
from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload







class        lowerCAmelCase__      :

						def __init__(			self       ,							a = None				)					->      None:


								'''simple docstring'''

								if components is None:
										_UpperCamelCase						    =	[]
								_UpperCamelCase						    =	list(a				)

						def __len__(			self				)					->      int:


								'''simple docstring'''

								return len(self.__components				)

						def __str__(			self				)					->      str:


								'''simple docstring'''

								return "(" + ",".join(map(a       ,							self.__components				)				) + ")"

						def __add__(			self       ,							a				)					->      Vector:


								'''simple docstring'''

								_UpperCamelCase						    =	len(self				)
								if size == len(a				):
										_UpperCamelCase						    =	[self.__components[i] + other.component(a				) for i in range(a				)]
										return Vector(a				)
								else:
										raise Exception("""must have the same size"""				)

						def __sub__(			self       ,							a				)					->      Vector:


								'''simple docstring'''

								_UpperCamelCase						    =	len(self				)
								if size == len(a				):
										_UpperCamelCase						    =	[self.__components[i] - other.component(a				) for i in range(a				)]
										return Vector(a				)
								else:  # error case
										raise Exception("""must have the same size"""				)

						@overload
						def __mul__(			self       ,							a				)					->      Vector:


								'''simple docstring'''

								...

						@overload
						def __mul__(			self       ,							a				)					->      float:


								'''simple docstring'''

								...

						def __mul__(			self       ,							a				)					->      float | Vector:


								'''simple docstring'''

								if isinstance(a       ,							(float, int)				):
										_UpperCamelCase						    =	[c * other for c in self.__components]
										return Vector(a				)
								elif isinstance(a       ,							a				) and len(self				) == len(a				):
										_UpperCamelCase						    =	len(self				)
										_UpperCamelCase						    =	[self.__components[i] * other.component(a				) for i in range(a				)]
										return sum(a				)
								else:  # error case
										raise Exception("""invalid operand!"""				)

						def  A_				(			self				)					->      Vector:


								'''simple docstring'''

								return Vector(self.__components				)

						def  A_				(			self       ,							a				)					->      float:


								'''simple docstring'''

								if isinstance(a       ,							a				) and -len(self.__components				) <= i < len(self.__components				):
										return self.__components[i]
								else:
										raise Exception("""index out of range"""				)

						def  A_				(			self       ,							a       ,							a				)					->      None:


								'''simple docstring'''

								assert -len(self.__components				) <= pos < len(self.__components				)
								_UpperCamelCase						    =	value

						def  A_				(			self				)					->      float:


								'''simple docstring'''

								if len(self.__components				) == 0:
										raise Exception("""Vector is empty"""				)
								_UpperCamelCase						    =	[c**2 for c in self.__components]
								return math.sqrt(sum(a				)				)







						def  A_				(			self       ,							a       ,							a = False				)					->      float:


								'''simple docstring'''

								_UpperCamelCase						    =	self * other
								_UpperCamelCase						    =	self.euclidean_length() * other.euclidean_length()
								if deg:
										return math.degrees(math.acos(num / den				)				)
								else:
										return math.acos(num / den				)




def 							__A(lowerCAmelCase )		->				Vector:

		"""simple docstring"""






		assert isinstance(lowerCAmelCase						,  lowerCAmelCase )
		return Vector([0] * dimension )


def 							__A(lowerCAmelCase						,  lowerCAmelCase )		->				Vector:

		"""simple docstring"""






		assert isinstance(lowerCAmelCase						,  lowerCAmelCase ) and (isinstance(lowerCAmelCase						,  lowerCAmelCase ))
		_UpperCamelCase						    =	[0] * dimension
		_UpperCamelCase						    =	1
		return Vector(lowerCAmelCase )


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				Vector:

		"""simple docstring"""






		assert (
		    isinstance(lowerCAmelCase						,  lowerCAmelCase )
		    and isinstance(lowerCAmelCase						,  lowerCAmelCase )
		    and (isinstance(lowerCAmelCase						,  (int, float) ))
		)
		return x * scalar + y


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				Vector:

		"""simple docstring"""






		random.seed(lowerCAmelCase )
		_UpperCamelCase						    =	[random.randint(lowerCAmelCase						,  lowerCAmelCase ) for _ in range(lowerCAmelCase )]
		return Vector(lowerCAmelCase )







class        lowerCAmelCase__      :

						def __init__(			self       ,							a       ,							a       ,							a				)					->      None:


								'''simple docstring'''

								_UpperCamelCase						    =	matrix
								_UpperCamelCase						    =	w
								_UpperCamelCase						    =	h

						def __str__(			self				)					->      str:


								'''simple docstring'''

								_UpperCamelCase						    =	""""""
								for i in range(self.__height				):
										ans += "|"
										for j in range(self.__width				):
												if j < self.__width - 1:
														ans += str(self.__matrix[i][j]				) + ","
												else:
														ans += str(self.__matrix[i][j]				) + "|\n"
								return ans

						def __add__(			self       ,							a				)					->      Matrix:


								'''simple docstring'''

								if self.__width == other.width() and self.__height == other.height():
										_UpperCamelCase						    =	[]
										for i in range(self.__height				):
												_UpperCamelCase						    =	[
												    self.__matrix[i][j] + other.component(a       ,							a				)
												    for j in range(self.__width				)
												]
												matrix.append(a				)
										return Matrix(a       ,							self.__width       ,							self.__height				)
								else:
										raise Exception("""matrix must have the same dimension!"""				)

						def __sub__(			self       ,							a				)					->      Matrix:


								'''simple docstring'''

								if self.__width == other.width() and self.__height == other.height():
										_UpperCamelCase						    =	[]
										for i in range(self.__height				):
												_UpperCamelCase						    =	[
												    self.__matrix[i][j] - other.component(a       ,							a				)
												    for j in range(self.__width				)
												]
												matrix.append(a				)
										return Matrix(a       ,							self.__width       ,							self.__height				)
								else:
										raise Exception("""matrices must have the same dimension!"""				)

						@overload
						def __mul__(			self       ,							a				)					->      Matrix:


								'''simple docstring'''

								...

						@overload
						def __mul__(			self       ,							a				)					->      Vector:


								'''simple docstring'''

								...

						def __mul__(			self       ,							a				)					->      Vector | Matrix:


								'''simple docstring'''

								if isinstance(a       ,							a				):  # matrix-vector
										if len(a				) == self.__width:
												_UpperCamelCase						    =	zero_vector(self.__height				)
												for i in range(self.__height				):
														_UpperCamelCase						    =	[
														    self.__matrix[i][j] * other.component(a				)
														    for j in range(self.__width				)
														]
														ans.change_component(a       ,							sum(a				)				)
												return ans
										else:
												raise Exception(
												    """vector must have the same size as the """
												    """number of columns of the matrix!"""				)
								elif isinstance(a       ,							(int, float)				):  # matrix-scalar
										_UpperCamelCase						    =	[
										    [self.__matrix[i][j] * other for j in range(self.__width				)]
										    for i in range(self.__height				)
										]
										return Matrix(a       ,							self.__width       ,							self.__height				)
								return None

						def  A_				(			self				)					->      int:


								'''simple docstring'''

								return self.__height

						def  A_				(			self				)					->      int:


								'''simple docstring'''

								return self.__width

						def  A_				(			self       ,							a       ,							a				)					->      float:


								'''simple docstring'''

								if 0 <= x < self.__height and 0 <= y < self.__width:
										return self.__matrix[x][y]
								else:
										raise Exception("""change_component: indices out of bounds"""				)

						def  A_				(			self       ,							a       ,							a       ,							a				)					->      None:


								'''simple docstring'''

								if 0 <= x < self.__height and 0 <= y < self.__width:
										_UpperCamelCase						    =	value
								else:
										raise Exception("""change_component: indices out of bounds"""				)

						def  A_				(			self       ,							a       ,							a				)					->      float:


								'''simple docstring'''

								if self.__height != self.__width:
										raise Exception("""Matrix is not square"""				)
								_UpperCamelCase						    =	self.__matrix[:x] + self.__matrix[x + 1 :]
								for i in range(len(a				)				):
										_UpperCamelCase						    =	minor[i][:y] + minor[i][y + 1 :]
								return Matrix(a       ,							self.__width - 1       ,							self.__height - 1				).determinant()

						def  A_				(			self       ,							a       ,							a				)					->      float:


								'''simple docstring'''

								if self.__height != self.__width:
										raise Exception("""Matrix is not square"""				)
								if 0 <= x < self.__height and 0 <= y < self.__width:
										return (-1) ** (x + y) * self.minor(a       ,							a				)
								else:
										raise Exception("""Indices out of bounds"""				)







						def  A_				(			self				)					->      float:


								'''simple docstring'''

								if self.__height != self.__width:
										raise Exception("""Matrix is not square"""				)
								if self.__height < 1:
										raise Exception("""Matrix has no element"""				)
								elif self.__height == 1:
										return self.__matrix[0][0]
								elif self.__height == 2:
										return (
										    self.__matrix[0][0] * self.__matrix[1][1]
										    - self.__matrix[0][1] * self.__matrix[1][0]
										)
								else:
										_UpperCamelCase						    =	[
										    self.__matrix[0][y] * self.cofactor(0       ,							a				) for y in range(self.__width				)
										]
										return sum(a				)




def 							__A(lowerCAmelCase )		->				Matrix:

		"""simple docstring"""






		_UpperCamelCase						    =	[[0] * n for _ in range(lowerCAmelCase )]
		return Matrix(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )







def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				Matrix:

		"""simple docstring"""






		random.seed(lowerCAmelCase )
		_UpperCamelCase						    =	[
		    [random.randint(lowerCAmelCase						,  lowerCAmelCase ) for _ in range(lowerCAmelCase )] for _ in range(lowerCAmelCase )
		]
		return Matrix(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )





import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM


def 							__A(lowerCAmelCase )		->				List[str]:

		"""simple docstring"""






		if "model" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""model."""						,  """""" )
		if "norm1" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""norm1"""						,  """attention.output.LayerNorm""" )
		if "norm2" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""norm2"""						,  """output.LayerNorm""" )
		if "norm" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""norm"""						,  """LayerNorm""" )
		if "transformer" in orig_key:
				_UpperCamelCase						    =	orig_key.split(""".""" )[0].split("""_""" )[-1]
				_UpperCamelCase						    =	orig_key.replace(F'transformer_{layer_num}'						,  F'encoder.layer.{layer_num}' )
		if "mha.attn" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""mha.attn"""						,  """attention.self""" )
		if "mha" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""mha"""						,  """attention""" )
		if "W_q" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""W_q"""						,  """self.query""" )
		if "W_k" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""W_k"""						,  """self.key""" )
		if "W_v" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""W_v"""						,  """self.value""" )
		if "ff1" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""ff1"""						,  """intermediate.dense""" )
		if "ff2" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""ff2"""						,  """output.dense""" )
		if "ff" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""ff"""						,  """output.dense""" )
		if "mlm_class" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""mlm.mlm_class"""						,  """cls.predictions.decoder""" )
		if "mlm" in orig_key:
				_UpperCamelCase						    =	orig_key.replace("""mlm"""						,  """cls.predictions.transform""" )
		if "cls" not in orig_key:
				_UpperCamelCase						    =	"""yoso.""" + orig_key

		return orig_key


def 							__A(lowerCAmelCase						,  lowerCAmelCase )		->				List[str]:

		"""simple docstring"""






		for key in orig_state_dict.copy().keys():
				_UpperCamelCase						    =	orig_state_dict.pop(lowerCAmelCase )

				if ("pooler" in key) or ("sen_class" in key):
						continue
				else:
						_UpperCamelCase						    =	val

		_UpperCamelCase						    =	orig_state_dict["""cls.predictions.decoder.bias"""]
		_UpperCamelCase						    =	torch.arange(lowerCAmelCase ).expand((1, -1) ) + 2

		return orig_state_dict


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				Optional[int]:

		"""simple docstring"""






		_UpperCamelCase						    =	torch.load(lowerCAmelCase						,  map_location="""cpu""" )["""model_state_dict"""]
		_UpperCamelCase						    =	YosoConfig.from_json_file(lowerCAmelCase )
		_UpperCamelCase						    =	YosoForMaskedLM(lowerCAmelCase )

		_UpperCamelCase						    =	convert_checkpoint_helper(config.max_position_embeddings						,  lowerCAmelCase )

		print(model.load_state_dict(lowerCAmelCase ) )
		model.eval()
		model.save_pretrained(lowerCAmelCase )

		print(F'Checkpoint successfuly converted. Model saved at {pytorch_dump_path}' )


if __name__ == "__main__":
		lowerCamelCase__	=							argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    "--pytorch_model_path", default=None, type=str, required=True, help="Path to YOSO pytorch checkpoint."
		)
		parser.add_argument(
		    "--config_file",
		    default=None,
		    type=str,
		    required=True,
		    help="The json file for YOSO model config.",
		)
		parser.add_argument(
		    "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
		)
		lowerCamelCase__	=							parser.parse_args()
		convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)



