




def       UpperCAmelCase       (     _snake_case						, _snake_case							):
							lowerCAmelCase   =		len(_snake_case							) + 1
							lowerCAmelCase   =		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.
							lowerCAmelCase   =		[[0 for i in range(_snake_case							)] for j in range(_snake_case							)]

							# since string of zero length match pattern of zero length
							lowerCAmelCase   =		1

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

							# since string of zero length will match with pattern where there
							# is at least one * alternatively
							for j in range(1						, _snake_case							):
														lowerCAmelCase   =		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] == ".":
																												lowerCAmelCase   =		dp[i - 1][j - 1]

																					elif pattern[j - 1] == "*":
																												if dp[i][j - 2] == 1:
																																			lowerCAmelCase   =		1
																												elif pattern[j - 2] in (input_string[i - 1], "."):
																																			lowerCAmelCase   =		dp[i - 1][j]
																												else:
																																			lowerCAmelCase   =		0
																					else:
																												lowerCAmelCase   =		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 :")

		UpperCAmelCase_						="""aab"""
		UpperCAmelCase_						="""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}''')









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


UpperCAmelCase_						=logging.get_logger(__name__)

UpperCAmelCase_						={
    """google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}


class 							__UpperCamelCase			( __UpperCAmelCase  ):





				'''simple docstring'''



				__a							: Any										="""switch_transformers"""
				__a							: Union[str, Any]										=["""past_key_values"""]
				__a							: Dict										={"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}



				def __init__( self       , UpperCAmelCase_=3_21_28       , UpperCAmelCase_=7_68       , UpperCAmelCase_=64       , UpperCAmelCase_=20_48       , UpperCAmelCase_=64       , UpperCAmelCase_=12       , UpperCAmelCase_=3       , UpperCAmelCase_=12       , UpperCAmelCase_=3       , UpperCAmelCase_=12       , UpperCAmelCase_=8       , UpperCAmelCase_=False       , UpperCAmelCase_=0.01       , UpperCAmelCase_="float32"       , UpperCAmelCase_=False       , UpperCAmelCase_=32       , UpperCAmelCase_=1_28       , UpperCAmelCase_=0.1       , UpperCAmelCase_=1E-6       , UpperCAmelCase_=0.001       , UpperCAmelCase_=0.001       , UpperCAmelCase_=1.0       , UpperCAmelCase_="relu"       , UpperCAmelCase_=True       , UpperCAmelCase_=False       , UpperCAmelCase_=True       , UpperCAmelCase_=0       , UpperCAmelCase_=1       , **UpperCAmelCase_       , ):
											lowerCAmelCase   =		vocab_size
											lowerCAmelCase   =		d_model
											lowerCAmelCase   =		d_kv
											lowerCAmelCase   =		d_ff

											lowerCAmelCase   =		num_sparse_encoder_layers

											lowerCAmelCase   =		num_layers
											lowerCAmelCase   =		(
											    num_decoder_layers if num_decoder_layers is not None else self.num_layers
											)  # default = symmetry
											lowerCAmelCase   =		num_sparse_decoder_layers

											# This tells us, each how many encoder layer we'll have to set a sparse layer.
											if self.num_sparse_encoder_layers > 0:
																		lowerCAmelCase   =		self.num_layers // self.num_sparse_encoder_layers
											else:
																		lowerCAmelCase   =		self.num_layers  # HACK: this will create 0 sparse layers

											# This tells us, each how many encoder layer we'll have to set a sparse layer.
											if self.num_sparse_decoder_layers > 0:
																		lowerCAmelCase   =		self.num_decoder_layers // self.num_sparse_decoder_layers
											else:
																		lowerCAmelCase   =		self.num_decoder_layers  # HACK: this will create 0 sparse layers

											lowerCAmelCase   =		num_heads
											lowerCAmelCase   =		num_experts
											lowerCAmelCase   =		expert_capacity
											lowerCAmelCase   =		router_bias
											lowerCAmelCase   =		router_jitter_noise
											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   =		router_dtype

											lowerCAmelCase   =		router_ignore_padding_tokens
											lowerCAmelCase   =		relative_attention_num_buckets
											lowerCAmelCase   =		relative_attention_max_distance

											lowerCAmelCase   =		dropout_rate
											lowerCAmelCase   =		layer_norm_epsilon
											lowerCAmelCase   =		initializer_factor
											lowerCAmelCase   =		feed_forward_proj
											lowerCAmelCase   =		use_cache
											lowerCAmelCase   =		add_router_probs

											lowerCAmelCase   =		router_z_loss_coef
											lowerCAmelCase   =		router_aux_loss_coef

											lowerCAmelCase   =		self.feed_forward_proj.split('''-'''						)
											lowerCAmelCase   =		act_info[-1]
											lowerCAmelCase   =		act_info[0] == '''gated'''

											if len(UpperCAmelCase_						) > 1 and act_info[0] != "gated" or len(UpperCAmelCase_						) > 2:
																		raise ValueError(
																		    F"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
																		    '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
																		    '''\'gated-gelu\' or \'relu\''''						)

											# for backwards compatibility
											if feed_forward_proj == "gated-gelu":
																		lowerCAmelCase   =		'''gelu_new'''

											super().__init__(
											    pad_token_id=UpperCAmelCase_       , eos_token_id=UpperCAmelCase_       , is_encoder_decoder=UpperCAmelCase_       , **UpperCAmelCase_       , )



