



import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
			from .tokenization_reformer import ReformerTokenizer
else:
			UpperCamelCase__			=    None


UpperCamelCase__			=    logging.get_logger(__name__)


UpperCamelCase__			=    '▁'

UpperCamelCase__			=    {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase__			=    {
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

UpperCamelCase__			=    {
    'google/reformer-crime-and-punishment': 52_42_88,
}
class       _lowerCAmelCase (			_UpperCAmelCase      ):






			"""simple docstring"""





			lowercase__   :	Tuple  			=      VOCAB_FILES_NAMES
			lowercase__   :	Any  			=      PRETRAINED_VOCAB_FILES_MAP
			lowercase__   :	Any  			=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowercase__   :	List[Any]  			=      ['''input_ids''', '''attention_mask''']
			lowercase__   :	int  			=      ReformerTokenizer





			def __init__(					self						:							Tuple      ,  lowercase						:							List[Any]=None      ,  lowercase						:							Any=None      ,  lowercase						:							Tuple="</s>"      ,  lowercase						:							Dict="<unk>"      ,  lowercase						:							List[Any]=[]      ,  **lowercase						:							str      ,  )    ->       Optional[Any]:
									"""simple docstring"""







									super().__init__(
									    _UpperCAmelCase      ,  tokenizer_file=_UpperCAmelCase      ,  eos_token=_UpperCAmelCase      ,  unk_token=_UpperCAmelCase      ,  additional_special_tokens=_UpperCAmelCase      ,  **_UpperCAmelCase      ,  )

									__lowercase											=					vocab_file
									__lowercase											=					False if not self.vocab_file else True







			def 		snake_case__      (					self						:							str      ,  lowercase						:							str      ,  lowercase						:							Union[str, Any] = None )    ->       Tuple[str]:
									"""simple docstring"""







									if not self.can_save_slow_tokenizer:
															raise ValueError(
															    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
															    """tokenizer.""" )

									if not os.path.isdir(_UpperCAmelCase ):
															logger.error(F"Vocabulary path ({save_directory}) should be a directory" )
															return
									__lowercase											=					os.path.join(
									    _UpperCAmelCase      ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

									if os.path.abspath(self.vocab_file ) != os.path.abspath(_UpperCAmelCase ):
															copyfile(self.vocab_file      ,  _UpperCAmelCase )

									return (out_vocab_file,)













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


_UpperCAmelCase					:						Any         =     logging.get_logger(__name__)

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


class 		lowerCAmelCase_				(  UpperCamelCase ):
     __lowerCamelCase       :    Any 	=     '''tvlt'''





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

        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