'''simple docstring'''
import os
import sys

lowercase__  :      List[Any]     =					os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


lowercase__  :      Any     =					[
    """torch""",
    """numpy""",
    """tokenizers""",
    """filelock""",
    """requests""",
    """tqdm""",
    """regex""",
    """sentencepiece""",
    """sacremoses""",
    """importlib_metadata""",
    """huggingface_hub""",
]



@add_start_docstrings(AutoConfig.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  int							,    **_UpperCamelCase  :  int					):


      '''simple docstring'''


      return AutoConfig.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)



@add_start_docstrings(AutoTokenizer.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  Optional[int]							,    **_UpperCamelCase  :  Union[str, Any]					):


      '''simple docstring'''


      return AutoTokenizer.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)



@add_start_docstrings(AutoModel.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  str							,    **_UpperCamelCase  :  str					):


      '''simple docstring'''


      return AutoModel.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)



@add_start_docstrings(AutoModelForCausalLM.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  Optional[int]							,    **_UpperCamelCase  :  List[str]					):


      '''simple docstring'''


      return AutoModelForCausalLM.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)



@add_start_docstrings(AutoModelForMaskedLM.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  str							,    **_UpperCamelCase  :  List[Any]					):


      '''simple docstring'''


      return AutoModelForMaskedLM.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)



@add_start_docstrings(AutoModelForSequenceClassification.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  int							,    **_UpperCamelCase  :  Any					):


      '''simple docstring'''


      return AutoModelForSequenceClassification.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)





@add_start_docstrings(AutoModelForQuestionAnswering.__doc__					)
def  __lowerCamelCase       (      *_UpperCamelCase  :  Optional[int]							,    **_UpperCamelCase  :  Optional[int]					):


      '''simple docstring'''


      return AutoModelForQuestionAnswering.from_pretrained(*UpperCamelCase__							,    **UpperCamelCase__					)






'''simple docstring'''
from datetime import datetime

import matplotlib.pyplot as plt
import torch



def  __lowerCamelCase       (      _UpperCamelCase  :  Union[str, Any]					):


      '''simple docstring'''


      for param in module.parameters():
            UpperCAmelCase_            =  False



def  __lowerCamelCase       (      ):


      '''simple docstring'''


      UpperCAmelCase_            =  '''cuda''' if torch.cuda.is_available() else '''cpu'''
      if torch.backends.mps.is_available() and torch.backends.mps.is_built():
            UpperCAmelCase_            =  '''mps'''
      if device == "mps":
            print(
                '''WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'''
                ''' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'''
                ''' with generations.'''					)
      return device



def  __lowerCamelCase       (      _UpperCamelCase  :  Union[str, Any]					):


      '''simple docstring'''


      UpperCAmelCase_            =  plt.imshow(_UpperCamelCase					)
      fig.axes.get_xaxis().set_visible(_UpperCamelCase					)
      fig.axes.get_yaxis().set_visible(_UpperCamelCase					)
      plt.show()





def  __lowerCamelCase       (      ):


      '''simple docstring'''


      UpperCAmelCase_            =  datetime.now()
      UpperCAmelCase_            =  current_time.strftime('''%H:%M:%S'''					)
      return timestamp





