






"""simple docstring"""



import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
    _UpperCamelCase		:  Optional[int]						=		[]

    _UpperCamelCase		:  int						=		os.path.join('tests', 'models', '**', 'test_modeling_*.py')
    _UpperCamelCase		:  Union[str, Any]						=		glob.glob(pattern)
    # TODO: deal with TF/Flax too
    _UpperCamelCase		:  Union[str, Any]						=		[
        x for x in test_files if not (x.startswith('test_modeling_tf_') or x.startswith('test_modeling_flax_'))
    ]

    for test_file in test_files:
        _UpperCamelCase		:  List[str]						=		get_tester_classes(test_file)
        for tester_class in tester_classes:
            # A few tester classes don't have `parent` parameter in `__init__`.
            # TODO: deal this better
            try:
                _UpperCamelCase		:  List[str]						=		tester_class(parent=None)
            except Exception:
                continue
            if hasattr(tester, 'get_config'):
                _UpperCamelCase		:  str						=		tester.get_config()
                for k, v in config.to_dict().items():
                    if isinstance(v, int):
                        _UpperCamelCase		:  int						=		None
                        if k in ["vocab_size"]:
                            _UpperCamelCase		:  Any						=		1_0_0
                        elif k in ["max_position_embeddings"]:
                            _UpperCamelCase		:  Tuple						=		1_2_8
                        elif k in ["hidden_size", "d_model"]:
                            _UpperCamelCase		:  str						=		4_0
                        elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
                            _UpperCamelCase		:  str						=		5
                        if target is not None and v > target:
                            failures.append(
                                F'''{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'''
                                F''' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'''
                                F''' than {target}.'''
                            )

    if len(failures) > 0:
        raise Exception(F'''There were {len(failures)} failures:\n''' + '\n'.join(failures))










"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCamelCase		:  str						=		{
    'configuration_wav2vec2_conformer': [
        'WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Wav2Vec2ConformerConfig',
    ],
}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase		:  str						=		[
        'WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'Wav2Vec2ConformerForAudioFrameClassification',
        'Wav2Vec2ConformerForCTC',
        'Wav2Vec2ConformerForPreTraining',
        'Wav2Vec2ConformerForSequenceClassification',
        'Wav2Vec2ConformerForXVector',
        'Wav2Vec2ConformerModel',
        'Wav2Vec2ConformerPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_wavaveca_conformer import (
        WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        WavaVecaConformerConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_wavaveca_conformer import (
            WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            WavaVecaConformerForAudioFrameClassification,
            WavaVecaConformerForCTC,
            WavaVecaConformerForPreTraining,
            WavaVecaConformerForSequenceClassification,
            WavaVecaConformerForXVector,
            WavaVecaConformerModel,
            WavaVecaConformerPreTrainedModel,
        )

else:
    import sys

    _UpperCamelCase		:  Union[str, Any]						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


