




'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


A							:				Dict			     =	logging.get_logger(__name__)

A							:				List[Any]			     =	{
    """ZinengTang/tvlt-base""": """https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json""",
}






class 	SCREAMING_SNAKE_CASE(    __A					):
       snake_case_			:					Tuple   = """tvlt"""

       def __init__(   self ,		lowerCamelCase__=224 ,		lowerCamelCase__=2048 ,		lowerCamelCase__=128 ,		lowerCamelCase__=[16, 16] ,		lowerCamelCase__=[16, 16] ,		lowerCamelCase__=3 ,		lowerCamelCase__=1 ,		lowerCamelCase__=8 ,		lowerCamelCase__=768 ,		lowerCamelCase__=12 ,		lowerCamelCase__=12 ,		lowerCamelCase__=3072 ,		lowerCamelCase__="gelu" ,		lowerCamelCase__=0.0 ,		lowerCamelCase__=0.0 ,		lowerCamelCase__=0.02 ,		lowerCamelCase__=1E-6 ,		lowerCamelCase__=True ,		lowerCamelCase__=False ,		lowerCamelCase__=16 ,		lowerCamelCase__=512 ,		lowerCamelCase__=8 ,		lowerCamelCase__=2048 ,		lowerCamelCase__=0.75 ,		lowerCamelCase__=0.15 ,		lowerCamelCase__="frame-level" ,		lowerCamelCase__=True ,		lowerCamelCase__=True ,		lowerCamelCase__="classification" ,		**lowerCamelCase__ ,		)   -> List[Any]:

           """simple docstring"""



           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}'					)

           __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_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A							:				Tuple			     =	{
    """configuration_dpr""": ["""DPR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPRConfig"""],
    """tokenization_dpr""": [
        """DPRContextEncoderTokenizer""",
        """DPRQuestionEncoderTokenizer""",
        """DPRReaderOutput""",
        """DPRReaderTokenizer""",
    ],
}


try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A							:				str			     =	[
      """DPRContextEncoderTokenizerFast""",
      """DPRQuestionEncoderTokenizerFast""",
      """DPRReaderTokenizerFast""",
  ]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A							:				Tuple			     =	[
      """DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DPRContextEncoder""",
      """DPRPretrainedContextEncoder""",
      """DPRPreTrainedModel""",
      """DPRPretrainedQuestionEncoder""",
      """DPRPretrainedReader""",
      """DPRQuestionEncoder""",
      """DPRReader""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A							:				Tuple			     =	[
      """TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFDPRContextEncoder""",
      """TFDPRPretrainedContextEncoder""",
      """TFDPRPretrainedQuestionEncoder""",
      """TFDPRPretrainedReader""",
      """TFDPRQuestionEncoder""",
      """TFDPRReader""",
  ]


if TYPE_CHECKING:
  from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
  from .tokenization_dpr import (
      DPRContextEncoderTokenizer,
      DPRQuestionEncoderTokenizer,
      DPRReaderOutput,
      DPRReaderTokenizer,
  )

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_dpr_fast import (
        DPRContextEncoderTokenizerFast,
        DPRQuestionEncoderTokenizerFast,
        DPRReaderTokenizerFast,
    )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_dpr import (
        DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPRContextEncoder,
        DPRPretrainedContextEncoder,
        DPRPreTrainedModel,
        DPRPretrainedQuestionEncoder,
        DPRPretrainedReader,
        DPRQuestionEncoder,
        DPRReader,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_dpr import (
        TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFDPRContextEncoder,
        TFDPRPretrainedContextEncoder,
        TFDPRPretrainedQuestionEncoder,
        TFDPRPretrainedReader,
        TFDPRQuestionEncoder,
        TFDPRReader,
    )

else:
  import sys

  A							:				int			     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




