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


snake_case :		Any							      =  logging.get_logger(__name__)

snake_case :		Optional[int]							      =  {
    "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}





class       _snake_case					(     snake_case				):
			UpperCamelCase__          =    'gpt_neox'







			def __init__(				self						,   _a=50_432						,   _a=6_144						,   _a=44						,   _a=64						,   _a=24_576						,   _a="gelu"						,   _a=0.25						,   _a=10_000						,   _a=0.0						,   _a=0.0						,   _a=0.1						,   _a=2_048						,   _a=0.02						,   _a=1e-5						,   _a=True						,   _a=0						,   _a=2						,   _a=False						,   _a=True						,   _a=None						,   **_a						,   ):
				super().__init__(bos_token_id=_a						,   eos_token_id=_a						,   **_a		)
				__magic_name__		:		List[Any]	   =     vocab_size
				__magic_name__		:		List[Any]	   =     max_position_embeddings
				__magic_name__		:		Optional[Any]	   =     hidden_size
				__magic_name__		:		Union[str, Any]	   =     num_hidden_layers
				__magic_name__		:		Optional[Any]	   =     num_attention_heads
				__magic_name__		:		List[Any]	   =     intermediate_size
				__magic_name__		:		List[str]	   =     hidden_act
				__magic_name__		:		Union[str, Any]	   =     rotary_pct
				__magic_name__		:		Any	   =     rotary_emb_base
				__magic_name__		:		int	   =     attention_dropout
				__magic_name__		:		Optional[int]	   =     hidden_dropout
				__magic_name__		:		List[str]	   =     classifier_dropout
				__magic_name__		:		List[Any]	   =     initializer_range
				__magic_name__		:		str	   =     layer_norm_eps
				__magic_name__		:		Optional[int]	   =     use_cache
				__magic_name__		:		Any	   =     tie_word_embeddings
				__magic_name__		:		Optional[Any]	   =     use_parallel_residual
				__magic_name__		:		Dict	   =     rope_scaling
				self._rope_scaling_validation()

				if self.hidden_size % self.num_attention_heads != 0:
					raise ValueError(
					    "The hidden size is not divisble by the number of attention heads! Make sure to update them!"		)







			def 			SCREAMING_SNAKE_CASE    (				self		):
				if self.rope_scaling is None:
					return

				if not isinstance(self.rope_scaling						,   _a		) or len(self.rope_scaling		) != 2:
					raise ValueError(
					    "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
					    f'''got {self.rope_scaling}'''		)
				__magic_name__		:		Dict	   =     self.rope_scaling.get("type"						,   _a		)
				__magic_name__		:		int	   =     self.rope_scaling.get("factor"						,   _a		)
				if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
					raise ValueError(
					    f'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''		)
				if rope_scaling_factor is None or not isinstance(_a						,   _a		) or rope_scaling_factor <= 1.0:
					raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''		)


def   lowerCAmelCase_						(					_snake_case      :  str      ,   _snake_case      :  str   )				->		bool:







	'''simple docstring'''


	__magic_name__		:		Union[str, Any]	   =     len(_snake_case   ) + 1
	__magic_name__		:		List[str]	   =     len(_snake_case   ) + 1

	# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
	# length i of input_string matches with prefix string of length j of
	# given pattern.
	# "dp" stands for dynamic programming.
	__magic_name__		:		str	   =     [[0 for i in range(_snake_case   )] for j in range(_snake_case   )]

	# since string of zero length match pattern of zero length
	__magic_name__		:		Optional[int]	   =     1

	# since pattern of zero length will never match with string of non-zero length
	for i in range(1      ,   _snake_case   ):
		__magic_name__		:		Optional[int]	   =     0

	# since string of zero length will match with pattern where there
	# is at least one * alternatively
	for j in range(1      ,   _snake_case   ):
		__magic_name__		:		Union[str, Any]	   =     dp[0][j - 2] if pattern[j - 1] == "*" else 0

	# now using bottom-up approach to find for all remaining lengths
	for i in range(1      ,   _snake_case   ):
		for j in range(1      ,   _snake_case   ):
			if input_string[i - 1] == pattern[j - 1] or pattern[j - 1] == ".":
				__magic_name__		:		Optional[int]	   =     dp[i - 1][j - 1]

			elif pattern[j - 1] == "*":
				if dp[i][j - 2] == 1:
					__magic_name__		:		Optional[Any]	   =     1
				elif pattern[j - 2] in (input_string[i - 1], "."):
					__magic_name__		:		List[Any]	   =     dp[i - 1][j]
				else:
					__magic_name__		:		Union[str, Any]	   =     0
			else:
				__magic_name__		:		Dict	   =     0

	return bool(dp[-1][-1]   )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				# inputing the strings
				# input_string = input("input a string :")
				# pattern = input("input a pattern :")

				snake_case :		Optional[Any]							      =  "aab"
				snake_case :		List[str]							      =  "c*a*b"

				# using function to check whether given string matches the given pattern
				if match_pattern(input_string, pattern):
								print(F"{input_string} matches the given pattern {pattern}")
				else:
								print(F"{input_string} does not match with the given pattern {pattern}")
