





from __future__ import annotations

from typing import Any


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


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


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__       ,lowerCAmelCase__	):
  return [[x * n for x in row] for row in matrix]


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__       ,lowerCAmelCase__	):
  if _check_not_integer(lowerCAmelCase__	) and _check_not_integer(lowerCAmelCase__	):
    lowerCamelCase_  :    Optional[Any]   	=			_verify_matrix_sizes(lowerCAmelCase__       ,lowerCAmelCase__	)

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


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
  lowerCamelCase_  :    List[Any]   	=			int(lowerCAmelCase__	)
  return [[int(row == column	) for column in range(lowerCAmelCase__	)] for row in range(lowerCAmelCase__	)]


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__       ,lowerCAmelCase__ = True	):
  if _check_not_integer(lowerCAmelCase__	):
    if return_map:
      return map(lowerCAmelCase__       ,zip(*lowerCAmelCase__	)	)
    else:
      return list(map(lowerCAmelCase__       ,zip(*lowerCAmelCase__	)	)	)
  raise TypeError('Expected a matrix, got int/list instead'	)


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__	):
  lowerCamelCase_  :    Optional[Any]   	=			matrix[:row] + matrix[row + 1 :]
  return [row[:column] + row[column + 1 :] for row in minor]


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
  if len(lowerCAmelCase__	) == 1:
    return matrix[0][0]

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


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
  lowerCamelCase_  :    Any   	=			determinant(lowerCAmelCase__	)
  if det == 0:
    return None

  lowerCamelCase_  :    Any   	=			[
      [determinant(minor(lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__	)	) for j in range(len(lowerCAmelCase__	)	)]
      for i in range(len(lowerCAmelCase__	)	)
  ]

  lowerCamelCase_  :    Optional[int]   	=			[
      [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]	)]
      for row in range(len(lowerCAmelCase__	)	)
  ]
  lowerCamelCase_  :    Union[str, Any]   	=			list(transpose(lowerCAmelCase__	)	)
  return scalar_multiply(lowerCAmelCase__       ,1 / det	)


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
  return not isinstance(lowerCAmelCase__       ,lowerCAmelCase__	) and not isinstance(matrix[0]       ,lowerCAmelCase__	)


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
  return len(lowerCAmelCase__	), len(matrix[0]	)


def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__       ,lowerCAmelCase__	):
  lowerCamelCase_  :    str   	=			_shape(lowerCAmelCase__	) + _shape(lowerCAmelCase__	)
  if shape[0] != shape[3] or shape[1] != shape[2]:
    lowerCamelCase_  :    str   	=			(
        "operands could not be broadcast together with shape "
        F"({shape[0], shape[1]}), ({shape[2], shape[3]})"
    )
    raise ValueError(lowerCAmelCase__	)
  return (shape[0], shape[2]), (shape[1], shape[3])


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


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()







import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

_lowercase		:     Optional[Any] 					=[(1,)]


def 		_SCREAMING_SNAKE_CASE    (   ):
		lowerCamelCase_  :    Union[str, Any]   	=			bool(os.getenv('RUN_SLOW'       ,0	)	)
		if run_slow:
				assert True
		else:
				assert False, "should have been skipped"


def 		_SCREAMING_SNAKE_CASE    (   ):
		lowerCamelCase_  :    List[str]   	=			bool(os.getenv('RUN_SLOW'       ,0	)	)
		if run_slow and torch_device == "cuda":
				assert True
		else:
				assert False, "should have been skipped"






@require_torch
class 	UpperCamelCase_     (     unittest.TestCase       ):



					@slow
					@require_torch_gpu
					def      __a    (		self    :    Tuple	):
							check_slow_torch_cuda()



					@require_torch_gpu
					@slow
					def      __a    (		self    :    Optional[int]	):
							check_slow_torch_cuda()





					@parameterized.expand(lowerCamelCase	)
					@slow
					def      __a    (		self    :    List[str]					,			lowerCamelCase    :    Optional[Any]=None	):
							check_slow()


@slow
@require_torch_gpu
def 		_SCREAMING_SNAKE_CASE    (   ):
		check_slow_torch_cuda()


@require_torch_gpu
@slow
def 		_SCREAMING_SNAKE_CASE    (   ):
		check_slow_torch_cuda()


@slow
@pytest.mark.parametrize('param'       ,[1]	)
def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
		check_slow()





@pytest.mark.parametrize('param'       ,[1]	)
@slow
def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
		check_slow()
