code: 
  
  
  import json
  import os
  import subprocess
  import sys
  import warnings
  from argparse import ArgumentParser
  from contextlib import AbstractContextManager
  from typing import Dict, List, Optional
  
  import requests
  
  from ..utils import logging
  from . import BaseTransformersCLICommand
  
  
  __snake_case             =	logging.get_logger(__name__)  # pylint: disable=invalid-name
  
  
  __snake_case             =	"lfs-multipart-upload"
  
  
  
  class   __lowerCamelCase (snake_case__	):
  
  
  
  
  
  
  
         @staticmethod
         def 		snake_case_  ( A_:   Tuple				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = parser.add_parser(
                  'lfs-enable-largefiles',help=(
                      'Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'
                  ),)
              enable_parser.add_argument('path',type=__snake_case,help='Local path to repository you want to configure.'				)
              enable_parser.set_defaults(func=lambda A_				: LfsEnableCommand(__snake_case				)				)
  
              __UpperCamelCase   = parser.add_parser(
                  __snake_case,help=(
                      'Deprecated: use `huggingface-cli` instead. '
                      'Command will get called by git-lfs, do not call it directly.'
                  ),)
              upload_parser.set_defaults(func=lambda A_				: LfsUploadCommand(__snake_case				)				)
  
  
  
  class   __lowerCamelCase :
  
  
  
  
  
  
  
         def __init__( self:   List[Any],A_:   Optional[int]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = args
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   List[str]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              warnings.warn(
                  'Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'				)
              __UpperCamelCase   = os.path.abspath(self.args.path				)
              if not os.path.isdir(__snake_case				):
                   print('This does not look like a valid git repo.'				)
                   exit(1				)
              subprocess.run(
                  'git config lfs.customtransfer.multipart.path transformers-cli'.split(),check=__snake_case,cwd=__snake_case				)
              subprocess.run(
                  F'''git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}'''.split(),check=__snake_case,cwd=__snake_case,)
              print('Local repo set up for largefiles'				)
  
  
  
  
  
  
  def 		_A		(		_lowercase   )				->   Union[str, Any]:
  
  
       """simple docstring"""
  
  
       __UpperCamelCase   = json.dumps(UpperCamelCase_   ) + '\n'
       sys.stdout.write(UpperCamelCase_   )
       sys.stdout.flush()
  
  
  
  
  
  
  def 		_A		(		)				->   str:
  
  
       """simple docstring"""
  
  
       __UpperCamelCase   = json.loads(sys.stdin.readline().strip()   )
  
       if "terminate" in (msg.get('type'   ), msg.get('event'   )):
            # terminate message received
            return None
  
       if msg.get('event'   ) not in ("download", "upload"):
            logger.critical('Received unexpected message'   )
            sys.exit(1   )
  
       return msg
  
  
  
  class   __lowerCamelCase (snake_case__	):
  
  
  
  
  
  
  
         def __init__( self:   List[Any],A_:   Any,A_:   List[Any],A_:   Union[str, Any]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = filepath
              __UpperCamelCase   = seek_from
              __UpperCamelCase   = read_limit
              __UpperCamelCase   = 0
  
  
  
  
  
  
  
         def __enter__( self:   List[str]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = open(self.filepath,'rb'				)
              self.f.seek(self.seek_from				)
              return self
  
  
  
  
  
  
  
         def __len__( self:   Union[str, Any]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = os.fstat(self.f.fileno()				).st_size
              return min(self.read_limit,total_length - self.seek_from				)
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   Optional[int],A_:   Dict=-1				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              if self.n_seen >= self.read_limit:
                   return b""
              __UpperCamelCase   = self.read_limit - self.n_seen
              __UpperCamelCase   = self.f.read(remaining_amount if n < 0 else min(__snake_case,__snake_case				)				)
              self.n_seen += len(__snake_case				)
              return data
  
  
  
  
  
  
  
         def __iter__( self:   List[str]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              yield self.read(n=4 * 1024 * 1024				)
  
  
  
  
  
  
  
         def __exit__( self:   str,*A_:   str				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              self.f.close()
  
  
  
  class   __lowerCamelCase :
  
  
  
  
  
  
  
         def __init__( self:   List[str],A_:   List[Any]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = args
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   int				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = json.loads(sys.stdin.readline().strip()				)
              if not (init_msg.get('event'				) == "init" and init_msg.get('operation'				) == "upload"):
                   write_msg({'error': {'code': 32, 'message': 'Wrong lfs init operation'}}				)
                   sys.exit(1				)
  
              # The transfer process should use the information it needs from the
              # initiation structure, and also perform any one-off setup tasks it
              # needs to do. It should then respond on stdout with a simple empty
              # confirmation structure, as follows:
              write_msg({}				)
  
              # After the initiation exchange, git-lfs will send any number of
              # transfer requests to the stdin of the transfer process, in a serial sequence.
              while True:
                   __UpperCamelCase   = read_msg()
                   if msg is None:
                        # When all transfers have been processed, git-lfs will send
                        # a terminate event to the stdin of the transfer process.
                        # On receiving this message the transfer process should
                        # clean up and terminate. No response is expected.
                        sys.exit(0				)
  
                   __UpperCamelCase   = msg['oid']
                   __UpperCamelCase   = msg['path']
                   __UpperCamelCase   = msg['action']['href']
                   __UpperCamelCase   = msg['action']['header']
                   __UpperCamelCase   = int(header.pop('chunk_size'				)				)
                   __UpperCamelCase   = list(header.values()				)
  
                   __UpperCamelCase   = []
                   for i, presigned_url in enumerate(__snake_case				):
                        with FileSlice(__snake_case,seek_from=i * chunk_size,read_limit=__snake_case				) as data:
                             __UpperCamelCase   = requests.put(__snake_case,data=__snake_case				)
                             r.raise_for_status()
                             parts.append(
                                 {
                                     'etag': r.headers.get('etag'				),
                                     'partNumber': i + 1,
                                 }				)
                             # In order to support progress reporting while data is uploading / downloading,
                             # the transfer process should post messages to stdout
                             write_msg(
                                 {
                                     'event': 'progress',
                                     'oid': oid,
                                     'bytesSoFar': (i + 1) * chunk_size,
                                     'bytesSinceLast': chunk_size,
                                 }				)
                             # Not precise but that's ok.
  
                   __UpperCamelCase   = requests.post(
                       __snake_case,json={
                           'oid': oid,
                           'parts': parts,
                       },)
                   r.raise_for_status()
  
                   write_msg({'event': 'complete', 'oid': oid}				)
  
  
  
style_context: 
  
  
  import argparse
  import json
  
  from transformers import GPTNeoConfig, GPTNeoForCausalLM, load_tf_weights_in_gpt_neo
  from transformers.utils import logging
  
  
  logging.set_verbosity_info()
  
  
  
  
  
  
  def 		_A		(		_lowercase				,     _lowercase				,     _lowercase   )				->   List[str]:
  
  
       """simple docstring"""
  
  
       __UpperCamelCase   = json.load(open(_lowercase				,     'r'   )   )
       __UpperCamelCase   = GPTNeoConfig(
           hidden_size=config_json['n_embd']				,     num_layers=config_json['n_layer']				,     num_heads=config_json['n_head']				,     attention_types=config_json['attention_types']				,     max_position_embeddings=config_json['n_positions']				,     resid_dropout=config_json['res_dropout']				,     embed_dropout=config_json['embed_dropout']				,     attention_dropout=config_json['attn_dropout']				,     )
       print(f'''Building PyTorch model from configuration: {config}'''   )
       __UpperCamelCase   = GPTNeoForCausalLM(_lowercase   )
  
       # Load weights from tf checkpoint
       load_tf_weights_in_gpt_neo(_lowercase				,     _lowercase				,     _lowercase   )
  
       # Save pytorch-model
       print(f'''Save PyTorch model to {pytorch_dump_path}'''   )
       model.save_pretrained(_lowercase   )
  
  
  if __name__ == "__main__":
      __snake_case             =	argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
      )
      parser.add_argument(
          '''--config_file''',
          default=None,
          type=str,
          required=True,
          help=(
              '''The config json file corresponding to the pre-trained mesh-tf model. \n'''
              '''This specifies the model architecture.'''
          ),
      )
      parser.add_argument(
          '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
      )
      __snake_case             =	parser.parse_args()
      convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)
  
  
  