"""simple docstring"""







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_    :    Union[str, Any]											=						None


UpperCamelCase_    :    Tuple											=						logging.get_logger(__name__)


UpperCamelCase_    :    List[Any]											=						"""▁"""

UpperCamelCase_    :    Optional[Any]											=						{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCamelCase_    :    List[str]											=						{
    """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_    :    str											=						{
    """google/reformer-crime-and-punishment""": 52_4288,
}


class      _lowercase						(				SCREAMING_SNAKE_CASE__					):
				lowerCamelCase__									=    VOCAB_FILES_NAMES
				lowerCamelCase__									=    PRETRAINED_VOCAB_FILES_MAP
				lowerCamelCase__									=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCamelCase__									=    ['input_ids', 'attention_mask']
				lowerCamelCase__									=    ReformerTokenizer

				def __init__(       self    :      Any    ,      _lowercase    :      Optional[Any]=None    ,      _lowercase    :      List[str]=None    ,      _lowercase    :      List[str]="</s>"    ,      _lowercase    :      Optional[int]="<unk>"    ,      _lowercase    :      List[str]=[]    ,      **_lowercase    :      Optional[Any]    ,      ):


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

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

				def     A	(       self    :      List[str]    ,      _lowercase    :      Dict    ,      _lowercase    :      Optional[int] = None       ):


										'''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
										UpperCAmelCase__   		=						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,)


"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase_    :    Optional[Any]											=						logging.get_logger(__name__)

UpperCamelCase_    :    Optional[int]											=						{
    """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/config.json""",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}


class      _lowercase						(				__lowerCamelCase					):
				lowerCamelCase__									=    'rembert'

				def __init__(       self    :      List[Any]    ,      _lowercase    :      Tuple=2_5_0_3_0_0    ,      _lowercase    :      Tuple=1_1_5_2    ,      _lowercase    :      List[Any]=3_2    ,      _lowercase    :      Dict=1_8    ,      _lowercase    :      str=2_5_6    ,      _lowercase    :      Optional[Any]=1_6_6_4    ,      _lowercase    :      Union[str, Any]=4_6_0_8    ,      _lowercase    :      Optional[Any]="gelu"    ,      _lowercase    :      Optional[Any]=0.0    ,      _lowercase    :      Tuple=0.0    ,      _lowercase    :      Dict=0.1    ,      _lowercase    :      str=5_1_2    ,      _lowercase    :      Tuple=2    ,      _lowercase    :      int=0.02    ,      _lowercase    :      Tuple=1e-12    ,      _lowercase    :      Union[str, Any]=True    ,      _lowercase    :      Optional[int]=0    ,      _lowercase    :      Any=3_1_2    ,      _lowercase    :      Optional[Any]=3_1_3    ,      **_lowercase    :      str    ,      ):


										'''simple docstring'''
										super().__init__(pad_token_id=_lowercase    ,      bos_token_id=_lowercase    ,      eos_token_id=_lowercase    ,      **_lowercase       )

										UpperCAmelCase__   		=						vocab_size
										UpperCAmelCase__   		=						input_embedding_size
										UpperCAmelCase__   		=						output_embedding_size
										UpperCAmelCase__   		=						max_position_embeddings
										UpperCAmelCase__   		=						hidden_size
										UpperCAmelCase__   		=						num_hidden_layers
										UpperCAmelCase__   		=						num_attention_heads
										UpperCAmelCase__   		=						intermediate_size
										UpperCAmelCase__   		=						hidden_act
										UpperCAmelCase__   		=						hidden_dropout_prob
										UpperCAmelCase__   		=						attention_probs_dropout_prob
										UpperCAmelCase__   		=						classifier_dropout_prob
										UpperCAmelCase__   		=						initializer_range
										UpperCAmelCase__   		=						type_vocab_size
										UpperCAmelCase__   		=						layer_norm_eps
										UpperCAmelCase__   		=						use_cache
										UpperCAmelCase__   		=						False


class      _lowercase						(				__lowerCamelCase					):

				@property
				def     A	(       self    :      str       ):


										'''simple docstring'''
										if self.task == "multiple-choice":
																UpperCAmelCase__   		=						{0: """batch""", 1: """choice""", 2: """sequence"""}
										else:
																UpperCAmelCase__   		=						{0: """batch""", 1: """sequence"""}
										return OrderedDict(
										    [
										        ("""input_ids""", dynamic_axis),
										        ("""attention_mask""", dynamic_axis),
										        ("""token_type_ids""", dynamic_axis),
										    ]       )

				@property
				def     A	(       self    :      Tuple       ):


										'''simple docstring'''
										return 1e-4

