

'''simple docstring'''





import operator as op




def 					_lowercase     (				a_				:					Any				)				->	List[Any]:




					'''simple docstring'''







					__magic_name__							=    []
					__magic_name__							=    lambda a_					,a_				: int(x / y				)  # noqa: E731 integer division operation
					__magic_name__							=    {
					    '^': op.pow,
					    '*': op.mul,
					    '/': div,
					    '+': op.add,
					    '-': op.sub,
					}  # operators & their respective operation

					# print table header
					print('Symbol'.center(8				)					,'Action'.center(1_2				)					,'Stack'					,sep=' | '				)
					print('-' * (3_0 + len(a_				))				)

					for x in post_fix:
										if x.isdigit():  # if x in digit
															stack.append(a_				)  # append x to stack
															# output in tabular format
															print(x.rjust(8				)					,('push(' + x + ')').ljust(1_2				)					,','.join(a_				)					,sep=' | '				)
										else:
															__magic_name__							=    stack.pop()  # pop stack
															# output in tabular format
															print(''.rjust(8				)					,('pop(' + b + ')').ljust(1_2				)					,','.join(a_				)					,sep=' | '				)

															__magic_name__							=    stack.pop()  # pop stack
															# output in tabular format
															print(''.rjust(8				)					,('pop(' + a + ')').ljust(1_2				)					,','.join(a_				)					,sep=' | '				)

															stack.append(
															    str(opr[x](int(a_				)					,int(a_				)				)				)				)  # evaluate the 2 values popped from stack & push result to stack
															# output in tabular format
															print(
															    x.rjust(8				)					,('push(' + a + x + b + ')').ljust(1_2				)					,','.join(a_				)					,sep=' | '					,)

					return int(stack[0]				)


if __name__ == "__main__":
						A__						=							input("\n\nEnter a Postfix Equation (space separated) = ").split(" ")
						print("\n\tResult = ", solve(Postfix))







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A__						=							logging.get_logger(__name__)

A__						=							{
    "camembert-base": "https://huggingface.co/camembert-base/resolve/main/config.json",
    "umberto-commoncrawl-cased-v1": (
        "https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"
    ),
    "umberto-wikipedia-uncased-v1": (
        "https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"
    ),
}

class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):
	_lowercase  :   Optional[int]       				=  "camembert"







	def __init__(   self: Optional[Any]  , __UpperCamelCase: Any=3_05_22  , __UpperCamelCase: Tuple=7_68  , __UpperCamelCase: str=12  , __UpperCamelCase: Optional[int]=12  , __UpperCamelCase: List[str]=30_72  , __UpperCamelCase: Any="gelu"  , __UpperCamelCase: Optional[int]=0.1  , __UpperCamelCase: Any=0.1  , __UpperCamelCase: str=5_12  , __UpperCamelCase: Dict=2  , __UpperCamelCase: str=0.02  , __UpperCamelCase: List[Any]=1E-12  , __UpperCamelCase: List[Any]=1  , __UpperCamelCase: Any=0  , __UpperCamelCase: Union[str, Any]=2  , __UpperCamelCase: Dict="absolute"  , __UpperCamelCase: Any=True  , __UpperCamelCase: Any=None  , **__UpperCamelCase: Union[str, Any]  , ):

						'''simple docstring'''





						super().__init__(pad_token_id=__UpperCamelCase  , bos_token_id=__UpperCamelCase  , eos_token_id=__UpperCamelCase  , **__UpperCamelCase      )

						__magic_name__							=    vocab_size
						__magic_name__							=    hidden_size
						__magic_name__							=    num_hidden_layers
						__magic_name__							=    num_attention_heads
						__magic_name__							=    hidden_act
						__magic_name__							=    intermediate_size
						__magic_name__							=    hidden_dropout_prob
						__magic_name__							=    attention_probs_dropout_prob
						__magic_name__							=    max_position_embeddings
						__magic_name__							=    type_vocab_size
						__magic_name__							=    initializer_range
						__magic_name__							=    layer_norm_eps
						__magic_name__							=    position_embedding_type
						__magic_name__							=    use_cache
						__magic_name__							=    classifier_dropout




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						if self.task == "multiple-choice":
											__magic_name__							=    {0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
											__magic_name__							=    {0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ('input_ids', dynamic_axis),
						        ('attention_mask', dynamic_axis),
						    ]      )




