from collections import OrderedDict
from typing import Mapping

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


snake_case      =    logging.get_logger(__name__)

snake_case      =    {
    'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json',
    'xlm-mlm-ende-1024': 'https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json',
    'xlm-mlm-enfr-1024': 'https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json',
    'xlm-mlm-enro-1024': 'https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json',
    'xlm-mlm-tlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json',
    'xlm-mlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json',
    'xlm-clm-enfr-1024': 'https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json',
    'xlm-clm-ende-1024': 'https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json',
    'xlm-mlm-17-1280': 'https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json',
    'xlm-mlm-100-1280': 'https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json',
}



class __A     (      _lowerCamelCase						):

							'''simple docstring'''

							a_     =					'''xlm'''
							a_     =					{
							    '''hidden_size''': '''emb_dim''',
							    '''num_attention_heads''': '''n_heads''',
							    '''num_hidden_layers''': '''n_layers''',
							    '''n_words''': '''vocab_size''',  # For backward compatibility
							}






							def __init__(				self   ,	_snake_case=3_0145   ,	_snake_case=2048   ,	_snake_case=12   ,	_snake_case=16   ,	_snake_case=0.1   ,	_snake_case=0.1   ,	_snake_case=True   ,	_snake_case=False   ,	_snake_case=False   ,	_snake_case=False   ,	_snake_case=1   ,	_snake_case=True   ,	_snake_case=512   ,	_snake_case=2048**-0.5   ,	_snake_case=1E-1_2   ,	_snake_case=0.02   ,	_snake_case=0   ,	_snake_case=1   ,	_snake_case=2   ,	_snake_case=3   ,	_snake_case=5   ,	_snake_case=True   ,	_snake_case="first"   ,	_snake_case=True   ,	_snake_case=None   ,	_snake_case=True   ,	_snake_case=0.1   ,	_snake_case=5   ,	_snake_case=5   ,	_snake_case=0   ,	_snake_case=0   ,	_snake_case=2   ,	_snake_case=0   ,	**_snake_case   ,	):
												_lowerCAmelCase			:		Optional[int]          = vocab_size
												_lowerCAmelCase			:		List[str]          = emb_dim
												_lowerCAmelCase			:		List[Any]          = n_layers
												_lowerCAmelCase			:		Optional[Any]          = n_heads
												_lowerCAmelCase			:		int          = dropout
												_lowerCAmelCase			:		List[str]          = attention_dropout
												_lowerCAmelCase			:		Optional[int]          = gelu_activation
												_lowerCAmelCase			:		Optional[Any]          = sinusoidal_embeddings
												_lowerCAmelCase			:		Tuple          = causal
												_lowerCAmelCase			:		Dict          = asm
												_lowerCAmelCase			:		Union[str, Any]          = n_langs
												_lowerCAmelCase			:		Any          = use_lang_emb
												_lowerCAmelCase			:		Union[str, Any]          = layer_norm_eps
												_lowerCAmelCase			:		Optional[int]          = bos_index
												_lowerCAmelCase			:		str          = eos_index
												_lowerCAmelCase			:		int          = pad_index
												_lowerCAmelCase			:		List[Any]          = unk_index
												_lowerCAmelCase			:		Optional[Any]          = mask_index
												_lowerCAmelCase			:		Tuple          = is_encoder
												_lowerCAmelCase			:		List[str]          = max_position_embeddings
												_lowerCAmelCase			:		Optional[Any]          = embed_init_std
												_lowerCAmelCase			:		Union[str, Any]          = init_std
												_lowerCAmelCase			:		int          = summary_type
												_lowerCAmelCase			:		Tuple          = summary_use_proj
												_lowerCAmelCase			:		Union[str, Any]          = summary_activation
												_lowerCAmelCase			:		Any          = summary_proj_to_labels
												_lowerCAmelCase			:		Optional[Any]          = summary_first_dropout
												_lowerCAmelCase			:		str          = start_n_top
												_lowerCAmelCase			:		Union[str, Any]          = end_n_top
												_lowerCAmelCase			:		Any          = mask_token_id
												_lowerCAmelCase			:		Optional[int]          = lang_id

												if "n_words" in kwargs:
																	_lowerCAmelCase			:		Any          = kwargs["n_words"]

												super().__init__(pad_token_id=lowercase_   ,	bos_token_id=lowercase_   ,	**lowercase_ )



class __A     (      _lowerCamelCase						):

							'''simple docstring'''

							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												if self.task == "multiple-choice":
																	_lowerCAmelCase			:		Union[str, Any]          = {0: "batch", 1: "choice", 2: "sequence"}
												else:
																	_lowerCAmelCase			:		Union[str, Any]          = {0: "batch", 1: "sequence"}
												return OrderedDict(
												    [
												        ("input_ids", dynamic_axis),
												        ("attention_mask", dynamic_axis),
												        ("token_type_ids", dynamic_axis),
												    ] )












'''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))

