

"""simple docstring"""




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


__A	:       Tuple        =						logging.get_logger(__name__)

__A	:       Union[str, Any]        =						{
    'ZinengTang/tvlt-base': 'https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json',
}





class      __UpperCamelCase					(  _A		):
		SCREAMING_SNAKE_CASE														=       "tvlt"


		def __init__(self					:						str	,	__SCREAMING_SNAKE_CASE					:						Dict=2_2_4	,	__SCREAMING_SNAKE_CASE					:						Union[str, Any]=2_0_4_8	,	__SCREAMING_SNAKE_CASE					:						Any=1_2_8	,	__SCREAMING_SNAKE_CASE					:						Tuple=[1_6, 1_6]	,	__SCREAMING_SNAKE_CASE					:						List[str]=[1_6, 1_6]	,	__SCREAMING_SNAKE_CASE					:						Optional[int]=3	,	__SCREAMING_SNAKE_CASE					:						Union[str, Any]=1	,	__SCREAMING_SNAKE_CASE					:						Tuple=8	,	__SCREAMING_SNAKE_CASE					:						Optional[Any]=7_6_8	,	__SCREAMING_SNAKE_CASE					:						Optional[Any]=1_2	,	__SCREAMING_SNAKE_CASE					:						str=1_2	,	__SCREAMING_SNAKE_CASE					:						Optional[Any]=3_0_7_2	,	__SCREAMING_SNAKE_CASE					:						Union[str, Any]="gelu"	,	__SCREAMING_SNAKE_CASE					:						Optional[int]=0.0	,	__SCREAMING_SNAKE_CASE					:						int=0.0	,	__SCREAMING_SNAKE_CASE					:						Tuple=0.0_2	,	__SCREAMING_SNAKE_CASE					:						Any=1E-6	,	__SCREAMING_SNAKE_CASE					:						Optional[Any]=True	,	__SCREAMING_SNAKE_CASE					:						Optional[Any]=False	,	__SCREAMING_SNAKE_CASE					:						Dict=1_6	,	__SCREAMING_SNAKE_CASE					:						Dict=5_1_2	,	__SCREAMING_SNAKE_CASE					:						List[Any]=8	,	__SCREAMING_SNAKE_CASE					:						List[Any]=2_0_4_8	,	__SCREAMING_SNAKE_CASE					:						Any=0.7_5	,	__SCREAMING_SNAKE_CASE					:						List[str]=0.1_5	,	__SCREAMING_SNAKE_CASE					:						Union[str, Any]="frame-level"	,	__SCREAMING_SNAKE_CASE					:						Union[str, Any]=True	,	__SCREAMING_SNAKE_CASE					:						Dict=True	,	__SCREAMING_SNAKE_CASE					:						Union[str, Any]="classification"	,	**__SCREAMING_SNAKE_CASE					:						Tuple	,	):
							super().__init__(**__SCREAMING_SNAKE_CASE)

							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}""")

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

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

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

							A     =   task_matching
							A     =   task_mae
							A     =   loss_type







"""simple docstring"""
import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property




class  _snake_case	(    unittest.TestCase							):






							@cached_property
							def 				__lowercase	(       self    :      str     ):






												"""simple docstring"""



												return BlenderbotTokenizer.from_pretrained("""facebook/blenderbot-3B"""     )






							@cached_property
							def 				__lowercase	(       self    :      str     ):






												"""simple docstring"""



												return BlenderbotTokenizerFast.from_pretrained("""facebook/blenderbot-3B"""     )






							def 				__lowercase	(       self    :      int     ):






												"""simple docstring"""



												__a:    Optional[int]		     =       self.tokenizer_ab
												__a:    Union[str, Any]		     =       """ I am a small frog."""
												__a:    str		     =       tok([src_text]    ,			padding=snake_case__    ,			truncation=snake_case__     )["""input_ids"""]
												__a:    Optional[Any]		     =       tok.batch_decode(snake_case__    ,			skip_special_tokens=snake_case__    ,			clean_up_tokenization_spaces=snake_case__     )[0]
												assert src_text == decoded






							def 				__lowercase	(       self    :      List[Any]     ):






												"""simple docstring"""



												__a:    str		     =       self.rust_tokenizer_ab
												__a:    Optional[Any]		     =       """ I am a small frog."""
												__a:    str		     =       tok([src_text]    ,			padding=snake_case__    ,			truncation=snake_case__     )["""input_ids"""]
												__a:    Union[str, Any]		     =       tok.batch_decode(snake_case__    ,			skip_special_tokens=snake_case__    ,			clean_up_tokenization_spaces=snake_case__     )[0]
												assert src_text == decoded






							def 				__lowercase	(       self    :      List[str]     ):






												"""simple docstring"""



												assert self.tokenizer_ab.add_prefix_space
												assert self.tokenizer_ab([""" Sam""", """Sam"""]     ).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]






							def 				__lowercase	(       self    :      Any     ):






												"""simple docstring"""



												assert self.rust_tokenizer_ab.add_prefix_space
												assert self.rust_tokenizer_ab([""" Sam""", """Sam"""]     ).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]
