



'''simple docstring'''





from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
_lowerCAmelCase      						=	HfArgumentParser(InitializationArguments)
_lowerCAmelCase      						=	parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
_lowerCAmelCase      						=	AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
_lowerCAmelCase      						=	{
    '''vocab_size''': len(tokenizer),
    '''scale_attn_by_inverse_layer_idx''': True,
    '''reorder_and_upcast_attn''': True,
}

# Load model config (GPT-2 large in this case)
_lowerCAmelCase      						=	AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
_lowerCAmelCase      						=	AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)






def    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       if number < 0 or shift_amount < 0:
              raise ValueError('both inputs must be positive integers'     )

       lowercase__:   str  			=   str(bin(snake_case     )     )
       binary_number += "0" * shift_amount
       return binary_number




def    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       if number < 0 or shift_amount < 0:
              raise ValueError('both inputs must be positive integers'     )

       lowercase__:   Optional[Any]  			=   str(bin(snake_case     )     )[2:]
       if shift_amount >= len(snake_case     ):
              return "0b0"
       lowercase__:   Optional[int]  			=   binary_number[: len(snake_case     ) - shift_amount]
       return "0b" + shifted_binary_number




def    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       if number >= 0:  # Get binary representation of positive number
              lowercase__:   Union[str, Any]  			=   '0' + str(bin(snake_case     )     ).strip('-'     )[2:]
       else:  # Get binary (2's complement) representation of negative number
              lowercase__:   Dict  			=   len(bin(snake_case     )[3:]     )  # Find 2's complement of number
              lowercase__:   int  			=   bin(abs(snake_case     ) - (1 << binary_number_length)     )[3:]
              lowercase__:   Any  			=   (
                  '1' + '0' * (binary_number_length - len(snake_case     )) + binary_number
              )

       if shift_amount >= len(snake_case     ):
              return "0b" + binary_number[0] * len(snake_case     )
       return (
           "0b"
           + binary_number[0] * shift_amount
           + binary_number[: len(snake_case     ) - shift_amount]
       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()


