





import json
import sys




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       str:
  with open(_SCREAMING_SNAKE_CASE		,						encoding='utf-8'		) as f:
    lowercase__           =  json.load(_SCREAMING_SNAKE_CASE		)

  lowercase__           =  ['<details>', '<summary>Show updated benchmarks!</summary>', ' ']

  for benchmark_name in sorted(_SCREAMING_SNAKE_CASE		):
    lowercase__           =  results[benchmark_name]

    lowercase__           =  benchmark_name.split('/'		)[-1]
    output_md.append(F"""### Benchmark: {benchmark_file_name}"""		)

    lowercase__           =  '| metric |'
    lowercase__           =  '|--------|'
    lowercase__           =  '| new / old (diff) |'
    for metric_name in sorted(_SCREAMING_SNAKE_CASE		):
      lowercase__           =  benchmark_res[metric_name]
      lowercase__           =  metric_vals['new']
      lowercase__           =  metric_vals.get('old'		,						_SCREAMING_SNAKE_CASE		)
      lowercase__           =  metric_vals.get('diff'		,						_SCREAMING_SNAKE_CASE		)

      lowercase__           =  F""" {new_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE		,						(int, float)		) else 'None'

      if old_val is not None:
        val_str += F""" / {old_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE		,						(int, float)		) else "None"
      if dif_val is not None:
        val_str += F""" ({dif_val:f})""" if isinstance(_SCREAMING_SNAKE_CASE		,						(int, float)		) else "None"

      title += " " + metric_name + " |"
      lines += "---|"
      value += val_str + " |"

    output_md += [title, lines, value, " "]

  output_md.append('</details>'		)

  with open(_SCREAMING_SNAKE_CASE		,						'w'		,						encoding='utf-8'		) as f:
    f.writelines('\n'.join(_SCREAMING_SNAKE_CASE		)		)


if __name__ == "__main__":
      lowercase_          =		sys.argv[1]
      lowercase_          =		sys.argv[2]

      format_json_to_md(input_json_file, output_md_file)









import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
      from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
      import torch_xla.core.xla_model as xm




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       List[str]:
  if is_torch_version('<'		,						'2.0.0'		) or not hasattr(_SCREAMING_SNAKE_CASE		,						'_dynamo'		):
    return False
  return isinstance(_SCREAMING_SNAKE_CASE		,						torch._dynamo.eval_frame.OptimizedModule		)




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE = True		)    ->       Dict:
  lowercase__           =  (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

  lowercase__           =  is_compiled_module(_SCREAMING_SNAKE_CASE		)
  if is_compiled:
    lowercase__           =  model
    lowercase__           =  model._orig_mod

  if is_deepspeed_available():
    options += (DeepSpeedEngine,)

  while isinstance(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		):
    lowercase__           =  model.module

  if not keep_fpaa_wrapper:
    lowercase__           =  getattr(_SCREAMING_SNAKE_CASE		,						'forward'		)
    lowercase__           =  model.__dict__.pop('_original_forward'		,						_SCREAMING_SNAKE_CASE		)
    if original_forward is not None:
      while hasattr(_SCREAMING_SNAKE_CASE		,						'__wrapped__'		):
        lowercase__           =  forward.__wrapped__
        if forward == original_forward:
          break
      lowercase__           =  forward
    if getattr(_SCREAMING_SNAKE_CASE		,						'_converted_to_transformer_engine'		,						_SCREAMING_SNAKE_CASE		):
      convert_model(_SCREAMING_SNAKE_CASE		,						to_transformer_engine=_SCREAMING_SNAKE_CASE		)

  if is_compiled:
    lowercase__           =  model
    lowercase__           =  compiled_model

  return model




def       __UpperCamelCase  ()    ->       Tuple:
  PartialState().wait_for_everyone()




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       List[Any]:
  if PartialState().distributed_type == DistributedType.TPU:
    xm.save(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)
  elif PartialState().local_process_index == 0:
    torch.save(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)




@contextmanager
def       __UpperCamelCase  (**_SCREAMING_SNAKE_CASE		)    ->       Optional[Any]:
  for key, value in kwargs.items():
    lowercase__           =  str(_SCREAMING_SNAKE_CASE		)

  yield

  for key in kwargs:
    if key.upper() in os.environ:
      del os.environ[key.upper()]




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       List[str]:
  if not hasattr(_SCREAMING_SNAKE_CASE		,						'__qualname__'		) and not hasattr(_SCREAMING_SNAKE_CASE		,						'__name__'		):
    lowercase__           =  getattr(_SCREAMING_SNAKE_CASE		,						'__class__'		,						_SCREAMING_SNAKE_CASE		)
  if hasattr(_SCREAMING_SNAKE_CASE		,						'__qualname__'		):
    return obj.__qualname__
  if hasattr(_SCREAMING_SNAKE_CASE		,						'__name__'		):
    return obj.__name__
  return str(_SCREAMING_SNAKE_CASE		)




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       Dict:
  for key, value in source.items():
    if isinstance(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		):
      lowercase__           =  destination.setdefault(_SCREAMING_SNAKE_CASE		,						{}		)
      merge_dicts(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)
    else:
      lowercase__           =  value

  return destination




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE = None		)    ->       bool:
  if port is None:
    lowercase__           =  29500
  with socket.socket(socket.AF_INET		,						socket.SOCK_STREAM		) as s:
    return s.connect_ex(('localhost', port)		) == 0


