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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase__		:Any			  =   logging.get_logger(__name__)

lowercase__		:str			  =   {
    "vocab_file": "vocab.txt",
    "merges_file": "bpe.codes",
}

lowercase__		:List[Any]			  =   {
    "vocab_file": {
        "vinai/phobert-base": "https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt",
        "vinai/phobert-large": "https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt",
    },
    "merges_file": {
        "vinai/phobert-base": "https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes",
        "vinai/phobert-large": "https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes",
    },
}

lowercase__		:Tuple			  =   {
    "vinai/phobert-base": 256,
    "vinai/phobert-large": 256,
}



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						set()
					lowercase						     =						word[0]
					for char in word[1:]:
										pairs.add((prev_char, char)		)
										lowercase						     =						char

					lowercase						     =						set(lowerCAmelCase__		)
					return pairs







class     lowercase		( SCREAMING_SNAKE_CASE__		):
							lowercase_	:	List[Any]	 =VOCAB_FILES_NAMES
							lowercase_	:	Optional[int]	 =PRETRAINED_VOCAB_FILES_MAP
							lowercase_	:	Optional[Any]	 =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




							def __init__(    self       ,A__       ,A__       ,A__="<s>"       ,A__="</s>"       ,A__="</s>"       ,A__="<s>"       ,A__="<unk>"       ,A__="<pad>"       ,A__="<mask>"       ,**A__       ,):
												super().__init__(
												    bos_token=A__       ,eos_token=A__       ,unk_token=A__       ,sep_token=A__       ,cls_token=A__       ,pad_token=A__       ,mask_token=A__       ,**A__       ,)

												lowercase						     =						vocab_file
												lowercase						     =						merges_file

												lowercase						     =						{}
												lowercase						     =						0
												lowercase						     =						1
												lowercase						     =						2
												lowercase						     =						3

												self.add_from_file(A__)

												lowercase						     =						{v: k for k, v in self.encoder.items()}

												with open(A__       ,encoding='''utf-8''') as merges_handle:
																	lowercase						     =						merges_handle.read().split('''\n''')[:-1]
												lowercase						     =						[tuple(merge.split()[:-1]) for merge in merges]
												lowercase						     =						dict(zip(A__       ,range(len(A__))))
												lowercase						     =						{}




							def 			A__				(    self       ,A__       ,A__ = None):

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




							def 			A__				(    self       ,A__       ,A__ = None       ,A__ = False):

												if already_has_special_tokens:
																	return super().get_special_tokens_mask(
																	    token_ids_a=A__       ,token_ids_a=A__       ,already_has_special_tokens=A__)

												if token_ids_a is None:
																	return [1] + ([0] * len(A__)) + [1]
												return [1] + ([0] * len(A__)) + [1, 1] + ([0] * len(A__)) + [1]




							def 			A__				(    self       ,A__       ,A__ = None):
												lowercase						     =						[self.sep_token_id]
												lowercase						     =						[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]




							@property
							def 			A__				(    self):
												return len(self.encoder)




							def 			A__				(    self):
												return dict(self.encoder       ,**self.added_tokens_encoder)




							def 			A__				(    self       ,A__):
												if token in self.cache:
																	return self.cache[token]
												lowercase						     =						tuple(A__)
												lowercase						     =						tuple(list(word[:-1]) + [word[-1] + '''</w>'''])
												lowercase						     =						get_pairs(A__)

												if not pairs:
																	return token

												while True:
																	lowercase						     =						min(A__       ,key=lambda A__: self.bpe_ranks.get(A__       ,float('''inf''')))
																	if bigram not in self.bpe_ranks:
																						break
																	lowercase     ,						lowercase						     =						bigram
																	lowercase						     =						[]
																	lowercase						     =						0
																	while i < len(A__):
																						try:
																											lowercase						     =						word.index(A__       ,A__)
																						except ValueError:
																											new_word.extend(word[i:])
																											break
																						else:
																											new_word.extend(word[i:j])
																											lowercase						     =						j

																						if word[i] == first and i < len(A__) - 1 and word[i + 1] == second:
																											new_word.append(first + second)
																											i += 2
																						else:
																											new_word.append(word[i])
																											i += 1
																	lowercase						     =						tuple(A__)
																	lowercase						     =						new_word
																	if len(A__) == 1:
																						break
																	else:
																						lowercase						     =						get_pairs(A__)
												lowercase						     =						'''@@ '''.join(A__)
												lowercase						     =						word[:-4]
												lowercase						     =						word
												return word




							def 			A__				(    self       ,A__):
												lowercase						     =						[]

												lowercase						     =						re.findall(r'''\S+\n?'''       ,A__)

												for token in words:
																	split_tokens.extend(list(self.bpe(A__).split(''' ''')))
												return split_tokens




							def 			A__				(    self       ,A__):
												return self.encoder.get(A__       ,self.encoder.get(self.unk_token))




							def 			A__				(    self       ,A__):
												return self.decoder.get(A__       ,self.unk_token)




							def 			A__				(    self       ,A__):
												lowercase						     =						''' '''.join(A__).replace('''@@ '''       ,'''''').strip()
												return out_string




							def 			A__				(    self       ,A__       ,A__ = None):
												if not os.path.isdir(A__):
																	logger.error(f'Vocabulary path ({save_directory}) should be a directory')
																	return
												lowercase						     =						os.path.join(
												    A__       ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])
												lowercase						     =						os.path.join(
												    A__       ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file'''])

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

												if os.path.abspath(self.merges_file) != os.path.abspath(A__):
																	copyfile(self.merges_file       ,A__)

												return out_vocab_file, out_merge_file





							def 			A__				(    self       ,A__):
												if isinstance(A__       ,A__):
																	try:
																						with open(A__       ,'''r'''       ,encoding='''utf-8''') as fd:
																											self.add_from_file(A__)
																	except FileNotFoundError as fnfe:
																						raise fnfe
																	except UnicodeError:
																						raise Exception(f'Incorrect encoding detected in {f}, please rebuild the dataset')
																	return

												lowercase						     =						f.readlines()
												for lineTmp in lines:
																	lowercase						     =						lineTmp.strip()
																	lowercase						     =						line.rfind(''' ''')
																	if idx == -1:
																						raise ValueError('''Incorrect dictionary format, expected \'<token> <cnt>\'''')
																	lowercase						     =						line[:idx]
																	lowercase						     =						len(self.encoder)






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase__		:Any			  =   {
    "configuration_distilbert": [
        "DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "DistilBertConfig",
        "DistilBertOnnxConfig",
    ],
    "tokenization_distilbert": ["DistilBertTokenizer"],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Tuple			  =   ["DistilBertTokenizerFast"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Union[str, Any]			  =   [
							    "DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "DistilBertForMaskedLM",
							    "DistilBertForMultipleChoice",
							    "DistilBertForQuestionAnswering",
							    "DistilBertForSequenceClassification",
							    "DistilBertForTokenClassification",
							    "DistilBertModel",
							    "DistilBertPreTrainedModel",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Optional[int]			  =   [
							    "TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "TFDistilBertForMaskedLM",
							    "TFDistilBertForMultipleChoice",
							    "TFDistilBertForQuestionAnswering",
							    "TFDistilBertForSequenceClassification",
							    "TFDistilBertForTokenClassification",
							    "TFDistilBertMainLayer",
							    "TFDistilBertModel",
							    "TFDistilBertPreTrainedModel",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Union[str, Any]			  =   [
							    "FlaxDistilBertForMaskedLM",
							    "FlaxDistilBertForMultipleChoice",
							    "FlaxDistilBertForQuestionAnswering",
							    "FlaxDistilBertForSequenceClassification",
							    "FlaxDistilBertForTokenClassification",
							    "FlaxDistilBertModel",
							    "FlaxDistilBertPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_distilbert import (
							    DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DistilBertConfig,
							    DistilBertOnnxConfig,
							)
							from .tokenization_distilbert import DistilBertTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_distilbert_fast import DistilBertTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_distilbert import (
														    DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DistilBertForMaskedLM,
														    DistilBertForMultipleChoice,
														    DistilBertForQuestionAnswering,
														    DistilBertForSequenceClassification,
														    DistilBertForTokenClassification,
														    DistilBertModel,
														    DistilBertPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_distilbert import (
														    TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFDistilBertForMaskedLM,
														    TFDistilBertForMultipleChoice,
														    TFDistilBertForQuestionAnswering,
														    TFDistilBertForSequenceClassification,
														    TFDistilBertForTokenClassification,
														    TFDistilBertMainLayer,
														    TFDistilBertModel,
														    TFDistilBertPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_distilbert import (
														    FlaxDistilBertForMaskedLM,
														    FlaxDistilBertForMultipleChoice,
														    FlaxDistilBertForQuestionAnswering,
														    FlaxDistilBertForSequenceClassification,
														    FlaxDistilBertForTokenClassification,
														    FlaxDistilBertModel,
														    FlaxDistilBertPreTrainedModel,
														)

else:
							import sys

							lowercase__		:List[str]			  =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




