





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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						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.'''					)
       _UpperCamelCase              =						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.'''					)

       _UpperCamelCase              =						components[:-1] + [test_fn.replace('''.py'''    ,       ''''''					)]
       _UpperCamelCase              =						'''.'''.join(lowerCAmelCase					)

       return test_module_path


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						get_module_path(lowerCAmelCase					)
       _UpperCamelCase              =						importlib.import_module(lowerCAmelCase					)

       return test_module


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						[]
       _UpperCamelCase              =						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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						[]
       _UpperCamelCase              =						get_test_module(lowerCAmelCase					)
       for attr in dir(lowerCAmelCase					):
              _UpperCamelCase              =						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).
              _UpperCamelCase              =						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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						get_test_classes(lowerCAmelCase					)
       _UpperCamelCase              =						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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						test_class()
       if hasattr(lowerCAmelCase    ,       '''setUp'''					):
              test.setUp()

       _UpperCamelCase              =						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:
                     _UpperCamelCase              =						test.model_tester.__class__

       return model_tester


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase					):
       _UpperCamelCase              =						get_test_classes(lowerCAmelCase					)

       _UpperCamelCase              =						[]
       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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase					):
       _UpperCamelCase              =						get_test_classes_for_model(lowerCAmelCase    ,       lowerCAmelCase					)

       _UpperCamelCase              =						[]
       for test_class in test_classes:
              _UpperCamelCase              =						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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						get_test_classes(lowerCAmelCase					)
       _UpperCamelCase              =						{test_class: get_model_tester_from_test_class(lowerCAmelCase					) for test_class in test_classes}
       return test_tester_mapping


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						get_model_classes(lowerCAmelCase					)
       _UpperCamelCase              =						{
           model_class: get_test_classes_for_model(lowerCAmelCase    ,       lowerCAmelCase					) for model_class in model_classes
       }
       return model_test_mapping


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						get_model_classes(lowerCAmelCase					)
       _UpperCamelCase              =						{
           model_class: get_tester_classes_for_model(lowerCAmelCase    ,       lowerCAmelCase					) for model_class in model_classes
       }
       return model_to_tester_mapping


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       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













import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
       import torch

       from transformers.generation import (
           MaxLengthCriteria,
           MaxNewTokensCriteria,
           MaxTimeCriteria,
           StoppingCriteriaList,
           validate_stopping_criteria,
       )

@require_torch
class  __A(						unittest.TestCase ):

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						3
            _UpperCamelCase              =						250

            _UpperCamelCase              =						ids_tensor((batch_size, length),       A      )
            _UpperCamelCase              =						torch.ones((batch_size, length),       device=A,       dtype=torch.float      ) / length
            return input_ids, scores

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(5      )

            _UpperCamelCase              =						StoppingCriteriaList(
                [
                    MaxLengthCriteria(max_length=10      ),
                    MaxTimeCriteria(max_time=0.1      ),
                ]      )

            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(9      )
            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(10      )
            self.assertTrue(criteria(A,       A      )      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						MaxLengthCriteria(max_length=10      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(5      )
            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(9      )
            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(10      )
            self.assertTrue(criteria(A,       A      )      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						MaxNewTokensCriteria(start_length=5,       max_new_tokens=5      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(5      )
            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(9      )
            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(10      )
            self.assertTrue(criteria(A,       A      )      )

            _UpperCamelCase              =						StoppingCriteriaList([criteria]      )
            self.assertEqual(criteria_list.max_length,       10      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase       ,		_UpperCamelCase              =						self._get_tensors(5      )

            _UpperCamelCase              =						MaxTimeCriteria(max_time=0.1      )
            self.assertFalse(criteria(A,       A      )      )

            _UpperCamelCase              =						MaxTimeCriteria(max_time=0.1,       initial_timestamp=time.time() - 0.2      )
            self.assertTrue(criteria(A,       A      )      )



     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10      )]      ),       10      )

            with self.assertWarns(A      ):
                   validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10      )]      ),       11      )

            _UpperCamelCase              =						validate_stopping_criteria(StoppingCriteriaList(),       11      )

            self.assertEqual(len(A      ),       1      )






