

import functools
import operator

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


lowerCAmelCase						:   Dict										=    logging.get_logger(__name__)

lowerCAmelCase						:   str										=    {
    '''facebook/hubert-base-ls960''': '''https://huggingface.co/facebook/hubert-base-ls960/resolve/main/config.json''',
    # See all Hubert models at https://huggingface.co/models?filter=hubert
}
class     SCREAMING_SNAKE_CASE__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     Tuple				    =       '''hubert'''

       def __init__(						self       :						Union[str, Any]    ,		lowerCAmelCase__       :						List[Any]=32    ,		lowerCAmelCase__       :						Any=768    ,		lowerCAmelCase__       :						List[Any]=12    ,		lowerCAmelCase__       :						Tuple=12    ,		lowerCAmelCase__       :						Optional[int]=3072    ,		lowerCAmelCase__       :						Dict="gelu"    ,		lowerCAmelCase__       :						List[str]=0.1    ,		lowerCAmelCase__       :						str=0.1    ,		lowerCAmelCase__       :						List[str]=0.1    ,		lowerCAmelCase__       :						int=True    ,		lowerCAmelCase__       :						Tuple=0.0    ,		lowerCAmelCase__       :						Union[str, Any]=0.1    ,		lowerCAmelCase__       :						Dict=0.1    ,		lowerCAmelCase__       :						int=0.02    ,		lowerCAmelCase__       :						Optional[int]=1E-5    ,		lowerCAmelCase__       :						List[str]="group"    ,		lowerCAmelCase__       :						List[str]="gelu"    ,		lowerCAmelCase__       :						Any=(512, 512, 512, 512, 512, 512, 512)    ,		lowerCAmelCase__       :						str=(5, 2, 2, 2, 2, 2, 2)    ,		lowerCAmelCase__       :						Union[str, Any]=(10, 3, 3, 3, 3, 2, 2)    ,		lowerCAmelCase__       :						Optional[Any]=False    ,		lowerCAmelCase__       :						Dict=128    ,		lowerCAmelCase__       :						List[Any]=16    ,		lowerCAmelCase__       :						Optional[Any]=False    ,		lowerCAmelCase__       :						Optional[int]=True    ,		lowerCAmelCase__       :						List[Any]=0.05    ,		lowerCAmelCase__       :						Any=10    ,		lowerCAmelCase__       :						Dict=2    ,		lowerCAmelCase__       :						Dict=0.0    ,		lowerCAmelCase__       :						Tuple=10    ,		lowerCAmelCase__       :						List[str]=0    ,		lowerCAmelCase__       :						int="sum"    ,		lowerCAmelCase__       :						Optional[Any]=False    ,		lowerCAmelCase__       :						List[Any]=False    ,		lowerCAmelCase__       :						int=256    ,		lowerCAmelCase__       :						List[Any]=0    ,		lowerCAmelCase__       :						Union[str, Any]=1    ,		lowerCAmelCase__       :						Tuple=2    ,		**lowerCAmelCase__       :						str    ,		)			->    Union[str, Any]:
             super().__init__(**lowerCAmelCase__    ,		pad_token_id=lowerCAmelCase__    ,		bos_token_id=lowerCAmelCase__    ,		eos_token_id=lowerCAmelCase__							)
             snake_case__					=   hidden_size
             snake_case__					=   feat_extract_norm
             snake_case__					=   feat_extract_activation
             snake_case__					=   list(lowerCAmelCase__							)
             snake_case__					=   list(lowerCAmelCase__							)
             snake_case__					=   list(lowerCAmelCase__							)
             snake_case__					=   conv_bias
             snake_case__					=   num_conv_pos_embeddings
             snake_case__					=   num_conv_pos_embedding_groups
             snake_case__					=   len(self.conv_dim							)
             snake_case__					=   num_hidden_layers
             snake_case__					=   intermediate_size
             snake_case__					=   hidden_act
             snake_case__					=   num_attention_heads
             snake_case__					=   hidden_dropout
             snake_case__					=   attention_dropout
             snake_case__					=   activation_dropout
             snake_case__					=   feat_proj_layer_norm
             snake_case__					=   feat_proj_dropout
             snake_case__					=   final_dropout
             snake_case__					=   layerdrop
             snake_case__					=   layer_norm_eps
             snake_case__					=   initializer_range
             snake_case__					=   vocab_size
             snake_case__					=   do_stable_layer_norm
             snake_case__					=   use_weighted_layer_sum
             snake_case__					=   classifier_proj_size

             if (
                 (len(self.conv_stride							) != self.num_feat_extract_layers)
                 or (len(self.conv_kernel							) != self.num_feat_extract_layers)
                 or (len(self.conv_dim							) != self.num_feat_extract_layers)
             ):
                   raise ValueError(
                       """Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="""
                       """ `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="""
                       f''' {len(self.conv_dim							)}`, `len(config.conv_stride) = {len(self.conv_stride							)}`,'''
                       f''' `len(config.conv_kernel) = {len(self.conv_kernel							)}`.'''							)

             # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
             snake_case__					=   apply_spec_augment
             snake_case__					=   mask_time_prob
             snake_case__					=   mask_time_length
             snake_case__					=   mask_time_min_masks
             snake_case__					=   mask_feature_prob
             snake_case__					=   mask_feature_length
             snake_case__					=   mask_feature_min_masks

             # ctc loss
             snake_case__					=   ctc_loss_reduction
             snake_case__					=   ctc_zero_infinity

       @property
       def UpperCAmelCase_						(						self       :						Union[str, Any]							)			->    Tuple:
             return functools.reduce(operator.mul    ,		self.conv_stride    ,		1							)









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:
       lowerCAmelCase						:   Union[str, Any]										=    None


lowerCAmelCase						:   str										=    logging.get_logger(__name__)


lowerCAmelCase						:   Any										=    '''▁'''

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

lowerCAmelCase						:   Optional[Any]										=    {
    '''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'''
        )
    },
}

lowerCAmelCase						:   Union[str, Any]										=    {
    '''google/reformer-crime-and-punishment''': 52_4288,
}
class     SCREAMING_SNAKE_CASE__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     Union[str, Any]				    =       VOCAB_FILES_NAMES
       UpperCamelCase__ :     str				    =       PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase__ :     str				    =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase__ :     str				    =       ['''input_ids''', '''attention_mask''']
       UpperCamelCase__ :     Optional[Any]				    =       ReformerTokenizer

       def __init__(						self       :						List[str]    ,		lowerCAmelCase__       :						Tuple=None    ,		lowerCAmelCase__       :						Optional[Any]=None    ,		lowerCAmelCase__       :						Dict="</s>"    ,		lowerCAmelCase__       :						Tuple="<unk>"    ,		lowerCAmelCase__       :						Dict=[]    ,		**lowerCAmelCase__       :						Optional[Any]    ,		)			->    Dict:
             super().__init__(
                 lowerCAmelCase__    ,		tokenizer_file=lowerCAmelCase__    ,		eos_token=lowerCAmelCase__    ,		unk_token=lowerCAmelCase__    ,		additional_special_tokens=lowerCAmelCase__    ,		**lowerCAmelCase__    ,		)

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

       def UpperCAmelCase_						(						self       :						int    ,		lowerCAmelCase__       :						str    ,		lowerCAmelCase__       :						Optional[str] = None							)			->    Tuple[str]:
             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(lowerCAmelCase__							):
                   logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''							)
                   return
             snake_case__					=   os.path.join(
                 lowerCAmelCase__    ,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)

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

             return (out_vocab_file,)






