
'''simple docstring'''



from __future__ import annotations

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

class    _a				:





       """simple docstring"""




       def __init__(							self       ,							A__ = None      )    ->			None:
          if components is None:
             _SCREAMING_SNAKE_CASE      =				[]
          _SCREAMING_SNAKE_CASE      =				list(A__      )






       def __len__(							self      )    ->			int:
          return len(self.__components      )






       def __str__(							self      )    ->			str:
          return "(" + ",".join(map(A__       ,							self.__components      )      ) + ")"






       def __add__(							self       ,							A__      )    ->			Vector:
          _SCREAMING_SNAKE_CASE      =				len(self      )
          if size == len(A__      ):
             _SCREAMING_SNAKE_CASE      =				[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:
          _SCREAMING_SNAKE_CASE      =				len(self      )
          if size == len(A__      ):
             _SCREAMING_SNAKE_CASE      =				[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:
          ...






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






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






       def        UpperCamelCase				(							self      )    ->			Vector:
          return Vector(self.__components      )






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






       def        UpperCamelCase				(							self       ,							A__       ,							A__      )    ->			None:
          assert -len(self.__components      ) <= pos < len(self.__components      )
          _SCREAMING_SNAKE_CASE      =				value






       def        UpperCamelCase				(							self      )    ->			float:
          if len(self.__components      ) == 0:
             raise Exception("""Vector is empty"""      )
          _SCREAMING_SNAKE_CASE      =				[c**2 for c in self.__components]
          return math.sqrt(sum(A__      )      )






       def        UpperCamelCase				(							self       ,							A__       ,							A__ = False      )    ->			float:
          _SCREAMING_SNAKE_CASE      =				self * other
          _SCREAMING_SNAKE_CASE      =				self.euclidean_length() * other.euclidean_length()
          if deg:
             return math.degrees(math.acos(num / den      )      )
          else:
             return math.acos(num / den      )






def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Vector:




   """simple docstring"""
   assert isinstance(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)
   return Vector([0] * dimension						)
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)     ->     Vector:




   """simple docstring"""
   assert isinstance(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						) and (isinstance(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						))
   _SCREAMING_SNAKE_CASE      =				[0] * dimension
   _SCREAMING_SNAKE_CASE      =				1
   return Vector(SCREAMING_SNAKE_CASE_						)
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)     ->     Vector:




   """simple docstring"""
   assert (
       isinstance(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)
       and isinstance(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)
       and (isinstance(SCREAMING_SNAKE_CASE_    ,      (int, float)						))
   )
   return x * scalar + y
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)     ->     Vector:




   """simple docstring"""
   random.seed(SCREAMING_SNAKE_CASE_						)
   _SCREAMING_SNAKE_CASE      =				[random.randint(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						) for _ in range(SCREAMING_SNAKE_CASE_						)]
   return Vector(SCREAMING_SNAKE_CASE_						)

class    _a				:





       """simple docstring"""




       def __init__(							self       ,							A__       ,							A__       ,							A__      )    ->			None:
          _SCREAMING_SNAKE_CASE      =				matrix
          _SCREAMING_SNAKE_CASE      =				w
          _SCREAMING_SNAKE_CASE      =				h






       def __str__(							self      )    ->			str:
          _SCREAMING_SNAKE_CASE      =				""""""
          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:
          if self.__width == other.width() and self.__height == other.height():
             _SCREAMING_SNAKE_CASE      =				[]
             for i in range(self.__height      ):
                _SCREAMING_SNAKE_CASE      =				[
                    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:
          if self.__width == other.width() and self.__height == other.height():
             _SCREAMING_SNAKE_CASE      =				[]
             for i in range(self.__height      ):
                _SCREAMING_SNAKE_CASE      =				[
                    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:
          ...






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






       def __mul__(							self       ,							A__      )    ->			Vector | Matrix:
          if isinstance(A__       ,							A__      ):  # matrix-vector
             if len(A__      ) == self.__width:
                _SCREAMING_SNAKE_CASE      =				zero_vector(self.__height      )
                for i in range(self.__height      ):
                   _SCREAMING_SNAKE_CASE      =				[
                       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
             _SCREAMING_SNAKE_CASE      =				[
                 [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        UpperCamelCase				(							self      )    ->			int:
          return self.__height






       def        UpperCamelCase				(							self      )    ->			int:
          return self.__width






       def        UpperCamelCase				(							self       ,							A__       ,							A__      )    ->			float:
          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        UpperCamelCase				(							self       ,							A__       ,							A__       ,							A__      )    ->			None:
          if 0 <= x < self.__height and 0 <= y < self.__width:
             _SCREAMING_SNAKE_CASE      =				value
          else:
             raise Exception("""change_component: indices out of bounds"""      )






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






       def        UpperCamelCase				(							self       ,							A__       ,							A__      )    ->			float:
          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        UpperCamelCase				(							self      )    ->			float:
          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:
             _SCREAMING_SNAKE_CASE      =				[
                 self.__matrix[0][y] * self.cofactor(0       ,							A__      ) for y in range(self.__width      )
             ]
             return sum(A__      )






def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Matrix:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				[[0] * n for _ in range(SCREAMING_SNAKE_CASE_						)]
   return Matrix(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)







def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)     ->     Matrix:




   """simple docstring"""
   random.seed(SCREAMING_SNAKE_CASE_						)
   _SCREAMING_SNAKE_CASE      =				[
       [random.randint(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						) for _ in range(SCREAMING_SNAKE_CASE_						)] for _ in range(SCREAMING_SNAKE_CASE_						)
   ]
   return Matrix(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)








'''simple docstring'''



import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding

class    _a				(_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE      =  ['image_processor', 'tokenizer']
       SCREAMING_SNAKE_CASE      =  'ChineseCLIPImageProcessor'
       SCREAMING_SNAKE_CASE      =  ('BertTokenizer', 'BertTokenizerFast')






       def __init__(							self       ,							A__=None       ,							A__=None       ,							**A__      )    ->			int:
          _SCREAMING_SNAKE_CASE      =				None
          if "feature_extractor" in kwargs:
             warnings.warn(
                 """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
                 """ instead."""       ,							A__       ,							)
             _SCREAMING_SNAKE_CASE      =				kwargs.pop("""feature_extractor"""      )

          _SCREAMING_SNAKE_CASE      =				image_processor if image_processor is not None else feature_extractor
          if image_processor is None:
             raise ValueError("""You need to specify an `image_processor`."""      )
          if tokenizer is None:
             raise ValueError("""You need to specify a `tokenizer`."""      )

          super().__init__(A__       ,							A__      )
          _SCREAMING_SNAKE_CASE      =				self.image_processor






       def __call__(							self       ,							A__=None       ,							A__=None       ,							A__=None       ,							**A__      )    ->			Optional[int]:

          if text is None and images is None:
             raise ValueError("""You have to specify either text or images. Both cannot be none."""      )

          if text is not None:
             _SCREAMING_SNAKE_CASE      =				self.tokenizer(A__       ,							return_tensors=A__       ,							**A__      )

          if images is not None:
             _SCREAMING_SNAKE_CASE      =				self.image_processor(A__       ,							return_tensors=A__       ,							**A__      )

          if text is not None and images is not None:
             _SCREAMING_SNAKE_CASE      =				image_features.pixel_values
             return encoding
          elif text is not None:
             return encoding
          else:
             return BatchEncoding(data=dict(**A__      )       ,							tensor_type=A__      )






       def        UpperCamelCase				(							self       ,							*A__       ,							**A__      )    ->			Dict:
          return self.tokenizer.batch_decode(*A__       ,							**A__      )






       def        UpperCamelCase				(							self       ,							*A__       ,							**A__      )    ->			Optional[Any]:
          return self.tokenizer.decode(*A__       ,							**A__      )






       @property
       def        UpperCamelCase				(							self      )    ->			List[Any]:
          _SCREAMING_SNAKE_CASE      =				self.tokenizer.model_input_names
          _SCREAMING_SNAKE_CASE      =				self.image_processor.model_input_names
          return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )






       @property
       def        UpperCamelCase				(							self      )    ->			Optional[int]:
          warnings.warn(
              """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""       ,							A__       ,							)
          return self.image_processor_class






