
"""simple docstring"""







def    __lowerCAmelCase    (_UpperCamelCase		):
	__lowerCAmelCase      :						Optional[int]						      =				0

	# if input_string is "aba" than new_input_string become "a|b|a"
	__lowerCAmelCase      :						Union[str, Any]						      =				''
	__lowerCAmelCase      :						Tuple						      =				''

	# append each character + "|" in new_string for range(0, length-1)
	for i in input_string[: len(_UpperCamelCase		) - 1]:
		new_input_string += i + "|"
	# append last character
	new_input_string += input_string[-1]

	# we will store the starting and ending of previous furthest ending palindromic
	# substring
	__lowerCAmelCase      :						List[str]						      =				0, 0

	# length[i] shows the length of palindromic substring with center i
	__lowerCAmelCase      :						List[Any]						      =				[1 for i in range(len(_UpperCamelCase		)		)]

	# for each character in new_string find corresponding palindromic string
	__lowerCAmelCase      :						Optional[int]						      =				0
	for j in range(len(_UpperCamelCase		)		):
		__lowerCAmelCase      :						int						      =				1 if j > r else min(length[l + r - j] // 2	,  r - j + 1		)
		while (
		    j - k >= 0
		    and j + k < len(_UpperCamelCase		)
		    and new_input_string[k + j] == new_input_string[j - k]
		):
			k += 1

		__lowerCAmelCase      :						List[str]						      =				2 * k - 1

		# does this string is ending after the previously explored end (that is r) ?
		# if yes the update the new r to the last index of this
		if j + k - 1 > r:
			__lowerCAmelCase      :						str						      =				j - k + 1  # noqa: E741
			__lowerCAmelCase      :						Optional[int]						      =				j + k - 1

		# update max_length and start position
		if max_length < length[j]:
			__lowerCAmelCase      :						Optional[Any]						      =				length[j]
			__lowerCAmelCase      :						List[Any]						      =				j

    # create that string
	__lowerCAmelCase      :						Optional[Any]						      =				new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
	for i in s:
		if i != "|":
			output_string += i

	return output_string


if __name__ == "__main__":
							import doctest

							doctest.testmod()

"""simple docstring"""







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


lowerCamelCase__        =		logging.get_logger(__name__)

lowerCamelCase__        =		{
    """facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}




class 			A__	(     _lowerCamelCase):
		A_						:	str           =     'nllb-moe'
		A_						:	Optional[Any]           =     ['past_key_values']
		A_						:	List[str]           =     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}

		def __init__(				self	,		_SCREAMING_SNAKE_CASE=12_81_12	,		_SCREAMING_SNAKE_CASE=10_24	,		_SCREAMING_SNAKE_CASE=12	,		_SCREAMING_SNAKE_CASE=40_96	,		_SCREAMING_SNAKE_CASE=16	,		_SCREAMING_SNAKE_CASE=12	,		_SCREAMING_SNAKE_CASE=40_96	,		_SCREAMING_SNAKE_CASE=16	,		_SCREAMING_SNAKE_CASE=0.05	,		_SCREAMING_SNAKE_CASE=0.05	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE="relu"	,		_SCREAMING_SNAKE_CASE=10_24	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=0.0	,		_SCREAMING_SNAKE_CASE=0.02	,		_SCREAMING_SNAKE_CASE=2	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE="float32"	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=1_28	,		_SCREAMING_SNAKE_CASE=64	,		_SCREAMING_SNAKE_CASE=4	,		_SCREAMING_SNAKE_CASE=4	,		_SCREAMING_SNAKE_CASE=0.001	,		_SCREAMING_SNAKE_CASE=0.001	,		_SCREAMING_SNAKE_CASE="all"	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=1.0	,		_SCREAMING_SNAKE_CASE=0.2	,		_SCREAMING_SNAKE_CASE=1	,		_SCREAMING_SNAKE_CASE=0	,		_SCREAMING_SNAKE_CASE=2	,		_SCREAMING_SNAKE_CASE=False	,		**_SCREAMING_SNAKE_CASE	,		):
			__lowerCAmelCase      :						int						      =				vocab_size
			__lowerCAmelCase      :						str						      =				max_position_embeddings
			__lowerCAmelCase      :						Dict						      =				d_model
			__lowerCAmelCase      :						Tuple						      =				encoder_ffn_dim
			__lowerCAmelCase      :						Optional[Any]						      =				encoder_layers
			__lowerCAmelCase      :						Any						      =				encoder_attention_heads
			__lowerCAmelCase      :						Tuple						      =				decoder_ffn_dim
			__lowerCAmelCase      :						Dict						      =				decoder_layers
			__lowerCAmelCase      :						str						      =				decoder_attention_heads
			__lowerCAmelCase      :						str						      =				dropout
			__lowerCAmelCase      :						List[str]						      =				attention_dropout
			__lowerCAmelCase      :						Optional[int]						      =				activation_dropout
			__lowerCAmelCase      :						List[Any]						      =				activation_function
			__lowerCAmelCase      :						List[str]						      =				init_std
			__lowerCAmelCase      :						Union[str, Any]						      =				encoder_layerdrop
			__lowerCAmelCase      :						List[Any]						      =				decoder_layerdrop
			__lowerCAmelCase      :						Optional[int]						      =				use_cache
			__lowerCAmelCase      :						Optional[Any]						      =				encoder_layers
			__lowerCAmelCase      :						Optional[int]						      =				scale_embedding  # scale factor will be sqrt(d_model) if True
			__lowerCAmelCase      :						Union[str, Any]						      =				router_z_loss_coef
			__lowerCAmelCase      :						Optional[Any]						      =				router_aux_loss_coef
			__lowerCAmelCase      :						int						      =				decoder_sparse_step
			__lowerCAmelCase      :						str						      =				encoder_sparse_step
			__lowerCAmelCase      :						Tuple						      =				num_experts
			__lowerCAmelCase      :						Dict						      =				expert_capacity
			__lowerCAmelCase      :						Union[str, Any]						      =				router_bias
			if router_dtype not in ["float32", "float16", "bfloat16"]:
				raise ValueError(f"`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}"			)
			__lowerCAmelCase      :						Union[str, Any]						      =				router_dtype

			__lowerCAmelCase      :						Any						      =				router_ignore_padding_tokens
			__lowerCAmelCase      :						str						      =				batch_prioritized_routing
			__lowerCAmelCase      :						Tuple						      =				second_expert_policy
			__lowerCAmelCase      :						List[str]						      =				normalize_router_prob_before_dropping
			__lowerCAmelCase      :						Dict						      =				moe_eval_capacity_token_fraction
			__lowerCAmelCase      :						Union[str, Any]						      =				moe_token_dropout
			__lowerCAmelCase      :						List[Any]						      =				output_router_logits
			super().__init__(
			    pad_token_id=_SCREAMING_SNAKE_CASE	,		bos_token_id=_SCREAMING_SNAKE_CASE	,		eos_token_id=_SCREAMING_SNAKE_CASE	,		is_encoder_decoder=_SCREAMING_SNAKE_CASE	,		decoder_start_token_id=_SCREAMING_SNAKE_CASE	,		**_SCREAMING_SNAKE_CASE	,		)