






from __future__ import annotations

from typing import Any


def __A   (				*__lowerCAmelCase     )->  Union[str, Any]:





						"""simple docstring"""



						if all(_check_not_integer(__UpperCamelCase     ) for m in matrix_s     ):
												for i in matrix_s[1:]:
																		_verify_matrix_sizes(matrix_s[0]			,		__UpperCamelCase     )
												return [[sum(__UpperCamelCase     ) for t in zip(*__UpperCamelCase     )] for m in zip(*__UpperCamelCase     )]
						raise TypeError('Expected a matrix, got int/list instead'     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  Any:





						"""simple docstring"""



						if (
						    _check_not_integer(__UpperCamelCase     )
						    and _check_not_integer(__UpperCamelCase     )
						    and _verify_matrix_sizes(__UpperCamelCase			,		__UpperCamelCase     )
						):
												return [[i - j for i, j in zip(*__UpperCamelCase     )] for m in zip(__UpperCamelCase			,		__UpperCamelCase     )]
						raise TypeError('Expected a matrix, got int/list instead'     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  str:





						"""simple docstring"""



						return [[x * n for x in row] for row in matrix]


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  Any:





						"""simple docstring"""



						if _check_not_integer(__UpperCamelCase     ) and _check_not_integer(__UpperCamelCase     ):
												_UpperCAmelCase ,			_UpperCAmelCase     =      _verify_matrix_sizes(__UpperCamelCase			,		__UpperCamelCase     )

						if cols[0] != rows[1]:
												_UpperCAmelCase     =      (
												    'Cannot multiply matrix of dimensions '
												    F"""({rows[0]},{cols[0]}) and ({rows[1]},{cols[1]})"""
												)
												raise ValueError(__UpperCamelCase     )
						return [
						    [sum(m * n for m, n in zip(__UpperCamelCase			,		__UpperCamelCase     )     ) for j in zip(*__UpperCamelCase     )] for i in matrix_a
						]


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





						"""simple docstring"""



						_UpperCAmelCase     =      int(__UpperCamelCase     )
						return [[int(row == column     ) for column in range(__UpperCamelCase     )] for row in range(__UpperCamelCase     )]


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase = True     )->  Dict:





						"""simple docstring"""



						if _check_not_integer(__UpperCamelCase     ):
												if return_map:
																		return map(__UpperCamelCase			,		zip(*__UpperCamelCase     )     )
												else:
																		return list(map(__UpperCamelCase			,		zip(*__UpperCamelCase     )     )     )
						raise TypeError('Expected a matrix, got int/list instead'     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  str:





						"""simple docstring"""



						_UpperCAmelCase     =      matrix[:row] + matrix[row + 1 :]
						return [row[:column] + row[column + 1 :] for row in minor]


def __A   (				__lowerCAmelCase     )->  str:





						"""simple docstring"""



						if len(__UpperCamelCase     ) == 1:
												return matrix[0][0]

						return sum(
						    x * determinant(minor(__UpperCamelCase			,		0			,		__UpperCamelCase     )     ) * (-1) ** i
						    for i, x in enumerate(matrix[0]     )     )


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





						"""simple docstring"""



						_UpperCAmelCase     =      determinant(__UpperCamelCase     )
						if det == 0:
												return None

						_UpperCAmelCase     =      [
						    [determinant(minor(__UpperCamelCase			,		__UpperCamelCase			,		__UpperCamelCase     )     ) for j in range(len(__UpperCamelCase     )     )]
						    for i in range(len(__UpperCamelCase     )     )
						]

						_UpperCAmelCase     =      [
						    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]     )]
						    for row in range(len(__UpperCamelCase     )     )
						]
						_UpperCAmelCase     =      list(transpose(__UpperCamelCase     )     )
						return scalar_multiply(__UpperCamelCase			,		1 / det     )


def __A   (				__lowerCAmelCase     )->  Any:





						"""simple docstring"""



						return not isinstance(__UpperCamelCase			,		__UpperCamelCase     ) and not isinstance(matrix[0]			,		__UpperCamelCase     )


def __A   (				__lowerCAmelCase     )->  List[Any]:





						"""simple docstring"""



						return len(__UpperCamelCase     ), len(matrix[0]     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  str:





						"""simple docstring"""



						_UpperCAmelCase     =      _shape(__UpperCamelCase     ) + _shape(__UpperCamelCase     )
						if shape[0] != shape[3] or shape[1] != shape[2]:
												_UpperCAmelCase     =      (
												    'operands could not be broadcast together with shape '
												    F"""({shape[0], shape[1]}), ({shape[2], shape[3]})"""
												)
												raise ValueError(__UpperCamelCase     )
						return (shape[0], shape[2]), (shape[1], shape[3])


def __A   (				)->  str:





						"""simple docstring"""



						_UpperCAmelCase     =      [[12, 10], [3, 9]]
						_UpperCAmelCase     =      [[3, 4], [7, 4]]
						_UpperCAmelCase     =      [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]]
						_UpperCAmelCase     =      [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
						print(F"""Add Operation, {add(__UpperCamelCase			,		__UpperCamelCase     ) = } \n"""     )
						print(
						    F"""Multiply Operation, {multiply(__UpperCamelCase			,		__UpperCamelCase     ) = } \n"""			,		)
						print(F"""Identity: {identity(5     )}\n"""     )
						print(F"""Minor of {matrix_c} = {minor(__UpperCamelCase			,		1			,		2     )} \n"""     )
						print(F"""Determinant of {matrix_b} = {determinant(__UpperCamelCase     )} \n"""     )
						print(F"""Inverse of {matrix_d} = {inverse(__UpperCamelCase     )}\n"""     )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()








import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


_a				     =  '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
'''





class __lowerCamelCase			(				unittest.TestCase					,	snake_case__):





	"""simple docstring"""






	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      load_tool('summarization'   )
							self.tool.setup()
							_UpperCAmelCase     =      load_tool('summarization'	,   remote=UpperCAmelCase   )

	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      self.tool(UpperCAmelCase   )
							self.assertEqual(
							    UpperCAmelCase	,   'Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'	,   )

	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      self.remote_tool(UpperCAmelCase   )
							self.assertEqual(
							    UpperCAmelCase	,   'Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'	,   )

	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      self.tool(text=UpperCAmelCase   )
							self.assertEqual(
							    UpperCAmelCase	,   'Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'	,   )

	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      self.remote_tool(text=UpperCAmelCase   )
							self.assertEqual(
							    UpperCAmelCase	,   'Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'	,   )
