from __future__ import annotations







def 						UpperCAmelCase							(		lowerCAmelCase_							)						->						list[int]:
     a	:     str						      =    [0] * max_one

     for i in range(0    ,   lowerCAmelCase_							):
          a	:     List[Any]						      =    i

     for i in range(2    ,   lowerCAmelCase_							):
          if totients[i] == i:
               for j in range(lowerCAmelCase_    ,   lowerCAmelCase_    ,   lowerCAmelCase_							):
                    totients[j] -= totients[j] // i

     return totients







def 						UpperCAmelCase							(		lowerCAmelCase_    ,   lowerCAmelCase_							)						->						bool:
     return sorted(str(lowerCAmelCase_							)							) == sorted(str(lowerCAmelCase_							)							)







def 						UpperCAmelCase							(		lowerCAmelCase_ = 1_0_0_0_0_0_0_0							)						->						int:
     a	:     Dict						      =    1  # i
     a	:     Tuple						      =    0  # φ(i)
     a	:     Any						      =    get_totients(max_n + 1							)

     for i in range(2    ,   max_n + 1							):
          a	:     str						      =    totients[i]

          if i * min_denominator < min_numerator * t and has_same_digits(lowerCAmelCase_    ,   lowerCAmelCase_							):
               a	:     List[str]						      =    i
               a	:     str						      =    t

     return min_numerator


if __name__ == "__main__":
  print(F'''{solution() = }''')
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase				 =   logging.get_logger(__name__)

UpperCAmelCase				 =   {
    """facebook/opt-125m""": """https://huggingface.co/facebook/opt-125m/blob/main/config.json""",
    """facebook/opt-350m""": """https://huggingface.co/facebook/opt-350m/blob/main/config.json""",
    """facebook/opt-1.3b""": """https://huggingface.co/facebook/opt-1.3b/blob/main/config.json""",
    """facebook/opt-2.7b""": """https://huggingface.co/facebook/opt-2.7b/blob/main/config.json""",
    """facebook/opt-6.7b""": """https://huggingface.co/facebook/opt-6.7b/blob/main/config.json""",
    """facebook/opt-13b""": """https://huggingface.co/facebook/opt-13b/blob/main/config.json""",
}






class 				_SCREAMING_SNAKE_CASE( snake_case__						):
   UpperCamelCase_					:    List[str]			      = 'opt'
   UpperCamelCase_					:    List[str]			      = ['past_key_values']
   def __init__(     self				,  lowerCAmelCase_=5_02_72				,  lowerCAmelCase_=7_68				,  lowerCAmelCase_=12				,  lowerCAmelCase_=30_72				,  lowerCAmelCase_=20_48				,  lowerCAmelCase_=True				,  lowerCAmelCase_=False				,  lowerCAmelCase_=None				,  lowerCAmelCase_=0.1				,  lowerCAmelCase_=0.0				,  lowerCAmelCase_=12				,  lowerCAmelCase_="relu"				,  lowerCAmelCase_=0.0				,  lowerCAmelCase_=0.02				,  lowerCAmelCase_=True				,  lowerCAmelCase_=1				,  lowerCAmelCase_=2				,  lowerCAmelCase_=2				,  lowerCAmelCase_=True				,  lowerCAmelCase_=True				,  **lowerCAmelCase_				,  )						->Any:
        super().__init__(
            pad_token_id=lowerCAmelCase_				,  bos_token_id=lowerCAmelCase_				,  eos_token_id=lowerCAmelCase_				,  **lowerCAmelCase_				,  )
        a	:     Dict						      =    vocab_size
        a	:     int						      =    max_position_embeddings
        a	:     List[Any]						      =    num_attention_heads
        a	:     Union[str, Any]						      =    word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
        a	:     Any						      =    ffn_dim
        a	:     Optional[int]						      =    hidden_size
        a	:     Optional[Any]						      =    num_hidden_layers
        a	:     Optional[int]						      =    dropout
        a	:     Optional[Any]						      =    attention_dropout
        a	:     Union[str, Any]						      =    activation_function
        a	:     Any						      =    init_std
        a	:     List[Any]						      =    layerdrop
        a	:     str						      =    use_cache
        a	:     Any						      =    do_layer_norm_before
        # We keep these variables at `True` for backward compatibility.
        a	:     List[Any]						      =    enable_bias
        a	:     List[str]						      =    layer_norm_elementwise_affine

        # Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
        # with checkpoints that have been fine-tuned before transformers v4.20.1
        # see https://github.com/facebookresearch/metaseq/pull/164
        a	:     Dict						      =    _remove_final_layer_norm