

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


_lowerCamelCase							=logging.get_logger(__name__)

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



class 						a_			(				lowerCamelCase_	):



      """simple docstring"""







      __UpperCAmelCase     						= 'tvlt'
      def __init__( self	:				Union[str, Any]     ,snake_case	:				Optional[Any]=224     ,snake_case	:				List[Any]=2048     ,snake_case	:				List[Any]=128     ,snake_case	:				str=[16, 16]     ,snake_case	:				Dict=[16, 16]     ,snake_case	:				Optional[int]=3     ,snake_case	:				Tuple=1     ,snake_case	:				Dict=8     ,snake_case	:				List[Any]=768     ,snake_case	:				Tuple=12     ,snake_case	:				Dict=12     ,snake_case	:				Union[str, Any]=3072     ,snake_case	:				Any="gelu"     ,snake_case	:				List[str]=0.0     ,snake_case	:				Optional[Any]=0.0     ,snake_case	:				Optional[int]=0.02     ,snake_case	:				Optional[Any]=1e-6     ,snake_case	:				int=True     ,snake_case	:				Tuple=False     ,snake_case	:				List[Any]=16     ,snake_case	:				int=512     ,snake_case	:				List[Any]=8     ,snake_case	:				Optional[Any]=2048     ,snake_case	:				int=0.75     ,snake_case	:				int=0.15     ,snake_case	:				List[str]="frame-level"     ,snake_case	:				Any=True     ,snake_case	:				Dict=True     ,snake_case	:				Any="classification"     ,**snake_case	:				Tuple     ,):
           super().__init__(**UpperCamelCase_							)

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

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

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

           SCREAMING_SNAKE_CASE 		=task_matching
           SCREAMING_SNAKE_CASE 		=task_mae
           SCREAMING_SNAKE_CASE 		=loss_type






'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A					:     List[Any]      ={'''configuration_umt5''': ['''UMT5Config''', '''UMT5OnnxConfig''']}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_A					:     Optional[Any]      =[
		    '''UMT5EncoderModel''',
		    '''UMT5ForConditionalGeneration''',
		    '''UMT5ForQuestionAnswering''',
		    '''UMT5Model''',
		    '''UMT5PreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_umta import UMTaConfig, UMTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_umta import (
				    UMTaEncoderModel,
				    UMTaForConditionalGeneration,
				    UMTaForQuestionAnswering,
				    UMTaModel,
				    UMTaPreTrainedModel,
				)
else:
		import sys

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