;     \
  }

DEFINE_MLU_STATUS_TYPE(cnrtStatus, cnrtSuccess, CNRT);
DEFINE_MLU_STATUS_TYPE(cnnlStatus, CNNL_STATUS_SUCCESS, CNNL);
44
DEFINE_MLU_STATUS_TYPE(mluOpStatus, MLUOP_STATUS_SUCCESS, MLUOP);
F
fwenguang 已提交
45
DEFINE_MLU_STATUS_TYPE(cnStatus, CN_SUCCESS, CN);
46 47 48
#ifdef PADDLE_WITH_CNCL
DEFINE_MLU_STATUS_TYPE(cnclStatus, CNCL_RET_SUCCESS, CNCL);
#endif
F
fwenguang 已提交
49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71

}  // namespace details

/*************** CNRT ERROR ***************/
inline bool is_error(cnrtStatus e) { return e != cnrtSuccess; }

inline std::string build_mlu_error_msg(cnrtStatus e) {
  std::ostringstream sout;
  sout << "MLU CNRT error(" << e << "), " << cnrtGetErrorName(e) << ": "
       << cnrtGetErrorStr(e);
  return sout.str();
}

/*************** CNNL ERROR ***************/
inline bool is_error(cnnlStatus stat) { return stat != CNNL_STATUS_SUCCESS; }

inline std::string build_mlu_error_msg(cnnlStatus stat) {
  std::ostringstream sout;
  sout << "MLU CNNL error(" << stat << "), " << cnnlGetErrorString(stat)
       << ". ";
  return sout.str();
}

72 73 74 75 76 77 78 79 80
/*************** MLU OP ERROR ***************/
inline bool is_error(mluOpStatus stat) { return stat != MLUOP_STATUS_SUCCESS; }

inline std::string build_mlu_error_msg(mluOpStatus stat) {
  std::ostringstream sout;
  sout << "MLU OP error(" << stat << "), " << mluOpGetErrorString(stat) << ". ";
  return sout.str();
}

F
fwenguang 已提交
81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
/*************** CN API ERROR ***************/
inline bool is_error(cnStatus stat) { return stat != CN_SUCCESS; }

inline std::string build_mlu_error_msg(cnStatus stat) {
  const char* error_name;
  const char* error_string;
  cnGetErrorName(stat, &error_name);
  cnGetErrorString(stat, &error_string);

  std::ostringstream sout;
  sout << "MLU CN error(" << static_cast<int>(stat) << "), " << error_name
       << " : " << error_string << ". ";
  return sout.str();
}

96 97 98 99 100 101 102 103 104 105 106
/*************** CNCL ERROR ***************/
#ifdef PADDLE_WITH_CNCL
inline bool is_error(cnclStatus e) { return e != CNCL_RET_SUCCESS; }

inline std::string build_mlu_error_msg(cnclStatus e) {
  std::ostringstream sout;
  sout << "MLU CNCL error(" << e << "), " << cnclGetErrorStr(e) << ". ";
  return sout.str();
}
#endif

F
fwenguang 已提交
107 108 109 110 111 112 113 114 115 116 117 118 119 120
#define PADDLE_ENFORCE_MLU_SUCCESS(COND)                       \
  do {                                                         \
    auto __cond__ = (COND);                                    \
    using __MLU_STATUS_TYPE__ = decltype(__cond__);            \
    constexpr auto __success_type__ =                          \
        ::paddle::platform::details::MLUStatusType<            \
            __MLU_STATUS_TYPE__>::kSuccess;                    \
    if (UNLIKELY(__cond__ != __success_type__)) {              \
      auto __summary__ = ::paddle::platform::errors::External( \
          ::paddle::platform::build_mlu_error_msg(__cond__));  \
      __THROW_ERROR_INTERNAL__(__summary__);                   \
    }                                                          \
  } while (0)

121 122 123 124 125 126 127 128
#define PADDLE_ENFORCE_MLU_LAUNCH_SUCCESS(OP)                  \
  do {                                                         \
    auto res = cnrtGetLastError();                             \
    if (UNLIKELY(res != cnrtSuccess)) {                        \
      auto msg = ::paddle::platform::build_mlu_error_msg(res); \
      PADDLE_THROW(platform::errors::Fatal(                    \
          "CNRT error after kernel (%s): %s", OP, msg));       \
    }                                                          \
F
fwenguang 已提交
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
  } while (0)

inline void retry_sleep(unsigned milliseconds) {
  if (milliseconds < 1000) {
    // usleep argument must be less than 1,000,000. Reference:
    // https://pubs.opengroup.org/onlinepubs/7908799/xsh/usleep.html
    usleep(milliseconds * 1000);
  } else {
    // clip to sleep in seconds because we can not and don't have to
    // sleep for exact milliseconds
    sleep(milliseconds / 1000);
  }
}

#define PADDLE_RETRY_MLU_SUCCESS(COND)                                  \
  do {                                                                  \
    auto __cond__ = (COND);                                             \
    int retry_count = 1;                                                \
    using __MLU_STATUS_TYPE__ = decltype(__cond__);                     \
    constexpr auto __success_type__ =                                   \
        ::paddle::platform::details::MLUStatusType<                     \
            __MLU_STATUS_TYPE__>::kSuccess;                             \
    while (UNLIKELY(__cond__ != __success_type__) && retry_count < 5) { \
      retry_sleep(FLAGS_gpu_allocator_retry_time);                      \
      __cond__ = (COND);                                                \
      ++retry_count;                                                    \
    }                                                                   \
    if (UNLIKELY(__cond__ != __success_type__)) {                       \
      auto __summary__ = ::paddle::platform::errors::External(          \
          ::paddle::platform::build_mlu_error_msg(__cond__));           \
      __THROW_ERROR_INTERNAL__(__summary__);                            \
    }                                                                   \
  } while (0)

#undef DEFINE_MLU_STATUS_TYPE
#endif  // PADDLE_WITH_MLU

}  // namespace platform
}  // namespace paddle