


def 			UpperCamelCase			(					_a				,						_a				,						_a				,						_a				,						_a				,						_a				,						)    ->							tuple[list[list[int]], list[list[str]]]:
     '''simple docstring'''





     lowercase_				:str       			=				list(a_						)
     lowercase_				:Optional[Any]       			=				list(a_						)
     lowercase_				:Union[str, Any]       			=				len(a_						)
     lowercase_				:List[Any]       			=				len(a_						)

     lowercase_				:Union[str, Any]       			=				[
         [0 for _ in range(len_destination_seq + 1						)] for _ in range(len_source_seq + 1						)
     ]
     lowercase_				:Optional[int]       			=				[
         ['''0''' for _ in range(len_destination_seq + 1						)] for _ in range(len_source_seq + 1						)
     ]

     for i in range(1				,						len_source_seq + 1						):
          lowercase_				:Dict       			=				i * delete_cost
          lowercase_				:Any       			=				f"D{source_seq[i - 1]:c}"

     for i in range(1				,						len_destination_seq + 1						):
          lowercase_				:Union[str, Any]       			=				i * insert_cost
          lowercase_				:str       			=				f"I{destination_seq[i - 1]:c}"

     for i in range(1				,						len_source_seq + 1						):
          for j in range(1				,						len_destination_seq + 1						):
               if source_seq[i - 1] == destination_seq[j - 1]:
                    lowercase_				:Optional[Any]       			=				costs[i - 1][j - 1] + copy_cost
                    lowercase_				:Dict       			=				f"C{source_seq[i - 1]:c}"
               else:
                    lowercase_				:List[Any]       			=				costs[i - 1][j - 1] + replace_cost
                    lowercase_				:Union[str, Any]       			=				f"R{source_seq[i - 1]:c}" + str(destination_seq[j - 1]						)

               if costs[i - 1][j] + delete_cost < costs[i][j]:
                    lowercase_				:Dict       			=				costs[i - 1][j] + delete_cost
                    lowercase_				:int       			=				f"D{source_seq[i - 1]:c}"

               if costs[i][j - 1] + insert_cost < costs[i][j]:
                    lowercase_				:Dict       			=				costs[i][j - 1] + insert_cost
                    lowercase_				:Tuple       			=				f"I{destination_seq[j - 1]:c}"

     return costs, ops




def 			UpperCamelCase			(					_a				,						_a				,						_a						)    ->							list[str]:
     '''simple docstring'''





     if i == 0 and j == 0:
          return []
     else:
          if ops[i][j][0] == "C" or ops[i][j][0] == "R":
               lowercase_				:Dict       			=				assemble_transformation(a_				,						i - 1				,						j - 1						)
               seq.append(ops[i][j]						)
               return seq
          elif ops[i][j][0] == "D":
               lowercase_				:int       			=				assemble_transformation(a_				,						i - 1				,						a_						)
               seq.append(ops[i][j]						)
               return seq
          else:
               lowercase_				:int       			=				assemble_transformation(a_				,						a_				,						j - 1						)
               seq.append(ops[i][j]						)
               return seq


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE   ,						SCREAMING_SNAKE_CASE				:						Any			   = compute_transform_tables("Python", "Algorithms", -1, 1, 2, 2)

   SCREAMING_SNAKE_CASE				:						Optional[int]			   = len(operations)
   SCREAMING_SNAKE_CASE				:						Union[str, Any]			   = len(operations[0])
   SCREAMING_SNAKE_CASE				:						Union[str, Any]			   = assemble_transformation(operations, m - 1, n - 1)

   SCREAMING_SNAKE_CASE				:						Tuple			   = list("Python")
   SCREAMING_SNAKE_CASE				:						Optional[int]			   = 0
   SCREAMING_SNAKE_CASE				:						Optional[int]			   = 0

   with open("min_cost.txt", "w") as file:
      for op in sequence:
         print("".join(string))

         if op[0] == "C":
            file.write("%-16s" % "Copy %c" % op[1])
            file.write("\t\t\t" + "".join(string))
            file.write("\r\n")

            cost -= 1
         elif op[0] == "R":
            SCREAMING_SNAKE_CASE				:						Any			   = op[2]

            file.write("%-16s" % ("Replace %c" % op[1] + " with " + str(op[2])))
            file.write("\t\t" + "".join(string))
            file.write("\r\n")

            cost += 1
         elif op[0] == "D":
            string.pop(i)

            file.write("%-16s" % "Delete %c" % op[1])
            file.write("\t\t\t" + "".join(string))
            file.write("\r\n")

            cost += 2
         else:
            string.insert(i, op[1])

            file.write("%-16s" % "Insert %c" % op[1])
            file.write("\t\t\t" + "".join(string))
            file.write("\r\n")

            cost += 2

         i += 1

      print("".join(string))
      print("Cost: ", cost)

      file.write("\r\nMinimum cost: " + str(cost))









import math
from collections import OrderedDict

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

from .utils import logging


lowerCamelCase_						     =  logging.get_logger(__name__)




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def __init__(		self   )					->					Any:
														'''simple docstring'''

														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      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return nn.functional.gelu(lowercase_			,			approximate='tanh'   )




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi   ) * (input + 0.04_47_15 * torch.pow(lowercase_			,			3.0   ))   ))




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def __init__(		self			,			lowercase_ = False   )					->					Optional[Any]:
														'''simple docstring'''

														super().__init__()
														if use_gelu_python:
																					lowerCAmelCase_										=     self._gelu_python
														else:
																					lowerCAmelCase_										=     nn.functional.gelu

							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return input * 0.5 * (1.0 + torch.erf(input / math.sqrt(2.0   )   ))






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return self.act(lowercase_   )




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return 0.5 * input * (1.0 + torch.tanh(input * 0.79_78_84_56_08 * (1.0 + 0.04_47_15 * input * input)   ))




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return input * torch.sigmoid(1.7_02 * input   )




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def __init__(		self			,			lowercase_			,			lowercase_   )					->					Optional[int]:
														'''simple docstring'''

														if min > max:
																					raise ValueError(f'''min should be < max (got min: {min}, max: {max})'''   )

														super().__init__()
														lowerCAmelCase_										=     min
														lowerCAmelCase_										=     max






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return torch.clip(gelu(lowercase_   )			,			self.min			,			self.max   )




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def __init__(		self   )					->					Union[str, Any]:
														'''simple docstring'''

														super().__init__()
														lowerCAmelCase_										=     math.sqrt(2 / math.pi   )






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return 0.5 * input * (1 + torch.tanh(self.precomputed_constant * (input + 0.04_47_15 * torch.pow(lowercase_			,			3   ))   ))




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return nn.functional.silu(lowercase_   )




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def __init__(		self   )					->					List[Any]:
														'''simple docstring'''

														super().__init__()
														if version.parse(torch.__version__   ) < version.parse('1.9.0'   ):
																					lowerCAmelCase_										=     self._mish_python
														else:
																					lowerCAmelCase_										=     nn.functional.mish

							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return input * torch.tanh(nn.functional.softplus(lowercase_   )   )






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return self.act(lowercase_   )




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_   )					->					Tensor:
														'''simple docstring'''

														return input




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_			,			lowercase_=0.70_71_07			,			lowercase_=0.28_20_95   )					->					Optional[Any]:
														'''simple docstring'''

														lowerCAmelCase_										=     (input - mu).div(sigma * math.sqrt(2.0   )   )
														return 0.5 * (1.0 + torch.erf(lowercase_   ))




class 							a_ (						nn.Module		):


							'''simple docstring'''






							def      _lowercase       (		self			,			lowercase_   )					->					Any:
														'''simple docstring'''

														lowerCAmelCase_										=     nn.functional.relu(lowercase_   )
														lowerCAmelCase_										=     torch.square(lowercase_   )
														return squared




class 							a_ (						a_		):


							'''simple docstring'''






							def __getitem__(		self			,			lowercase_   )					->					Any:
														'''simple docstring'''

														lowerCAmelCase_										=     super().__getitem__(lowercase_   )
														lowerCAmelCase_						,   lowerCAmelCase_										=     content if isinstance(lowercase_			,			lowercase_   ) else (content, {})
														return cls(**lowercase_   )


lowerCamelCase_						     =  {
    """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,
}
lowerCamelCase_						     =  ClassInstantier(ACTaCLS)
def      lowerCamelCase					(						a_	)	->			str:
							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
lowerCamelCase_						     =  get_activation("""gelu_python""")
lowerCamelCase_						     =  get_activation("""gelu_new""")
lowerCamelCase_						     =  get_activation("""gelu""")
lowerCamelCase_						     =  get_activation("""gelu_fast""")
lowerCamelCase_						     =  get_activation("""quick_gelu""")
lowerCamelCase_						     =  get_activation("""silu""")
lowerCamelCase_						     =  get_activation("""mish""")



lowerCamelCase_						     =  get_activation("""linear""")



