
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase											=    logging.get_logger(__name__)

_lowercase											=    {
    """tiiuae/falcon-40b""": """https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json""",
    """tiiuae/falcon-7b""": """https://huggingface.co/tiiuae/falcon-7b/resolve/main/config.json""",
}


class 			lowercase_		(      A       ):
       __lowerCamelCase				       =						"falcon"
       __lowerCamelCase				       =						["past_key_values"]


       def __init__(    self						,       __A=65_024						,       __A=4_544						,       __A=32						,       __A=71						,       __A=1e-5						,       __A=0.02						,       __A=True						,       __A=0.0						,       __A=0.0						,       __A=None						,       __A=False						,       __A=False						,       __A=True						,       __A=True						,       __A=False						,       __A=11						,       __A=11						,       **__A						,       )						->    Optional[int]:
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=vocab_size
              # Backward compatibility with n_embed kwarg
              SCREAMING_SNAKE_CASE_							:				Optional[Any]		=kwargs.pop('''n_embed'''						,       __A				)
              SCREAMING_SNAKE_CASE_							:				Tuple		=hidden_size if n_embed is None else n_embed
              SCREAMING_SNAKE_CASE_							:				Any		=num_hidden_layers
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=num_attention_heads
              SCREAMING_SNAKE_CASE_							:				List[str]		=layer_norm_epsilon
              SCREAMING_SNAKE_CASE_							:				List[str]		=initializer_range
              SCREAMING_SNAKE_CASE_							:				Optional[Any]		=use_cache
              SCREAMING_SNAKE_CASE_							:				Dict		=hidden_dropout
              SCREAMING_SNAKE_CASE_							:				List[Any]		=attention_dropout

              SCREAMING_SNAKE_CASE_							:				Any		=bos_token_id
              SCREAMING_SNAKE_CASE_							:				List[Any]		=eos_token_id
              SCREAMING_SNAKE_CASE_							:				List[str]		=num_attention_heads if num_kv_heads is None else num_kv_heads
              SCREAMING_SNAKE_CASE_							:				Tuple		=alibi
              SCREAMING_SNAKE_CASE_							:				str		=new_decoder_architecture
              SCREAMING_SNAKE_CASE_							:				List[str]		=multi_query  # Ignored when new_decoder_architecture is True
              SCREAMING_SNAKE_CASE_							:				str		=parallel_attn
              SCREAMING_SNAKE_CASE_							:				Any		=bias

              super().__init__(bos_token_id=__A						,       eos_token_id=__A						,       **__A				)


       @property
       def 	_snake_case				(    self				)						->    Optional[int]:
              return self.hidden_size // self.num_attention_heads





       @property
       def 	_snake_case				(    self				)						->    Optional[Any]:
              return not self.alibi


from collections.abc import Sequence
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     Sequence[int] | None = None				)			->						int:
       if nums is None or not nums:
              raise ValueError('''Input sequence should not be empty'''				)

       SCREAMING_SNAKE_CASE_							:				Tuple		=nums[0]
       for i in range(1			,							len(UpperCAmelCase_				)				):
              SCREAMING_SNAKE_CASE_							:				Any		=nums[i]
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=max(UpperCAmelCase_			,							ans + num			,							UpperCAmelCase_				)

       return ans


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 # Try on a sample input from the user
 _lowercase											=    int(input("""Enter number of elements : """).strip())
 _lowercase											=    list(map(int, input("""\nEnter the numbers : """).strip().split()))[:n]
 print(max_subsequence_sum(array))
