from __future__ import annotations

from queue import Queue
class        a_				:






	'''simple docstring'''






	def __init__(    self      :						Optional[Any]):







								'''simple docstring'''



								lowerCAmelCase__  			=      {}




	def 	__snake_case		(    self      :						int):







								'''simple docstring'''



								for i in self.vertices:
															print(UpperCAmelCase_    ,					' : '    ,					' -> '.join([str(UpperCAmelCase_) for j in self.vertices[i]]))




	def 	__snake_case		(    self      :						List[str]    ,					lowercase__      :						int    ,					lowercase__      :						int):







								'''simple docstring'''



								if from_vertex in self.vertices:
															self.vertices[from_vertex].append(UpperCAmelCase_)
								else:
															lowerCAmelCase__  			=      [to_vertex]




	def 	__snake_case		(    self      :						List[Any]    ,					lowercase__      :						int):







								'''simple docstring'''



								lowerCAmelCase__  			=      set()

								# create a first in first out queue to store all the vertices for BFS
								lowerCAmelCase__  			=      Queue()

								# mark the source node as visited and enqueue it
								visited.add(UpperCAmelCase_)
								queue.put(UpperCAmelCase_)

								while not queue.empty():
															lowerCAmelCase__  			=      queue.get()

															# loop through all adjacent vertex and enqueue it if not yet visited
															for adjacent_vertex in self.vertices[vertex]:
																						if adjacent_vertex not in visited:
																													queue.put(UpperCAmelCase_)
																													visited.add(UpperCAmelCase_)
								return visited


if __name__ == "__main__":
				from doctest import testmod

				testmod(verbose=True)

				lowerCAmelCase__					=				Graph()
				g.add_edge(0, 1)
				g.add_edge(0, 2)
				g.add_edge(1, 2)
				g.add_edge(2, 0)
				g.add_edge(2, 3)
				g.add_edge(3, 3)

				g.print_graph()
				# 0  :  1 -> 2
				# 1  :  2
				# 2  :  0 -> 3
				# 3  :  3

				assert sorted(g.bfs(2)) == [0, 1, 2, 3]

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
