
"""simple docstring"""

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

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


if is_sentencepiece_available():
      from .tokenization_camembert import CamembertTokenizer
else:
      UpperCamelCase     :    List[Any]       =			None


UpperCamelCase     :    Any       =			logging.get_logger(__name__)

UpperCamelCase     :    str       =			{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

UpperCamelCase     :    str       =			{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    },
    "tokenizer_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/tokenizer.json",
    },
}

UpperCamelCase     :    Dict       =			{
    "camembert-base": 5_1_2,
}

UpperCamelCase     :    Optional[int]       =			"▁"

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						VOCAB_FILES_NAMES
     lowercase						       =						PRETRAINED_VOCAB_FILES_MAP
     lowercase						       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase						       =						["input_ids", "attention_mask"]
     lowercase						       =						CamembertTokenizer





     def __init__(     self     ,					__UpperCAmelCase=None     ,					__UpperCAmelCase=None     ,					__UpperCAmelCase="<s>"     ,					__UpperCAmelCase="</s>"     ,					__UpperCAmelCase="</s>"     ,					__UpperCAmelCase="<s>"     ,					__UpperCAmelCase="<unk>"     ,					__UpperCAmelCase="<pad>"     ,					__UpperCAmelCase="<mask>"     ,					__UpperCAmelCase=["<s>NOTUSED", "</s>NOTUSED"]     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	AddedToken(__UpperCAmelCase     ,					lstrip=__UpperCAmelCase     ,					rstrip=__UpperCAmelCase				) if isinstance(__UpperCAmelCase     ,					__UpperCAmelCase				) else mask_token

      super().__init__(
          __UpperCAmelCase     ,					tokenizer_file=__UpperCAmelCase     ,					bos_token=__UpperCAmelCase     ,					eos_token=__UpperCAmelCase     ,					sep_token=__UpperCAmelCase     ,					cls_token=__UpperCAmelCase     ,					unk_token=__UpperCAmelCase     ,					pad_token=__UpperCAmelCase     ,					mask_token=__UpperCAmelCase     ,					additional_special_tokens=__UpperCAmelCase     ,					**__UpperCAmelCase     ,					)

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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      __UpperCamelCase      =	[self.cls_token_id]
      __UpperCamelCase      =	[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




      __UpperCamelCase      =	[self.sep_token_id]
      __UpperCamelCase      =	[self.cls_token_id]

      if token_ids_a is None:
       return len(cls + token_ids_a + sep				) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep				) * [0]







     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = 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     :    Union[str, Any]       =			logging.get_logger(__name__)

UpperCamelCase     :    int       =			{
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						"distilbert"
     lowercase						       =						{
         "hidden_size": "dim",
         "num_attention_heads": "n_heads",
         "num_hidden_layers": "n_layers",
     }





     def __init__(     self     ,					__UpperCAmelCase=3_0522     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=6     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=4 * 768     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase="gelu"     ,					__UpperCAmelCase=0.0_2     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.2     ,					__UpperCAmelCase=0     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	vocab_size
      __UpperCamelCase      =	max_position_embeddings
      __UpperCamelCase      =	sinusoidal_pos_embds
      __UpperCamelCase      =	n_layers
      __UpperCamelCase      =	n_heads
      __UpperCamelCase      =	dim
      __UpperCamelCase      =	hidden_dim
      __UpperCamelCase      =	dropout
      __UpperCamelCase      =	attention_dropout
      __UpperCamelCase      =	activation
      __UpperCamelCase      =	initializer_range
      __UpperCamelCase      =	qa_dropout
      __UpperCamelCase      =	seq_classif_dropout
      super().__init__(**__UpperCAmelCase     ,					pad_token_id=__UpperCAmelCase				)


class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):





     @property
     def 						UpperCAmelCase (     self				):

      '''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),
          ]				)



