



import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


lowerCAmelCase:      Optional[Any]		 =		["small", "medium", "large"]

lowerCAmelCase:      Dict		 =		"lm_head.decoder.weight"
lowerCAmelCase:      str		 =		"lm_head.weight"
def    lowerCamelCase__ (		_A				,    _A       ):
  a		:      List[Any]       =  torch.load(__A       )
  a		:      Tuple       =  d.pop(__A       )
  os.makedirs(__A				,    exist_ok=__A       )
  torch.save(__A				,    os.path.join(__A				,    __A       )       )


if __name__ == "__main__":
     lowerCAmelCase:      Dict		 =		argparse.ArgumentParser()
     parser.add_argument('--dialogpt_path', default='.', type=str)
     lowerCAmelCase:      Optional[int]		 =		parser.parse_args()
     for MODEL in DIALOGPT_MODELS:
          lowerCAmelCase:      Union[str, Any]		 =		os.path.join(args.dialogpt_path, F"{MODEL}_ft.pkl")
          lowerCAmelCase:      str		 =		F"./DialoGPT-{MODEL}"
          convert_dialogpt_checkpoint(
              checkpoint_path,
              pytorch_dump_folder_path,
          )




'''simple docstring'''






import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def    lowerCamelCase__ (		_A       ):
  return EnvironmentCommand()

class 							a__(      lowerCamelCase__			):







    @staticmethod
    def     lowercase_ (   __snake_case				:						ArgumentParser			):
      a		:      Tuple       =  parser.add_parser('env'			)
      download_parser.set_defaults(func=__snake_case			)







    def     lowercase_ (   self				:						List[str]			):
      a		:      str       =  huggingface_hub.__version__

      a		:      List[str]       =  'not installed'
      a		:      List[str]       =  'NA'
      if is_torch_available():
        import torch

        a		:      Optional[Any]       =  torch.__version__
        a		:      int       =  torch.cuda.is_available()

      a		:      Optional[int]       =  'not installed'
      if is_transformers_available():
        import transformers

        a		:      Tuple       =  transformers.__version__

      a		:      Dict       =  'not installed'
      if is_accelerate_available():
        import accelerate

        a		:      int       =  accelerate.__version__

      a		:      Any       =  'not installed'
      if is_xformers_available():
        import xformers

        a		:      Optional[int]       =  xformers.__version__

      a		:      List[str]       =  {
          '`diffusers` version': version,
          'Platform': platform.platform(),
          'Python version': platform.python_version(),
          'PyTorch version (GPU?)': F"""{pt_version} ({pt_cuda_available})""",
          'Huggingface_hub version': hub_version,
          'Transformers version': transformers_version,
          'Accelerate version': accelerate_version,
          'xFormers version': xformers_version,
          'Using GPU in script?': '<fill in>',
          'Using distributed or parallel set-up in script?': '<fill in>',
      }

      print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'			)
      print(self.format_dict(__snake_case			)			)

      return info







    @staticmethod
    def     lowercase_ (   __snake_case				:						Union[str, Any]			):
      return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]			) + "\n"