
from __future__ import annotations

from typing import Any







class      A__							:






				def __init__(						self					:      List[Any]    ,     a					:      int    ,     a					:      int    ,     a					:      float = 0   ):






							'''simple docstring'''







							lowerCAmelCase__      ,				lowerCAmelCase__      :      Dict         =		row, column
							lowerCAmelCase__      :      Dict         =		[[default_value for c in range(a   )] for r in range(a   )]






				def __str__(						self					:      Any   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[Any]         =		f'''Matrix consist of {self.row} rows and {self.column} columns\n'''

							# Make string identifier
							lowerCAmelCase__      :      Optional[int]         =		0
							for row_vector in self.array:
										for obj in row_vector:
													lowerCAmelCase__      :      int         =		max(a    ,     len(str(a   )   )   )
							lowerCAmelCase__      :      List[str]         =		f'''%{max_element_length}s'''

							# Make string and return
							def single_line(a					:      list[float]   ) -> str:
										nonlocal string_format_identifier
										lowerCAmelCase__      :      str         =		'['
										line += ", ".join(string_format_identifier % (obj,) for obj in row_vector   )
										line += "]"
										return line

							s += "\n".join(single_line(a   ) for row_vector in self.array   )
							return s






				def __repr__(						self					:      Union[str, Any]   ):






							'''simple docstring'''







							return str(self   )






				def 							_lowerCamelCase		(						self					:      Optional[Any]    ,     a					:      tuple[int, int]   ):






							'''simple docstring'''







							if not (isinstance(a    ,     (list, tuple)   ) and len(a   ) == 2):
										return False
							elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
										return False
							else:
										return True






				def __getitem__(						self					:      Union[str, Any]    ,     a					:      tuple[int, int]   ):






							'''simple docstring'''







							assert self.validate_indicies(a   )
							return self.array[loc[0]][loc[1]]






				def __setitem__(						self					:      Union[str, Any]    ,     a					:      tuple[int, int]    ,     a					:      float   ):






							'''simple docstring'''







							assert self.validate_indicies(a   )
							lowerCAmelCase__      :      Dict         =		value






				def __add__(						self					:      Any    ,     a					:      Matrix   ):






							'''simple docstring'''







							assert isinstance(a    ,     a   )
							assert self.row == another.row and self.column == another.column

							# Add
							lowerCAmelCase__      :      Tuple         =		Matrix(self.row    ,     self.column   )
							for r in range(self.row   ):
										for c in range(self.column   ):
													lowerCAmelCase__      :      Any         =		self[r, c] + another[r, c]
							return result






				def __neg__(						self					:      str   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Any         =		Matrix(self.row    ,     self.column   )
							for r in range(self.row   ):
										for c in range(self.column   ):
													lowerCAmelCase__      :      Tuple         =		-self[r, c]
							return result






				def __sub__(						self					:      str    ,     a					:      Matrix   ):






							'''simple docstring'''







							return self + (-another)






				def __mul__(						self					:      str    ,     a					:      int | float | Matrix   ):






							'''simple docstring'''







							if isinstance(a    ,     (int, float)   ):  # Scalar multiplication
										lowerCAmelCase__      :      int         =		Matrix(self.row    ,     self.column   )
										for r in range(self.row   ):
													for c in range(self.column   ):
																lowerCAmelCase__      :      Tuple         =		self[r, c] * another
										return result
							elif isinstance(a    ,     a   ):  # Matrix multiplication
										assert self.column == another.row
										lowerCAmelCase__      :      Any         =		Matrix(self.row    ,     another.column   )
										for r in range(self.row   ):
													for c in range(another.column   ):
																for i in range(self.column   ):
																			result[r, c] += self[r, i] * another[i, c]
										return result
							else:
										lowerCAmelCase__      :      Union[str, Any]         =		f'''Unsupported type given for another ({type(a   )})'''
										raise TypeError(a   )






				def 							_lowerCamelCase		(						self					:      str   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Union[str, Any]         =		Matrix(self.column    ,     self.row   )
							for r in range(self.row   ):
										for c in range(self.column   ):
													lowerCAmelCase__      :      List[str]         =		self[r, c]
							return result






				def 							_lowerCamelCase		(						self					:      str    ,     a					:      Matrix    ,     a					:      Matrix   ):






							'''simple docstring'''







							assert isinstance(a    ,     a   ) and isinstance(a    ,     a   )
							assert self.row == self.column == u.row == v.row  # u, v should be column vector
							assert u.column == v.column == 1  # u, v should be column vector

							# Calculate
							lowerCAmelCase__      :      List[str]         =		v.transpose()
							lowerCAmelCase__      :      int         =		(v_t * self * u)[0, 0] + 1
							if numerator_factor == 0:
										return None  # It's not invertable
							return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":
					def  lowerCAmelCase__			(  )				->		None:
								# a^(-1)
								lowerCAmelCase__      :      int         =		Matrix(3       ,							3       ,							0     )
								for i in range(3     ):
											lowerCAmelCase__      :      List[str]         =		1
								print(F'''a^(-1) is {ainv}'''     )
								# u, v
								lowerCAmelCase__      :      Optional[int]         =		Matrix(3       ,							1       ,							0     )
								lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      :      List[str]         =		1, 2, -3
								lowerCAmelCase__      :      List[str]         =		Matrix(3       ,							1       ,							0     )
								lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      :      str         =		4, -2, 5
								print(F'''u is {u}'''     )
								print(F'''v is {v}'''     )
								print(F'''uv^T is {u * v.transpose()}'''     )
								# Sherman Morrison
								print(F'''(a + uv^T)^(-1) is {ainv.sherman_morrison(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_     )}'''     )
					def  lowerCAmelCase__			(  )				->		None:
								import doctest

								doctest.testmod()







					testa()

from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
					from PIL import Image

					from ..image_utils import load_image

if is_tf_available():
					import tensorflow as tf

					from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
					from ..tf_utils import stable_softmax

if is_torch_available():
					from ..models.auto.modeling_auto import MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING

lowerCamelCase__          =		logging.get_logger(__name__)







@add_end_docstrings(__magic_name__	)
class      A__							(     __magic_name__	):






				def __init__(						self					:      int    ,     *a					:      Dict    ,     **a					:      Union[str, Any]   ):






							'''simple docstring'''







							super().__init__(*a    ,     **a   )
							requires_backends(self    ,     'vision'   )
							self.check_model_type(
							    TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
							    if self.framework == 'tf'
							    else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING   )






				def 							_lowerCamelCase		(						self					:      Dict    ,     a					:      List[str]=None   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Any         =		{}
							if top_k is not None:
										lowerCAmelCase__      :      Tuple         =		top_k
							return {}, {}, postprocess_params






				def __call__(						self					:      Any    ,     a					:      Union[str, List[str], "Image.Image", List["Image.Image"]]    ,     **a					:      List[Any]   ):






							'''simple docstring'''







							return super().__call__(a    ,     **a   )






				def 							_lowerCamelCase		(						self					:      Any    ,     a					:      Optional[Any]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[Any]         =		load_image(a   )
							lowerCAmelCase__      :      Optional[int]         =		self.image_processor(images=a    ,     return_tensors=self.framework   )
							return model_inputs






				def 							_lowerCamelCase		(						self					:      Optional[int]    ,     a					:      List[str]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Optional[Any]         =		self.model(**a   )
							return model_outputs






				def 							_lowerCamelCase		(						self					:      Optional[Any]    ,     a					:      List[Any]    ,     a					:      List[Any]=5   ):






							'''simple docstring'''







							if top_k > self.model.config.num_labels:
										lowerCAmelCase__      :      Optional[int]         =		self.model.config.num_labels

							if self.framework == "pt":
										lowerCAmelCase__      :      List[Any]         =		model_outputs.logits.softmax(-1   )[0]
										lowerCAmelCase__      ,				lowerCAmelCase__      :      Optional[int]         =		probs.topk(a   )
							elif self.framework == "tf":
										lowerCAmelCase__      :      Any         =		stable_softmax(model_outputs.logits    ,     axis=-1   )[0]
										lowerCAmelCase__      :      Any         =		tf.math.top_k(a    ,     k=a   )
										lowerCAmelCase__      ,				lowerCAmelCase__      :      int         =		topk.values.numpy(), topk.indices.numpy()
							else:
										raise ValueError(f'''Unsupported framework: {self.framework}'''   )

							lowerCAmelCase__      :      List[Any]         =		scores.tolist()
							lowerCAmelCase__      :      List[str]         =		ids.tolist()
							return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(a    ,     a   )]