



"""simple docstring"""







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


UpperCamelCase     =							logging.get_logger(__name__)

UpperCamelCase     =							{
    """google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/config.json""",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}






class       UpperCamelCase__			(   _lowerCAmelCase      ):

			"""simple docstring"""


			A__	:					Union[str, Any]							  =     "canine"


			def __init__(      self						,	SCREAMING_SNAKE_CASE__=768						,	SCREAMING_SNAKE_CASE__=12						,	SCREAMING_SNAKE_CASE__=12						,	SCREAMING_SNAKE_CASE__=3072						,	SCREAMING_SNAKE_CASE__="gelu"						,	SCREAMING_SNAKE_CASE__=0.1						,	SCREAMING_SNAKE_CASE__=0.1						,	SCREAMING_SNAKE_CASE__=16384						,	SCREAMING_SNAKE_CASE__=16						,	SCREAMING_SNAKE_CASE__=0.0_2						,	SCREAMING_SNAKE_CASE__=1e-12						,	SCREAMING_SNAKE_CASE__=0						,	SCREAMING_SNAKE_CASE__=0xE000						,	SCREAMING_SNAKE_CASE__=0xE001						,	SCREAMING_SNAKE_CASE__=4						,	SCREAMING_SNAKE_CASE__=4						,	SCREAMING_SNAKE_CASE__=8						,	SCREAMING_SNAKE_CASE__=16384						,	SCREAMING_SNAKE_CASE__=128						,	**SCREAMING_SNAKE_CASE__						,	)      ->	Union[str, Any]:
				super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__						,	bos_token_id=SCREAMING_SNAKE_CASE__						,	eos_token_id=SCREAMING_SNAKE_CASE__						,	**SCREAMING_SNAKE_CASE__		)

				A__											=					max_position_embeddings
				A__											=					hidden_size
				A__											=					num_hidden_layers
				A__											=					num_attention_heads
				A__											=					intermediate_size
				A__											=					hidden_act
				A__											=					hidden_dropout_prob
				A__											=					attention_probs_dropout_prob
				A__											=					initializer_range
				A__											=					type_vocab_size
				A__											=					layer_norm_eps

				# Character config:
				A__											=					downsampling_rate
				A__											=					upsampling_kernel_size
				A__											=					num_hash_functions
				A__											=					num_hash_buckets
				A__											=					local_transformer_stride









"""simple docstring"""







def       _lowerCamelCase				(							UpperCAmelCase_ :       Optional[Any]     )	-> Dict:






	"""simple docstring"""





	A__											=					[]
	A__											=					set({"(", "[", "{"}     )
	A__											=					set({")", "]", "}"}     )
	A__											=					{"{": "}", "[": "]", "(": ")"}

	for i in range(len(UpperCAmelCase_     )     ):
		if s[i] in open_brackets:
			stack.append(s[i]     )

		elif s[i] in closed_brackets and (
		    len(UpperCAmelCase_     ) == 0 or (len(UpperCAmelCase_     ) > 0 and open_to_closed[stack.pop()] != s[i])
		):
			return False

	return len(UpperCAmelCase_     ) == 0

def       _lowerCamelCase				(							)	-> str:






	"""simple docstring"""





	A__											=					input("Enter sequence of brackets: "     )
	if is_balanced(UpperCAmelCase_     ):
		print(UpperCAmelCase_,	"is balanced"     )
	else:
		print(UpperCAmelCase_,	"is not balanced"     )


if __name__ == "__main__":
			main()




