from typing import TYPE_CHECKING

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


lowerCAmelCase__					=				{
    "agents": ["Agent", "AzureOpenAiAgent", "HfAgent", "LocalAgent", "OpenAiAgent"],
    "base": ["PipelineTool", "RemoteTool", "Tool", "launch_gradio_demo", "load_tool"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__					=				["DocumentQuestionAnsweringTool"]
				lowerCAmelCase__					=				["ImageCaptioningTool"]
				lowerCAmelCase__					=				["ImageQuestionAnsweringTool"]
				lowerCAmelCase__					=				["ImageSegmentationTool"]
				lowerCAmelCase__					=				["SpeechToTextTool"]
				lowerCAmelCase__					=				["TextClassificationTool"]
				lowerCAmelCase__					=				["TextQuestionAnsweringTool"]
				lowerCAmelCase__					=				["TextSummarizationTool"]
				lowerCAmelCase__					=				["TextToSpeechTool"]
				lowerCAmelCase__					=				["TranslationTool"]

if TYPE_CHECKING:
				from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
				from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .document_question_answering import DocumentQuestionAnsweringTool
								from .image_captioning import ImageCaptioningTool
								from .image_question_answering import ImageQuestionAnsweringTool
								from .image_segmentation import ImageSegmentationTool
								from .speech_to_text import SpeechToTextTool
								from .text_classification import TextClassificationTool
								from .text_question_answering import TextQuestionAnsweringTool
								from .text_summarization import TextSummarizationTool
								from .text_to_speech import TextToSpeechTool
								from .translation import TranslationTool
else:
				import sys

				lowerCAmelCase__					=				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

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_				(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 UpperCAmelCase_							=      'tvlt'




 def __init__(    self      :						Dict    ,					lowercase__      :						str=224    ,					lowercase__      :						int=2_048    ,					lowercase__      :						int=128    ,					lowercase__      :						Optional[Any]=[16, 16]    ,					lowercase__      :						List[str]=[16, 16]    ,					lowercase__      :						Optional[int]=3    ,					lowercase__      :						Tuple=1    ,					lowercase__      :						Union[str, Any]=8    ,					lowercase__      :						int=768    ,					lowercase__      :						Tuple=12    ,					lowercase__      :						List[str]=12    ,					lowercase__      :						Union[str, Any]=3_072    ,					lowercase__      :						Union[str, Any]="gelu"    ,					lowercase__      :						Dict=0.0    ,					lowercase__      :						Tuple=0.0    ,					lowercase__      :						Union[str, Any]=0.02    ,					lowercase__      :						Any=1e-6    ,					lowercase__      :						Dict=True    ,					lowercase__      :						int=False    ,					lowercase__      :						Tuple=16    ,					lowercase__      :						Optional[int]=512    ,					lowercase__      :						int=8    ,					lowercase__      :						List[Any]=2_048    ,					lowercase__      :						Optional[int]=0.75    ,					lowercase__      :						Union[str, Any]=0.15    ,					lowercase__      :						List[str]="frame-level"    ,					lowercase__      :						Dict=True    ,					lowercase__      :						Tuple=True    ,					lowercase__      :						Any="classification"    ,					**lowercase__      :						Union[str, Any]    ,					):







        '''simple docstring'''



        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}""")

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

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

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

        lowerCAmelCase__  			=      task_matching
        lowerCAmelCase__  			=      task_mae
        lowerCAmelCase__  			=      loss_type
