




import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')





def        __UpperCAmelCase						(							lowerCamelCase_ :     int  )       ->  Tuple:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : List[str]					  =      test_file.split(os.path.sep  )
			if components[0:2] != ["tests", "models"]:
						raise ValueError(
						    '`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '
						    F'{test_file} instead.'  )
			SCREAMING_SNAKE_CASE_   : int					  =      components[-1]
			if not test_fn.endswith('py'  ):
						raise ValueError(F'`test_file` should be a python file. Got {test_fn} instead.'  )
			if not test_fn.startswith('test_modeling_'  ):
						raise ValueError(
						    F'`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.'  )

			SCREAMING_SNAKE_CASE_   : Tuple					  =      components[:-1] + [test_fn.replace('.py'  ,							''  )]
			SCREAMING_SNAKE_CASE_   : int					  =      '.'.join(lowerCamelCase_  )

			return test_module_path





def        __UpperCAmelCase						(							lowerCamelCase_ :     str  )       ->  Optional[int]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      get_module_path(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : List[str]					  =      importlib.import_module(lowerCamelCase_  )

			return test_module





def        __UpperCAmelCase						(							lowerCamelCase_ :     Optional[int]  )       ->  int:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : List[Any]					  =      []
			SCREAMING_SNAKE_CASE_   : str					  =      get_test_module(lowerCamelCase_  )
			for attr in dir(lowerCamelCase_  ):
						if attr.endswith('ModelTester'  ):
									tester_classes.append(getattr(lowerCamelCase_  ,							lowerCamelCase_  )  )

    # sort with class names
			return sorted(lowerCamelCase_  ,							key=lambda lowerCamelCase_  : x.__name__  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     List[Any]  )       ->  List[Any]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : str					  =      []
			SCREAMING_SNAKE_CASE_   : Optional[int]					  =      get_test_module(lowerCamelCase_  )
			for attr in dir(lowerCamelCase_  ):
						SCREAMING_SNAKE_CASE_   : List[str]					  =      getattr(lowerCamelCase_  ,							lowerCamelCase_  )
						# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
						# `all_model_classes` is not empty (which also excludes other special classes).
						SCREAMING_SNAKE_CASE_   : List[Any]					  =      getattr(lowerCamelCase_  ,							'all_model_classes'  ,							[]  )
						if len(lowerCamelCase_  ) > 0:
									test_classes.append(lowerCamelCase_  )

    # sort with class names
			return sorted(lowerCamelCase_  ,							key=lambda lowerCamelCase_  : x.__name__  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     Any  )       ->  Optional[int]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : str					  =      get_test_classes(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      set()
			for test_class in test_classes:
						model_classes.update(test_class.all_model_classes  )

			# sort with class names
			return sorted(lowerCamelCase_  ,							key=lambda lowerCamelCase_  : x.__name__  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     Dict  )       ->  Tuple:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      test_class()
			if hasattr(lowerCamelCase_  ,							'setUp'  ):
						test.setUp()

			SCREAMING_SNAKE_CASE_   : str					  =      None
			if hasattr(lowerCamelCase_  ,							'model_tester'  ):
						# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
						if test.model_tester is not None:
									SCREAMING_SNAKE_CASE_   : List[Any]					  =      test.model_tester.__class__

			return model_tester





def        __UpperCAmelCase						(							lowerCamelCase_ :     Optional[int]  ,							lowerCamelCase_ :     Optional[Any]  )       ->  str:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : List[str]					  =      get_test_classes(lowerCamelCase_  )

			SCREAMING_SNAKE_CASE_   : List[Any]					  =      []
			for test_class in test_classes:
						if model_class in test_class.all_model_classes:
									target_test_classes.append(lowerCamelCase_  )

    # sort with class names
			return sorted(lowerCamelCase_  ,							key=lambda lowerCamelCase_  : x.__name__  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     Tuple  ,							lowerCamelCase_ :     Tuple  )       ->  Optional[int]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : str					  =      get_test_classes_for_model(lowerCamelCase_  ,							lowerCamelCase_  )

			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      []
			for test_class in test_classes:
						SCREAMING_SNAKE_CASE_   : List[str]					  =      get_model_tester_from_test_class(lowerCamelCase_  )
						if tester_class is not None:
									tester_classes.append(lowerCamelCase_  )

    # sort with class names
			return sorted(lowerCamelCase_  ,							key=lambda lowerCamelCase_  : x.__name__  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     List[Any]  )       ->  Dict:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      get_test_classes(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Any					  =      {test_class: get_model_tester_from_test_class(lowerCamelCase_  ) for test_class in test_classes}
			return test_tester_mapping





def        __UpperCAmelCase						(							lowerCamelCase_ :     int  )       ->  Tuple:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      get_model_classes(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Dict					  =      {
			    model_class: get_test_classes_for_model(lowerCamelCase_  ,							lowerCamelCase_  ) for model_class in model_classes
			}
			return model_test_mapping





def        __UpperCAmelCase						(							lowerCamelCase_ :     Any  )       ->  int:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      get_model_classes(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      {
			    model_class: get_tester_classes_for_model(lowerCamelCase_  ,							lowerCamelCase_  ) for model_class in model_classes
			}
			return model_to_tester_mapping





def        __UpperCAmelCase						(							lowerCamelCase_ :     Dict  )       ->  str:







			"""simple docstring"""





			if isinstance(lowerCamelCase_  ,							lowerCamelCase_  ):
						return o
			elif isinstance(lowerCamelCase_  ,							lowerCamelCase_  ):
						return o.__name__
			elif isinstance(lowerCamelCase_  ,							(list, tuple)  ):
						return [to_json(lowerCamelCase_  ) for x in o]
			elif isinstance(lowerCamelCase_  ,							lowerCamelCase_  ):
						return {to_json(lowerCamelCase_  ): to_json(lowerCamelCase_  ) for k, v in o.items()}
			else:
						return o










from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
    import tensorflow as tf

    from transformers import AutoTokenizer, TFAutoModelForSeqaSeqLM

@require_tf
@require_sentencepiece
@require_tokenizers
class   lowerCAmelCase				(   unittest.TestCase     ):
 @slow
 def 	A_      ( self    : int      )     ->      Optional[Any]:
     lowerCamelCase__       : Tuple   					=						TFAutoModelForSeqaSeqLM.from_pretrained('google/mt5-small'      )
     lowerCamelCase__       : Any   					=						AutoTokenizer.from_pretrained('google/mt5-small'      )

     lowerCamelCase__       : int   					=						tokenizer('Hello there'     ,	return_tensors='tf'      ).input_ids
     lowerCamelCase__       : int   					=						tokenizer('Hi I am'     ,	return_tensors='tf'      ).input_ids

     lowerCamelCase__       : List[str]   					=						model(UpperCAmelCase     ,	labels=UpperCAmelCase      ).loss
     lowerCamelCase__       : List[Any]   					=						-tf.math.reduce_mean(UpperCAmelCase      ).numpy()

     lowerCamelCase__       : Dict   					=						-2_1.2_2_8_1_6_8
     self.assertTrue(abs(mtf_score - EXPECTED_SCORE      ) < 2e-4      )





