




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


_A							    =	logging.get_logger(__name__)

_A							    =	{
    """ZinengTang/tvlt-base""": """https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json""",
}


class 							_lowerCAmelCase		(     lowerCAmelCase__	):
				lowerCamelCase__									=    'tvlt'




				def __init__( self		,		snake_case_=224		,		snake_case_=2_048		,		snake_case_=128		,		snake_case_=[16, 16]		,		snake_case_=[16, 16]		,		snake_case_=3		,		snake_case_=1		,		snake_case_=8		,		snake_case_=768		,		snake_case_=12		,		snake_case_=12		,		snake_case_=3_072		,		snake_case_="gelu"		,		snake_case_=0.0		,		snake_case_=0.0		,		snake_case_=0.02		,		snake_case_=1E-6		,		snake_case_=True		,		snake_case_=False		,		snake_case_=16		,		snake_case_=512		,		snake_case_=8		,		snake_case_=2_048		,		snake_case_=0.75		,		snake_case_=0.15		,		snake_case_="frame-level"		,		snake_case_=True		,		snake_case_=True		,		snake_case_="classification"		,		**snake_case_		,		)    ->      Any:
											super().__init__(**_lowerCamelCase							)

											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}'							)

											SCREAMING_SNAKE_CASE			: int	     =image_size
											SCREAMING_SNAKE_CASE			: List[str]	     =spectrogram_length
											SCREAMING_SNAKE_CASE			: str	     =frequency_length
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =image_patch_size
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =audio_patch_size
											SCREAMING_SNAKE_CASE			: List[str]	     =num_image_channels
											SCREAMING_SNAKE_CASE			: Tuple	     =num_audio_channels
											SCREAMING_SNAKE_CASE			: List[Any]	     =num_frames

											SCREAMING_SNAKE_CASE			: Dict	     =hidden_size
											SCREAMING_SNAKE_CASE			: Tuple	     =num_hidden_layers
											SCREAMING_SNAKE_CASE			: List[Any]	     =num_attention_heads
											SCREAMING_SNAKE_CASE			: Any	     =intermediate_size
											SCREAMING_SNAKE_CASE			: Any	     =hidden_act
											SCREAMING_SNAKE_CASE			: Dict	     =hidden_dropout_prob
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =attention_probs_dropout_prob
											SCREAMING_SNAKE_CASE			: Optional[int]	     =initializer_range
											SCREAMING_SNAKE_CASE			: int	     =layer_norm_eps
											SCREAMING_SNAKE_CASE			: Optional[int]	     =qkv_bias
											SCREAMING_SNAKE_CASE			: int	     =use_mean_pooling

											SCREAMING_SNAKE_CASE			: int	     =decoder_num_attention_heads
											SCREAMING_SNAKE_CASE			: int	     =decoder_hidden_size
											SCREAMING_SNAKE_CASE			: int	     =decoder_num_hidden_layers
											SCREAMING_SNAKE_CASE			: Dict	     =decoder_intermediate_size
											SCREAMING_SNAKE_CASE			: int	     =pixel_mask_ratio
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =audio_mask_ratio
											SCREAMING_SNAKE_CASE			: Union[str, Any]	     =audio_mask_type

											SCREAMING_SNAKE_CASE			: Tuple	     =task_matching
											SCREAMING_SNAKE_CASE			: str	     =task_mae
											SCREAMING_SNAKE_CASE			: str	     =loss_type












from typing import TYPE_CHECKING

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


_A							    =	{"""configuration_regnet""": ["""REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RegNetConfig"""]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_A							    =	[
							    """REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """RegNetForImageClassification""",
							    """RegNetModel""",
							    """RegNetPreTrainedModel""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_A							    =	[
							    """TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFRegNetForImageClassification""",
							    """TFRegNetModel""",
							    """TFRegNetPreTrainedModel""",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_A							    =	[
							    """FlaxRegNetForImageClassification""",
							    """FlaxRegNetModel""",
							    """FlaxRegNetPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_regnet import (
														    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    RegNetForImageClassification,
														    RegNetModel,
														    RegNetPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_regnet import (
														    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFRegNetForImageClassification,
														    TFRegNetModel,
														    TFRegNetPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_regnet import (
														    FlaxRegNetForImageClassification,
														    FlaxRegNetModel,
														    FlaxRegNetPreTrainedModel,
														)


else:
							import sys

							_A							    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)






