



# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
a_    :  Tuple						  =		abspath(join(dirname(dirname(__file__)), 'src'))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)

def      __lowercase(						UpperCAmelCase__			):


      """simple docstring"""



      from diffusers.utils.testing_utils import pytest_addoption_shared

      pytest_addoption_shared(UpperCAmelCase__			)






def      __lowercase(						UpperCAmelCase__			):


      """simple docstring"""



      from diffusers.utils.testing_utils import pytest_terminal_summary_main

      lowerCamelCase             =		terminalreporter.config.getoption("--make-reports"			)
      if make_reports:
            pytest_terminal_summary_main(UpperCAmelCase__ , id=UpperCAmelCase__			)




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


a_    :  Tuple						  =		{'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechConfig']}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     a_    :  Union[str, Any]						  =		[
         'UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST',
         'UniSpeechForCTC',
         'UniSpeechForPreTraining',
         'UniSpeechForSequenceClassification',
         'UniSpeechModel',
         'UniSpeechPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_unispeech import (
              UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
              UniSpeechForCTC,
              UniSpeechForPreTraining,
              UniSpeechForSequenceClassification,
              UniSpeechModel,
              UniSpeechPreTrainedModel,
          )

else:
     import sys

     a_    :  Optional[Any]						  =		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)