import math
from collections import OrderedDict

import torch
from packaging import version
from torch import Tensor, nn

from .utils import logging


a     :			Union[str, Any]					    =						logging.get_logger(__name__)

class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def __init__(						self   ):
       super().__init__()
       if version.parse(torch.__version__   ) < version.parse("1.12.0"   ):
          raise ImportError(
              F'''You are using torch=={torch.__version__}, but torch>=1.12.0 is required to use '''
              "PytorchGELUTanh. Please upgrade torch."   )




    def     _a						(						self					,	lowerCamelCase__   ):
       return nn.functional.gelu(lowerCamelCase__					,	approximate="tanh"   )





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__   ):
       return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi   ) * (input + 0.0_4_4_7_1_5 * torch.pow(lowerCamelCase__					,	3.0   ))   ))





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def __init__(						self					,	lowerCamelCase__ = False   ):
       super().__init__()
       if use_gelu_python:
          lowerCAmelCase_:       str         =  self._gelu_python
       else:
          lowerCAmelCase_:       Dict         =  nn.functional.gelu




    def     _a						(						self					,	lowerCamelCase__   ):
       return input * 0.5 * (1.0 + torch.erf(input / math.sqrt(2.0   )   ))




    def     _a						(						self					,	lowerCamelCase__   ):
       return self.act(lowerCamelCase__   )





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__   ):
       return 0.5 * input * (1.0 + torch.tanh(input * 0.7_9_7_8_8_4_5_6_0_8 * (1.0 + 0.0_4_4_7_1_5 * input * input)   ))





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__   ):
       return input * torch.sigmoid(1.7_0_2 * input   )





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def __init__(						self					,	lowerCamelCase__					,	lowerCamelCase__   ):
       if min > max:
          raise ValueError(F'''min should be < max (got min: {min}, max: {max})'''   )

       super().__init__()
       lowerCAmelCase_:       str         =  min
       lowerCAmelCase_:       List[Any]         =  max




    def     _a						(						self					,	lowerCamelCase__   ):
       return torch.clip(gelu(lowerCamelCase__   )					,	self.min					,	self.max   )





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def __init__(						self   ):
       super().__init__()
       lowerCAmelCase_:       Any         =  math.sqrt(2 / math.pi   )




    def     _a						(						self					,	lowerCamelCase__   ):
       return 0.5 * input * (1 + torch.tanh(self.precomputed_constant * (input + 0.0_4_4_7_1_5 * torch.pow(lowerCamelCase__					,	3   ))   ))





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__   ):
       return nn.functional.silu(lowerCamelCase__   )





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def __init__(						self   ):
       super().__init__()
       if version.parse(torch.__version__   ) < version.parse("1.9.0"   ):
          lowerCAmelCase_:       Optional[Any]         =  self._mish_python
       else:
          lowerCAmelCase_:       Optional[int]         =  nn.functional.mish




    def     _a						(						self					,	lowerCamelCase__   ):
       return input * torch.tanh(nn.functional.softplus(lowerCamelCase__   )   )




    def     _a						(						self					,	lowerCamelCase__   ):
       return self.act(lowerCamelCase__   )





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__   ):
       return input





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__					,	lowerCamelCase__=0.7_0_7_1_0_7					,	lowerCamelCase__=0.2_8_2_0_9_5   ):
       lowerCAmelCase_:       Any         =  (input - mu).div(sigma * math.sqrt(2.0   )   )
       return 0.5 * (1.0 + torch.erf(lowerCamelCase__   ))





class 				_lowercase						(    nn.Module ):






    '''simple docstring'''




    def     _a						(						self					,	lowerCamelCase__   ):
       lowerCAmelCase_:       int         =  nn.functional.relu(lowerCamelCase__   )
       lowerCAmelCase_:       Optional[Any]         =  torch.square(lowerCamelCase__   )
       return squared





class 				_lowercase						(    UpperCAmelCase__ ):






    '''simple docstring'''




    def __getitem__(						self					,	lowerCamelCase__   ):
       lowerCAmelCase_:       int         =  super().__getitem__(lowerCamelCase__   )
       lowerCAmelCase_:       List[str]         =  content if isinstance(lowerCamelCase__					,	lowerCamelCase__   ) else (content, {})
       return cls(**lowerCamelCase__   )





a     :			Optional[int]					    =						{
    """gelu""": GELUActivation,
    """gelu_10""": (ClippedGELUActivation, {"""min""": -1_0, """max""": 1_0}),
    """gelu_fast""": FastGELUActivation,
    """gelu_new""": NewGELUActivation,
    """gelu_python""": (GELUActivation, {"""use_gelu_python""": True}),
    """gelu_pytorch_tanh""": PytorchGELUTanh,
    """gelu_accurate""": AccurateGELUActivation,
    """laplace""": LaplaceActivation,
    """linear""": LinearActivation,
    """mish""": MishActivation,
    """quick_gelu""": QuickGELUActivation,
    """relu""": nn.ReLU,
    """relu2""": ReLUSquaredActivation,
    """relu6""": nn.ReLUa,
    """sigmoid""": nn.Sigmoid,
    """silu""": SiLUActivation,
    """swish""": SiLUActivation,
    """tanh""": nn.Tanh,
}
a     :			List[Any]					    =						ClassInstantier(ACTaCLS)
def 		snake_case__  (		lowercase				):
   if activation_string in ACTaFN:
      return ACTaFN[activation_string]
   else:
      raise KeyError(F'''function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()				)}'''				)


# For backwards compatibility with: from activations import gelu_python
a     :			List[Any]					    =						get_activation("""gelu_python""")
a     :			Tuple					    =						get_activation("""gelu_new""")
a     :			List[Any]					    =						get_activation("""gelu""")
a     :			Optional[Any]					    =						get_activation("""gelu_fast""")
a     :			Optional[int]					    =						get_activation("""quick_gelu""")
a     :			str					    =						get_activation("""silu""")
a     :			Any					    =						get_activation("""mish""")







a     :			str					    =						get_activation("""linear""")
from .balanced_parentheses import balanced_parentheses
from .stack import Stack
def 		snake_case__  (		lowercase				):
   return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(lowercase       ,							-1				)
def 		snake_case__  (		lowercase				):
   if not balanced_parentheses(lowercase				):
      raise ValueError("Mismatched parentheses"				)
   lowerCAmelCase_:       Stack[str]         =  Stack()
   lowerCAmelCase_:       Union[str, Any]         =  []
   for char in expression_str:
      if char.isalpha() or char.isdigit():
         postfix.append(lowercase				)
      elif char == "(":
         stack.push(lowercase				)
      elif char == ")":
         while not stack.is_empty() and stack.peek() != "(":
            postfix.append(stack.pop()				)
         stack.pop()
      else:
         while not stack.is_empty() and precedence(lowercase				) <= precedence(stack.peek()				):
            postfix.append(stack.pop()				)
         stack.push(lowercase				)
   while not stack.is_empty():
      postfix.append(stack.pop()				)
   return " ".join(lowercase				)


if __name__ == "__main__":
 from doctest import testmod

 testmod()
 a     :			int					    =						"""a+b*(c^d-e)^(f+g*h)-i"""

 print("""Infix to Postfix Notation demonstration:\n""")
 print("""Infix notation: """ + expression)
 print("""Postfix notation: """ + infix_to_postfix(expression))