





import os
import sys
import unittest


UpperCAmelCase_							=				os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


UpperCAmelCase_							=				os.path.join("""tests""", """models""", """bert""", """test_modeling_bert.py""")
UpperCAmelCase_							=				os.path.join("""tests""", """models""", """blip""", """test_modeling_blip.py""")
class     UpperCamelCase__					(     unittest.TestCase				):






		'''simple docstring'''






		def 						snake_case__				(							self  )       -> int:






									"""simple docstring"""
									lowercase_	:   Dict  				=     get_test_to_tester_mapping(snake_case__  )
									lowercase_	:   str  				=     get_test_to_tester_mapping(snake_case__  )

									lowercase_	:   Tuple  				=     {"""BertModelTest""": """BertModelTester"""}

									lowercase_	:   Tuple  				=     {
									    """BlipModelTest""": """BlipModelTester""",
									    """BlipTextImageModelTest""": """BlipTextImageModelsModelTester""",
									    """BlipTextModelTest""": """BlipTextModelTester""",
									    """BlipTextRetrievalModelTest""": """BlipTextRetrievalModelTester""",
									    """BlipVQAModelTest""": """BlipVQAModelTester""",
									    """BlipVisionModelTest""": """BlipVisionModelTester""",
									}

									self.assertEqual(get_test_info.to_json(snake_case__  ),   snake_case__  )
									self.assertEqual(get_test_info.to_json(snake_case__  ),   snake_case__  )






		def 						snake_case__				(							self  )       -> Dict:






									"""simple docstring"""
									lowercase_	:   int  				=     get_model_to_test_mapping(snake_case__  )
									lowercase_	:   Any  				=     get_model_to_test_mapping(snake_case__  )

									lowercase_	:   Tuple  				=     {
									    """BertForMaskedLM""": ["""BertModelTest"""],
									    """BertForMultipleChoice""": ["""BertModelTest"""],
									    """BertForNextSentencePrediction""": ["""BertModelTest"""],
									    """BertForPreTraining""": ["""BertModelTest"""],
									    """BertForQuestionAnswering""": ["""BertModelTest"""],
									    """BertForSequenceClassification""": ["""BertModelTest"""],
									    """BertForTokenClassification""": ["""BertModelTest"""],
									    """BertLMHeadModel""": ["""BertModelTest"""],
									    """BertModel""": ["""BertModelTest"""],
									}

									lowercase_	:   str  				=     {
									    """BlipForConditionalGeneration""": ["""BlipTextImageModelTest"""],
									    """BlipForImageTextRetrieval""": ["""BlipTextRetrievalModelTest"""],
									    """BlipForQuestionAnswering""": ["""BlipVQAModelTest"""],
									    """BlipModel""": ["""BlipModelTest"""],
									    """BlipTextModel""": ["""BlipTextModelTest"""],
									    """BlipVisionModel""": ["""BlipVisionModelTest"""],
									}

									self.assertEqual(get_test_info.to_json(snake_case__  ),   snake_case__  )
									self.assertEqual(get_test_info.to_json(snake_case__  ),   snake_case__  )






		def 						snake_case__				(							self  )       -> int:






									"""simple docstring"""
									lowercase_	:   str  				=     get_model_to_tester_mapping(snake_case__  )
									lowercase_	:   int  				=     get_model_to_tester_mapping(snake_case__  )

									lowercase_	:   int  				=     {
									    """BertForMaskedLM""": ["""BertModelTester"""],
									    """BertForMultipleChoice""": ["""BertModelTester"""],
									    """BertForNextSentencePrediction""": ["""BertModelTester"""],
									    """BertForPreTraining""": ["""BertModelTester"""],
									    """BertForQuestionAnswering""": ["""BertModelTester"""],
									    """BertForSequenceClassification""": ["""BertModelTester"""],
									    """BertForTokenClassification""": ["""BertModelTester"""],
									    """BertLMHeadModel""": ["""BertModelTester"""],
									    """BertModel""": ["""BertModelTester"""],
									}

									lowercase_	:   List[str]  				=     {
									    """BlipForConditionalGeneration""": ["""BlipTextImageModelsModelTester"""],
									    """BlipForImageTextRetrieval""": ["""BlipTextRetrievalModelTester"""],
									    """BlipForQuestionAnswering""": ["""BlipVQAModelTester"""],
									    """BlipModel""": ["""BlipModelTester"""],
									    """BlipTextModel""": ["""BlipTextModelTester"""],
									    """BlipVisionModel""": ["""BlipVisionModelTester"""],
									}

									self.assertEqual(get_test_info.to_json(snake_case__  ),   snake_case__  )
									self.assertEqual(get_test_info.to_json(snake_case__  ),   snake_case__  )






from __future__ import annotations

import numpy as np
from numpy import floataa
from numpy.typing import NDArray





def  __magic_name__  (				lowercase				,       lowercase				,       lowercase				,       lowercase				,       )				-> list[float]:

							"""simple docstring"""



							lowercase_				,		lowercase_	:   List[str]  				=     coefficient_matrix.shape
							lowercase_				,		lowercase_	:   Any  				=     constant_matrix.shape

							if rowsa != colsa:
														lowercase_	:   List[Any]  				=     f"""Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}"""
														raise ValueError(lowercase				)

							if colsa != 1:
														lowercase_	:   Optional[int]  				=     f"""Constant matrix must be nx1 but received {rowsa}x{colsa}"""
														raise ValueError(lowercase				)

							if rowsa != rowsa:
														lowercase_	:   Tuple  				=     (
														    """Coefficient and constant matrices dimensions must be nxn and nx1 but """
														    f"""received {rowsa}x{colsa} and {rowsa}x{colsa}"""
														)
														raise ValueError(lowercase				)

							if len(lowercase				) != rowsa:
														lowercase_	:   int  				=     (
														    """Number of initial values must be equal to number of rows in coefficient """
														    f"""matrix but received {len(lowercase				)} and {rowsa}"""
														)
														raise ValueError(lowercase				)

							if iterations <= 0:
														raise ValueError("""Iterations must be at least 1"""				)

							lowercase_	:   NDArray[floataa]  				=     np.concatenate(
							    (coefficient_matrix, constant_matrix)				,       axis=1				)

							lowercase_				,		lowercase_	:   Dict  				=     table.shape

							strictly_diagonally_dominant(lowercase				)

							# Iterates the whole matrix for given number of times
							for _ in range(lowercase				):
														lowercase_	:   str  				=     []
														for row in range(lowercase				):
																					lowercase_	:   Dict  				=     0
																					for col in range(lowercase				):
																												if col == row:
																																			lowercase_	:   Optional[Any]  				=     table[row][col]
																												elif col == cols - 1:
																																			lowercase_	:   Tuple  				=     table[row][col]
																												else:
																																			temp += (-1) * table[row][col] * init_val[col]
																					lowercase_	:   List[Any]  				=     (temp + val) / denom
																					new_val.append(lowercase				)
														lowercase_	:   Optional[int]  				=     new_val

							return [float(lowercase				) for i in new_val]





def  __magic_name__  (				lowercase				)				-> bool:

							"""simple docstring"""



							lowercase_				,		lowercase_	:   str  				=     table.shape

							lowercase_	:   str  				=     True

							for i in range(0				,       lowercase				):
														lowercase_	:   Any  				=     0
														for j in range(0				,       cols - 1				):
																					if i == j:
																												continue
																					else:
																												total += table[i][j]

														if table[i][i] <= total:
																					raise ValueError("""Coefficient matrix is not strictly diagonally dominant"""				)

							return is_diagonally_dominant


# Test Cases
if __name__ == "__main__":
							import doctest

							doctest.testmod()