






"""simple docstring"""



from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCamelCase		:  Optional[int]						=		logging.get_logger(__name__)

_UpperCamelCase		:  Dict						=		{
    'ZinengTang/tvlt-base': 'https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json',
}

class 	a					(       a_     ):
    UpperCAmelCase_			:					int     					="tvlt"







    def __init__(      self							,		_lowerCamelCase=2_2_4							,		_lowerCamelCase=2_0_4_8							,		_lowerCamelCase=1_2_8							,		_lowerCamelCase=[1_6, 1_6]							,		_lowerCamelCase=[1_6, 1_6]							,		_lowerCamelCase=3							,		_lowerCamelCase=1							,		_lowerCamelCase=8							,		_lowerCamelCase=7_6_8							,		_lowerCamelCase=1_2							,		_lowerCamelCase=1_2							,		_lowerCamelCase=3_0_7_2							,		_lowerCamelCase="gelu"							,		_lowerCamelCase=0.0							,		_lowerCamelCase=0.0							,		_lowerCamelCase=0.0_2							,		_lowerCamelCase=1e-6							,		_lowerCamelCase=True							,		_lowerCamelCase=False							,		_lowerCamelCase=1_6							,		_lowerCamelCase=5_1_2							,		_lowerCamelCase=8							,		_lowerCamelCase=2_0_4_8							,		_lowerCamelCase=0.7_5							,		_lowerCamelCase=0.1_5							,		_lowerCamelCase="frame-level"							,		_lowerCamelCase=True							,		_lowerCamelCase=True							,		_lowerCamelCase="classification"							,		**_lowerCamelCase							,		):
      super().__init__(**lowercase__	)

      if audio_mask_type not in ("frame-level", "patch_level"):
        raise ValueError(
            'audio_mask_type must be one of two acceptable strategies - {\'frame_level\', \'patch-level\') '
            F'got {audio_mask_type}'	)

      lowercase							   =	image_size
      lowercase							   =	spectrogram_length
      lowercase							   =	frequency_length
      lowercase							   =	image_patch_size
      lowercase							   =	audio_patch_size
      lowercase							   =	num_image_channels
      lowercase							   =	num_audio_channels
      lowercase							   =	num_frames

      lowercase							   =	hidden_size
      lowercase							   =	num_hidden_layers
      lowercase							   =	num_attention_heads
      lowercase							   =	intermediate_size
      lowercase							   =	hidden_act
      lowercase							   =	hidden_dropout_prob
      lowercase							   =	attention_probs_dropout_prob
      lowercase							   =	initializer_range
      lowercase							   =	layer_norm_eps
      lowercase							   =	qkv_bias
      lowercase							   =	use_mean_pooling

      lowercase							   =	decoder_num_attention_heads
      lowercase							   =	decoder_hidden_size
      lowercase							   =	decoder_num_hidden_layers
      lowercase							   =	decoder_intermediate_size
      lowercase							   =	pixel_mask_ratio
      lowercase							   =	audio_mask_ratio
      lowercase							   =	audio_mask_type

      lowercase							   =	task_matching
      lowercase							   =	task_mae
      lowercase							   =	loss_type










"""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__)


