

_UpperCAmelCase		:       Optional[Any]						    =	"""Alexander Joslin"""

import operator as op

from .stack import Stack





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}

							snake_case_          =   Stack()
							snake_case_          =   Stack()

							for i in equation:
														if i.isdigit():
																					# RULE 1
																					operand_stack.push(int(UpperCamelCase__				)				)
														elif i in operators:
																					# RULE 2
																					operator_stack.push(UpperCamelCase__				)
														elif i == ")":
																					# RULE 4
																					snake_case_          =   operator_stack.peek()
																					operator_stack.pop()
																					snake_case_          =   operand_stack.peek()
																					operand_stack.pop()
																					snake_case_          =   operand_stack.peek()
																					operand_stack.pop()

																					snake_case_          =   operators[opr](UpperCamelCase__       ,							UpperCamelCase__				)
																					operand_stack.push(UpperCamelCase__				)

    # RULE 5
							return operand_stack.peek()


if __name__ == "__main__":
					_UpperCAmelCase		:       Any						    =	"""(5 + ((4 * 2) * (2 + 3)))"""
					# answer = 45
					print(F'''{equation} = {dijkstras_two_stack_algorithm(equation)}''')







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


_UpperCAmelCase		:       str						    =	logging.get_logger(__name__)

_UpperCAmelCase		:       int						    =	{
    """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 			lowercase    (	lowercase_      ):
				__SCREAMING_SNAKE_CASE :			int	      =      '''canine'''




				def __init__( self				,       snake_case=768				,       snake_case=12				,       snake_case=12				,       snake_case=3072				,       snake_case="gelu"				,       snake_case=0.1				,       snake_case=0.1				,       snake_case=1_6384				,       snake_case=16				,       snake_case=0.02				,       snake_case=1e-1_2				,       snake_case=0				,       snake_case=0xE000				,       snake_case=0xE001				,       snake_case=4				,       snake_case=4				,       snake_case=8				,       snake_case=1_6384				,       snake_case=128				,       **snake_case				,       ):
											super().__init__(pad_token_id=snake_case				,       bos_token_id=snake_case				,       eos_token_id=snake_case				,       **snake_case	)

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

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




