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


lowercase    :   Optional[int]		       =				logging.get_logger(__name__)

lowercase    :   Union[str, Any]		       =				{"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}

class __snake_case						( __snake_case	):
    _a						:		Optional[int]=							"openai-gpt"
    _a						:		int=							{
        "max_position_embeddings": "n_positions",
        "hidden_size": "n_embd",
        "num_attention_heads": "n_head",
        "num_hidden_layers": "n_layer",
    }
    def __init__(    self						,snake_case=40478						,snake_case=512						,snake_case=768						,snake_case=12						,snake_case=12						,snake_case="gelu"						,snake_case=0.1						,snake_case=0.1						,snake_case=0.1						,snake_case=1e-5						,snake_case=0.02						,snake_case="cls_index"						,snake_case=True						,snake_case=None						,snake_case=True						,snake_case=0.1						,**snake_case						,):



           '''simple docstring'''







           lowercase				:	Optional[int]			      = vocab_size
           lowercase				:	List[str]			      = n_positions
           lowercase				:	Union[str, Any]			      = n_embd
           lowercase				:	Tuple			      = n_layer
           lowercase				:	Tuple			      = n_head
           lowercase				:	Any			      = afn
           lowercase				:	Any			      = resid_pdrop
           lowercase				:	Union[str, Any]			      = embd_pdrop
           lowercase				:	int			      = attn_pdrop
           lowercase				:	Tuple			      = layer_norm_epsilon
           lowercase				:	Union[str, Any]			      = initializer_range
           lowercase				:	str			      = summary_type
           lowercase				:	Tuple			      = summary_use_proj
           lowercase				:	str			      = summary_activation
           lowercase				:	int			      = summary_first_dropout
           lowercase				:	str			      = summary_proj_to_labels
           super().__init__(**snake_case_ )







__A							:			Dict         =			"Alexander Joslin"

import operator as op

from .stack import Stack





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




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

    _A     =							Stack()
    _A     =							Stack()

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

            _A     =							operators[opr](_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)
            operand_stack.push(_SCREAMING_SNAKE_CASE				)

    # RULE 5
    return operand_stack.peek()


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





