


# Copyright 2021 The HuggingFace Team. 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.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


snake_case				:    int       				=     '''Create a default config file for Accelerate with only a few flags set.'''
def 				__lowerCamelCase						( UpperCAmelCase_						:		Optional[Any]="no" ,  UpperCAmelCase_						:		str = default_json_config_file ,  UpperCAmelCase_						:		bool = False						):




      """simple docstring"""





      a						:List[str] 							=       Path(UpperCAmelCase_						)
      path.parent.mkdir(parents=UpperCAmelCase_ ,  exist_ok=UpperCAmelCase_						)
      if path.exists():
            print(
                F'''Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.'''						)
            return False
      a						:Optional[Any] 							=       mixed_precision.lower()
      if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
            raise ValueError(
                F'''`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}'''						)
      a						:List[Any] 							=       {
          '''compute_environment''': '''LOCAL_MACHINE''',
          '''mixed_precision''': mixed_precision,
      }
      if torch.cuda.is_available():
            a						:Dict 							=       torch.cuda.device_count()
            a						:Tuple 							=       num_gpus
            a						:int 							=       False
            if num_gpus > 1:
                  a						:str 							=       '''MULTI_GPU'''
            else:
                  a						:List[Any] 							=       '''NO'''
      elif is_xpu_available() and use_xpu:
            a						:List[Any] 							=       torch.xpu.device_count()
            a						:Optional[int] 							=       num_xpus
            a						:List[Any] 							=       False
            if num_xpus > 1:
                  a						:int 							=       '''MULTI_XPU'''
            else:
                  a						:str 							=       '''NO'''
      elif is_npu_available():
            a						:List[str] 							=       torch.npu.device_count()
            a						:Any 							=       num_npus
            a						:Optional[int] 							=       False
            if num_npus > 1:
                  a						:List[str] 							=       '''MULTI_NPU'''
            else:
                  a						:Dict 							=       '''NO'''
      else:
            a						:str 							=       0
            a						:Optional[Any] 							=       True
            a						:Optional[Any] 							=       1
            a						:str 							=       '''NO'''
      a						:List[str] 							=       ClusterConfig(**UpperCAmelCase_						)
      config.to_json_file(UpperCAmelCase_						)
      return path
def 				__lowerCamelCase						( UpperCAmelCase_						:		List[str] ,  UpperCAmelCase_						:		Union[str, Any]						):




      """simple docstring"""





      a						:List[Any] 							=       parser.add_parser('''default''' ,  parents=UpperCAmelCase_ ,  help=UpperCAmelCase_ ,  formatter_class=UpperCAmelCase_						)
      parser.add_argument(
          '''--config_file''' ,  default=UpperCAmelCase_ ,  help=(
              '''The path to use to store the config file. Will default to a file named default_config.yaml in the cache '''
              '''location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '''
              '''such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '''
              '''with \'huggingface\'.'''
          ) ,  dest='''save_location''' ,  )

      parser.add_argument(
          '''--mixed_precision''' ,  choices=['''no''', '''fp16''', '''bf16'''] ,  type=UpperCAmelCase_ ,  help='''Whether or not to use mixed precision training. '''
          '''Choose between FP16 and BF16 (bfloat16) training. '''
          '''BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later.''' ,  default='''no''' ,  )
      parser.set_defaults(func=UpperCAmelCase_						)
      return parser






def 				__lowerCamelCase						( UpperCAmelCase_						:		int						):




      """simple docstring"""





      a						:Optional[Any] 							=       write_basic_config(args.mixed_precision ,  args.save_location						)
      if config_file:
            print(F'''accelerate configuration saved at {config_file}'''						)






import socket



def 	__SCREAMING_SNAKE_CASE  (					)							->					Optional[int]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      socket.socket(socket.AF_INET ,     socket.SOCK_STREAM	)
  SCREAMING_SNAKE_CASE__										=      socket.gethostname()
  SCREAMING_SNAKE_CASE__										=      1_23_12

  sock.connect((host, port)	)
  sock.send(B"""Hello server!"""	)

  with open("""Received_file""" ,     """wb"""	) as out_file:
    print("""File opened"""	)
    print("""Receiving data..."""	)
    while True:
      SCREAMING_SNAKE_CASE__										=      sock.recv(10_24	)
      if not data:
        break
      out_file.write(__UpperCamelCase	)

  print("""Successfully received the file"""	)
  sock.close()
  print("""Connection closed"""	)


if __name__ == "__main__":
   main()
