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

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


UpperCAmelCase_           =				logging.get_logger(__name__)

UpperCAmelCase_           =				{
    '''vocab_file''': '''vocab.txt''',
    '''merges_file''': '''bpe.codes''',
}

UpperCAmelCase_           =				{
    '''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''',
    },
}

UpperCAmelCase_           =				{
    '''vinai/phobert-base''': 2_5_6,
    '''vinai/phobert-large''': 2_5_6,
}




def    lowerCAmelCase_  (		lowercase:				Optional[int]		)     ->					List[str]:







 '''simple docstring'''
 _UpperCamelCase:  str    						=			set()
 _UpperCamelCase:  Optional[int]    						=			word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)		)
  _UpperCamelCase:  Optional[Any]    						=			char

 _UpperCamelCase:  Tuple    						=			set(lowercase		)
 return pairs





class 			__magic_name__	(		__a     ):





   """simple docstring"""




   lowerCAmelCase   :     Tuple	      = VOCAB_FILES_NAMES
   lowerCAmelCase   :     List[str]	      = PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase   :     List[str]	      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



   def __init__(						self       :	Dict		,	_lowercase       :	Tuple		,	_lowercase       :	List[Any]		,	_lowercase       :	Optional[Any]="<s>"		,	_lowercase       :	List[Any]="</s>"		,	_lowercase       :	List[str]="</s>"		,	_lowercase       :	List[Any]="<s>"		,	_lowercase       :	Any="<unk>"		,	_lowercase       :	Optional[int]="<pad>"		,	_lowercase       :	Dict="<mask>"		,	**_lowercase       :	List[str]		,	):



    """simple docstring"""



    super().__init__(
        bos_token=_lowercase		,	eos_token=_lowercase		,	unk_token=_lowercase		,	sep_token=_lowercase		,	cls_token=_lowercase		,	pad_token=_lowercase		,	mask_token=_lowercase		,	**_lowercase		,	)

    _UpperCamelCase:  Any    						=			vocab_file
    _UpperCamelCase:  Any    						=			merges_file

    _UpperCamelCase:  str    						=			{}
    _UpperCamelCase:  str    						=			0
    _UpperCamelCase:  Any    						=			1
    _UpperCamelCase:  int    						=			2
    _UpperCamelCase:  Optional[int]    						=			3

    self.add_from_file(_lowercase				)

    _UpperCamelCase:  Union[str, Any]    						=			{v: k for k, v in self.encoder.items()}

    with open(_lowercase		,	encoding='''utf-8'''				) as merges_handle:
     _UpperCamelCase:  Optional[Any]    						=			merges_handle.read().split('''\n'''				)[:-1]
    _UpperCamelCase:  Tuple    						=			[tuple(merge.split()[:-1]				) for merge in merges]
    _UpperCamelCase:  Union[str, Any]    						=			dict(zip(_lowercase		,	range(len(_lowercase				)				)				)				)
    _UpperCamelCase:  Optional[Any]    						=			{}



   def 	lowerCAmelCase    (						self       :	Tuple		,	_lowercase       :	List[int]		,	_lowercase       :	Optional[List[int]] = None				):



    """simple docstring"""



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



   def 	lowerCAmelCase    (						self       :	str		,	_lowercase       :	List[int]		,	_lowercase       :	Optional[List[int]] = None		,	_lowercase       :	bool = False				):



    """simple docstring"""



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

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



   def 	lowerCAmelCase    (						self       :	Optional[int]		,	_lowercase       :	List[int]		,	_lowercase       :	Optional[List[int]] = None				):



    """simple docstring"""



    _UpperCamelCase:  Optional[int]    						=			[self.sep_token_id]
    _UpperCamelCase:  Any    						=			[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 	lowerCAmelCase    (						self       :	int				):



    """simple docstring"""



    return len(self.encoder				)



   def 	lowerCAmelCase    (						self       :	Any				):



    """simple docstring"""



    return dict(self.encoder		,	**self.added_tokens_encoder				)



   def 	lowerCAmelCase    (						self       :	Any		,	_lowercase       :	Tuple				):



    """simple docstring"""



    if token in self.cache:
     return self.cache[token]
    _UpperCamelCase:  List[str]    						=			tuple(_lowercase				)
    _UpperCamelCase:  List[Any]    						=			tuple(list(word[:-1]				) + [word[-1] + '''</w>''']				)
    _UpperCamelCase:  Optional[int]    						=			get_pairs(_lowercase				)

    if not pairs:
     return token

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

      if word[i] == first and i < len(_lowercase				) - 1 and word[i + 1] == second:
       new_word.append(first + second				)
       i += 2
      else:
       new_word.append(word[i]				)
       i += 1
     _UpperCamelCase:  Dict    						=			tuple(_lowercase				)
     _UpperCamelCase:  List[Any]    						=			new_word
     if len(_lowercase				) == 1:
      break
     else:
      _UpperCamelCase:  int    						=			get_pairs(_lowercase				)
    _UpperCamelCase:  List[Any]    						=			'''@@ '''.join(_lowercase				)
    _UpperCamelCase:  Optional[int]    						=			word[:-4]
    _UpperCamelCase:  Any    						=			word
    return word



   def 	lowerCAmelCase    (						self       :	List[str]		,	_lowercase       :	str				):



    """simple docstring"""



    _UpperCamelCase:  Dict    						=			[]

    _UpperCamelCase:  Tuple    						=			re.findall(R'''\S+\n?'''		,	_lowercase				)

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



   def 	lowerCAmelCase    (						self       :	Dict		,	_lowercase       :	List[Any]				):



    """simple docstring"""



    return self.encoder.get(_lowercase		,	self.encoder.get(self.unk_token				)				)



   def 	lowerCAmelCase    (						self       :	Tuple		,	_lowercase       :	str				):



    """simple docstring"""



    return self.decoder.get(_lowercase		,	self.unk_token				)



   def 	lowerCAmelCase    (						self       :	Union[str, Any]		,	_lowercase       :	Optional[Any]				):



    """simple docstring"""



    _UpperCamelCase:  List[str]    						=			''' '''.join(_lowercase				).replace('''@@ '''		,	''''''				).strip()
    return out_string



   def 	lowerCAmelCase    (						self       :	List[str]		,	_lowercase       :	str		,	_lowercase       :	Optional[str] = None				):



    """simple docstring"""



    if not os.path.isdir(_lowercase				):
     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
     return
    _UpperCamelCase:  Tuple    						=			os.path.join(
        _lowercase		,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)
    _UpperCamelCase:  Optional[int]    						=			os.path.join(
        _lowercase		,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']				)

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

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

    return out_vocab_file, out_merge_file



   def 	lowerCAmelCase    (						self       :	int		,	_lowercase       :	List[Any]				):



    """simple docstring"""



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

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

import numpy as np

from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask


if is_flax_available():
  from transformers.models.bert.modeling_flax_bert import (
      FlaxBertForMaskedLM,
      FlaxBertForMultipleChoice,
      FlaxBertForNextSentencePrediction,
      FlaxBertForPreTraining,
      FlaxBertForQuestionAnswering,
      FlaxBertForSequenceClassification,
      FlaxBertForTokenClassification,
      FlaxBertModel,
  )




class 			__magic_name__	(		unittest.TestCase     ):





   """simple docstring"""




   def __init__(						self       :	Tuple		,	_lowercase       :	List[str]		,	_lowercase       :	Dict=13		,	_lowercase       :	Any=7		,	_lowercase       :	List[str]=True		,	_lowercase       :	Any=True		,	_lowercase       :	Optional[int]=True		,	_lowercase       :	int=True		,	_lowercase       :	str=99		,	_lowercase       :	Union[str, Any]=32		,	_lowercase       :	Any=5		,	_lowercase       :	Dict=4		,	_lowercase       :	Tuple=37		,	_lowercase       :	Optional[Any]="gelu"		,	_lowercase       :	Optional[int]=0.1		,	_lowercase       :	Any=0.1		,	_lowercase       :	Union[str, Any]=512		,	_lowercase       :	Dict=16		,	_lowercase       :	int=2		,	_lowercase       :	Union[str, Any]=0.02		,	_lowercase       :	Dict=4		,	):



    """simple docstring"""



    _UpperCamelCase:  List[str]    						=			parent
    _UpperCamelCase:  Optional[int]    						=			batch_size
    _UpperCamelCase:  Any    						=			seq_length
    _UpperCamelCase:  List[str]    						=			is_training
    _UpperCamelCase:  Union[str, Any]    						=			use_attention_mask
    _UpperCamelCase:  Union[str, Any]    						=			use_token_type_ids
    _UpperCamelCase:  str    						=			use_labels
    _UpperCamelCase:  List[str]    						=			vocab_size
    _UpperCamelCase:  Dict    						=			hidden_size
    _UpperCamelCase:  List[Any]    						=			num_hidden_layers
    _UpperCamelCase:  List[Any]    						=			num_attention_heads
    _UpperCamelCase:  Tuple    						=			intermediate_size
    _UpperCamelCase:  Optional[Any]    						=			hidden_act
    _UpperCamelCase:  Any    						=			hidden_dropout_prob
    _UpperCamelCase:  int    						=			attention_probs_dropout_prob
    _UpperCamelCase:  Optional[int]    						=			max_position_embeddings
    _UpperCamelCase:  List[Any]    						=			type_vocab_size
    _UpperCamelCase:  List[Any]    						=			type_sequence_label_size
    _UpperCamelCase:  List[Any]    						=			initializer_range
    _UpperCamelCase:  Optional[int]    						=			num_choices



   def 	lowerCAmelCase    (						self       :	Optional[Any]				):



    """simple docstring"""



    _UpperCamelCase:  int    						=			ids_tensor([self.batch_size, self.seq_length]		,	self.vocab_size				)

    _UpperCamelCase:  Optional[int]    						=			None
    if self.use_attention_mask:
     _UpperCamelCase:  List[str]    						=			random_attention_mask([self.batch_size, self.seq_length]				)

    _UpperCamelCase:  Optional[int]    						=			None
    if self.use_token_type_ids:
     _UpperCamelCase:  Tuple    						=			ids_tensor([self.batch_size, self.seq_length]		,	self.type_vocab_size				)

    _UpperCamelCase:  str    						=			BertConfig(
        vocab_size=self.vocab_size		,	hidden_size=self.hidden_size		,	num_hidden_layers=self.num_hidden_layers		,	num_attention_heads=self.num_attention_heads		,	intermediate_size=self.intermediate_size		,	hidden_act=self.hidden_act		,	hidden_dropout_prob=self.hidden_dropout_prob		,	attention_probs_dropout_prob=self.attention_probs_dropout_prob		,	max_position_embeddings=self.max_position_embeddings		,	type_vocab_size=self.type_vocab_size		,	is_decoder=_lowercase		,	initializer_range=self.initializer_range		,	)

    return config, input_ids, token_type_ids, attention_mask



   def 	lowerCAmelCase    (						self       :	Optional[Any]				):



    """simple docstring"""



    _UpperCamelCase:  Optional[Any]    						=			self.prepare_config_and_inputs()
    _UpperCamelCase						,				_UpperCamelCase						,				_UpperCamelCase						,				_UpperCamelCase:  Any    						=			config_and_inputs
    _UpperCamelCase:  List[Any]    						=			{'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
    return config, inputs_dict



   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    _UpperCamelCase:  Any    						=			self.prepare_config_and_inputs()
    _UpperCamelCase						,				_UpperCamelCase						,				_UpperCamelCase						,				_UpperCamelCase:  str    						=			config_and_inputs

    _UpperCamelCase:  int    						=			True
    _UpperCamelCase:  Optional[Any]    						=			floats_tensor([self.batch_size, self.seq_length, self.hidden_size]				)
    _UpperCamelCase:  Optional[Any]    						=			ids_tensor([self.batch_size, self.seq_length]		,	vocab_size=2				)

    return (
        config,
        input_ids,
        attention_mask,
        encoder_hidden_states,
        encoder_attention_mask,
    )




@require_flax
class 			__magic_name__	(		__a   ,						unittest.TestCase     ):





   """simple docstring"""




   lowerCAmelCase   :     Dict	      = True

   lowerCAmelCase   :     List[Any]	      = (
       (
           FlaxBertModel,
           FlaxBertForPreTraining,
           FlaxBertForMaskedLM,
           FlaxBertForMultipleChoice,
           FlaxBertForQuestionAnswering,
           FlaxBertForNextSentencePrediction,
           FlaxBertForSequenceClassification,
           FlaxBertForTokenClassification,
           FlaxBertForQuestionAnswering,
       )
       if is_flax_available()
       else ()
   )



   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    _UpperCamelCase:  Dict    						=			FlaxBertModelTester(self				)



   @slow
   def 	lowerCAmelCase    (						self       :	Tuple				):



    """simple docstring"""



    _UpperCamelCase:  Dict    						=			FlaxBertModel.from_pretrained('''bert-base-cased'''				)
    _UpperCamelCase:  int    						=			model(np.ones((1, 1)				)				)
    self.assertIsNotNone(_lowercase				)