import warnings

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


snake_case      =    logging.get_logger(__name__)

snake_case      =    {
    'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}



class __A     (      _lowerCamelCase						):

							'''simple docstring'''

							a_     =					'''mvp'''
							a_     =					['''past_key_values''']
							a_     =					{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}






							def __init__(				self   ,	_snake_case=5_0267   ,	_snake_case=1024   ,	_snake_case=12   ,	_snake_case=4096   ,	_snake_case=16   ,	_snake_case=12   ,	_snake_case=4096   ,	_snake_case=16   ,	_snake_case=0.0   ,	_snake_case=0.0   ,	_snake_case="gelu"   ,	_snake_case=1024   ,	_snake_case=0.1   ,	_snake_case=0.0   ,	_snake_case=0.0   ,	_snake_case=0.02   ,	_snake_case=0.0   ,	_snake_case=False   ,	_snake_case=True   ,	_snake_case=1   ,	_snake_case=0   ,	_snake_case=2   ,	_snake_case=True   ,	_snake_case=2   ,	_snake_case=2   ,	_snake_case=False   ,	_snake_case=100   ,	_snake_case=800   ,	**_snake_case   ,	):
												_lowerCAmelCase			:		List[str]          = vocab_size
												_lowerCAmelCase			:		List[Any]          = max_position_embeddings
												_lowerCAmelCase			:		int          = d_model
												_lowerCAmelCase			:		List[str]          = encoder_ffn_dim
												_lowerCAmelCase			:		Union[str, Any]          = encoder_layers
												_lowerCAmelCase			:		Optional[int]          = encoder_attention_heads
												_lowerCAmelCase			:		List[str]          = decoder_ffn_dim
												_lowerCAmelCase			:		Any          = decoder_layers
												_lowerCAmelCase			:		str          = decoder_attention_heads
												_lowerCAmelCase			:		List[Any]          = dropout
												_lowerCAmelCase			:		List[Any]          = attention_dropout
												_lowerCAmelCase			:		Any          = activation_dropout
												_lowerCAmelCase			:		Optional[Any]          = activation_function
												_lowerCAmelCase			:		int          = init_std
												_lowerCAmelCase			:		Optional[Any]          = encoder_layerdrop
												_lowerCAmelCase			:		Any          = decoder_layerdrop
												_lowerCAmelCase			:		Dict          = classifier_dropout
												_lowerCAmelCase			:		List[str]          = use_cache
												_lowerCAmelCase			:		Tuple          = encoder_layers
												_lowerCAmelCase			:		int          = scale_embedding  # scale factor will be sqrt(d_model) if True
												_lowerCAmelCase			:		Optional[Any]          = use_prompt
												_lowerCAmelCase			:		Any          = prompt_length
												_lowerCAmelCase			:		int          = prompt_mid_dim

												super().__init__(
												    pad_token_id=lowercase_   ,	bos_token_id=lowercase_   ,	eos_token_id=lowercase_   ,	is_encoder_decoder=lowercase_   ,	decoder_start_token_id=lowercase_   ,	forced_eos_token_id=lowercase_   ,	**lowercase_   ,	)

												if self.forced_bos_token_id is None and kwargs.get("force_bos_token_to_be_generated"   ,	lowercase_ ):
																	_lowerCAmelCase			:		Optional[int]          = self.bos_token_id
																	warnings.warn(
																	    F"""Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. """
																	    "The config can simply be saved and uploaded again to be fixed." )












'''simple docstring'''

import operator as op


def 						__magic_name__       (      __UpperCAmelCase      )						->   Dict:

					'''simple docstring'''

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

					# print table header
					print('''Symbol'''.center(8      ), '''Action'''.center(12      ), '''Stack''', sep=''' | '''      )
					print('''-''' * (30 + len(__UpperCAmelCase      ))      )

					for x in post_fix:
										if x.isdigit():  # if x in digit
															stack.append(__UpperCAmelCase      )  # append x to stack
															# output in tabular format
															print(x.rjust(8      ), ('''push(''' + x + ''')''').ljust(12      ), ''','''.join(__UpperCAmelCase      ), sep=''' | '''      )
										else:
															snake_case_		     =							stack.pop()  # pop stack
															# output in tabular format
															print(''''''.rjust(8      ), ('''pop(''' + b + ''')''').ljust(12      ), ''','''.join(__UpperCAmelCase      ), sep=''' | '''      )

															snake_case_		     =							stack.pop()  # pop stack
															# output in tabular format
															print(''''''.rjust(8      ), ('''pop(''' + a + ''')''').ljust(12      ), ''','''.join(__UpperCAmelCase      ), sep=''' | '''      )

															stack.append(
															    str(opr[x](int(__UpperCAmelCase      ), int(__UpperCAmelCase      )      )      )      )  # evaluate the 2 values popped from stack & push result to stack
															# output in tabular format
															print(
															    x.rjust(8      ), ('''push(''' + a + x + b + ''')''').ljust(12      ), ''','''.join(__UpperCAmelCase      ), sep=''' | ''', )

					return int(stack[0]      )


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

