


import json
import os
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

lowerCamelCase						 =	logging.get_logger(__name__)

lowerCamelCase						 =	{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

lowerCamelCase						 =	{
    'vocab_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'
        ),
    },
}

lowerCamelCase						 =	{
    'microsoft/deberta-base': 5_12,
    'microsoft/deberta-large': 5_12,
    'microsoft/deberta-xlarge': 5_12,
    'microsoft/deberta-base-mnli': 5_12,
    'microsoft/deberta-large-mnli': 5_12,
    'microsoft/deberta-xlarge-mnli': 5_12,
}

lowerCamelCase						 =	{
    'microsoft/deberta-base': {'do_lower_case': False},
    'microsoft/deberta-large': {'do_lower_case': False},
}




def      a_				(   ):
       '''simple docstring'''





       _lowerCamelCase	:		Optional[int]          =(
           list(range(ord('!'					)		,      ord('~'					) + 1					)					) + list(range(ord('¡'					)		,      ord('¬'					) + 1					)					) + list(range(ord('®'					)		,      ord('ÿ'					) + 1					)					)
       )
       _lowerCamelCase	:		Tuple          =bs[:]
       _lowerCamelCase	:		Union[str, Any]          =0
       for b in range(2**8					):
              if b not in bs:
                     bs.append(SCREAMING_SNAKE_CASE__					)
                     cs.append(2**8 + n					)
                     n += 1
       _lowerCamelCase	:		List[Any]          =[chr(SCREAMING_SNAKE_CASE__					) for n in cs]
       return dict(zip(SCREAMING_SNAKE_CASE__		,      SCREAMING_SNAKE_CASE__					)					)




def      a_				(   SCREAMING_SNAKE_CASE__ :				Dict					):
       '''simple docstring'''





       _lowerCamelCase	:		Tuple          =set()
       _lowerCamelCase	:		str          =word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)					)
              _lowerCamelCase	:		str          =char
       return pairs




class A  (       UpperCamelCase_					):
      UpperCamelCase__							:  Any				=VOCAB_FILES_NAMES
      UpperCamelCase__							:  Any				=PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase__							:  str				=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase__							:  str				=['input_ids', 'attention_mask', 'token_type_ids']






      def __init__( self						:					Any      ,       lowercase_						:					Union[str, Any]      ,       lowercase_						:					Optional[Any]      ,       lowercase_						:					List[Any]="replace"      ,       lowercase_						:					str="[CLS]"      ,       lowercase_						:					Any="[SEP]"      ,       lowercase_						:					str="[SEP]"      ,       lowercase_						:					List[str]="[CLS]"      ,       lowercase_						:					Dict="[UNK]"      ,       lowercase_						:					str="[PAD]"      ,       lowercase_						:					Union[str, Any]="[MASK]"      ,       lowercase_						:					List[Any]=False      ,       lowercase_						:					List[str]=False      ,       **lowercase_						:					Tuple      ,       ) ->						List[str]:
             """simple docstring"""




             _lowerCamelCase	:		Union[str, Any]          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else bos_token
             _lowerCamelCase	:		int          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else eos_token
             _lowerCamelCase	:		List[str]          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else sep_token
             _lowerCamelCase	:		Optional[Any]          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else cls_token
             _lowerCamelCase	:		Optional[int]          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else unk_token
             _lowerCamelCase	:		Optional[Any]          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else pad_token

             # Mask token behave like a normal word, i.e. include the space before it
             _lowerCamelCase	:		Dict          =AddedToken(lowercase_      ,       lstrip=lowercase_      ,       rstrip=lowercase_			) if isinstance(lowercase_      ,       lowercase_			) else mask_token

             super().__init__(
                 errors=lowercase_      ,       bos_token=lowercase_      ,       eos_token=lowercase_      ,       unk_token=lowercase_      ,       sep_token=lowercase_      ,       cls_token=lowercase_      ,       pad_token=lowercase_      ,       mask_token=lowercase_      ,       add_prefix_space=lowercase_      ,       add_bos_token=lowercase_      ,       **lowercase_      ,       )
             _lowerCamelCase	:		int          =add_bos_token

             with open(lowercase_      ,       encoding='utf-8'			) as vocab_handle:
                    _lowerCamelCase	:		List[str]          =json.load(lowercase_			)
             _lowerCamelCase	:		Any          ={v: k for k, v in self.encoder.items()}
             _lowerCamelCase	:		List[str]          =errors  # how to handle errors in decoding
             _lowerCamelCase	:		Union[str, Any]          =bytes_to_unicode()
             _lowerCamelCase	:		List[Any]          ={v: k for k, v in self.byte_encoder.items()}
             with open(lowercase_      ,       encoding='utf-8'			) as merges_handle:
                    _lowerCamelCase	:		Optional[Any]          =merges_handle.read().split('\n'			)[1:-1]
             _lowerCamelCase	:		Optional[Any]          =[tuple(merge.split()			) for merge in bpe_merges]
             _lowerCamelCase	:		Tuple          =dict(zip(lowercase_      ,       range(len(lowercase_			)			)			)			)
             _lowerCamelCase	:		int          ={}
             _lowerCamelCase	:		List[str]          =add_prefix_space

             # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
             _lowerCamelCase	:		Tuple          =re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'			)






      @property
      # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
      def 	lowerCamelCase	( self						:					str			) ->						Any:
             """simple docstring"""




             return len(self.encoder			)






      def 	lowerCamelCase	( self						:					int			) ->						Any:
             """simple docstring"""




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






      def 	lowerCamelCase	( self						:					List[str]      ,       lowercase_						:					Optional[int]			) ->						Any:
             """simple docstring"""




             if token in self.cache:
                    return self.cache[token]
             _lowerCamelCase	:		Optional[int]          =tuple(lowercase_			)
             _lowerCamelCase	:		Optional[int]          =get_pairs(lowercase_			)

             if not pairs:
                    return token

             while True:
                    _lowerCamelCase	:		Any          =min(lowercase_      ,       key=lambda lowercase_			: self.bpe_ranks.get(lowercase_      ,       float('inf'			)			)			)
                    if bigram not in self.bpe_ranks:
                           break
                    _lowerCamelCase     ,					_lowerCamelCase	:		int          =bigram
                    _lowerCamelCase	:		Any          =[]
                    _lowerCamelCase	:		int          =0
                    while i < len(lowercase_			):
                           try:
                                  _lowerCamelCase	:		Optional[Any]          =word.index(lowercase_      ,       lowercase_			)
                           except ValueError:
                                  new_word.extend(word[i:]			)
                                  break
                           else:
                                  new_word.extend(word[i:j]			)
                                  _lowerCamelCase	:		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
                    _lowerCamelCase	:		List[str]          =tuple(lowercase_			)
                    _lowerCamelCase	:		Optional[Any]          =new_word
                    if len(lowercase_			) == 1:
                           break
                    else:
                           _lowerCamelCase	:		List[Any]          =get_pairs(lowercase_			)
             _lowerCamelCase	:		Union[str, Any]          =' '.join(lowercase_			)
             _lowerCamelCase	:		Tuple          =word
             return word






      def 	lowerCamelCase	( self						:					str      ,       lowercase_						:					List[int]      ,       lowercase_						:					Optional[List[int]] = None			) ->						List[int]:
             """simple docstring"""




             if token_ids_a is None:
                    return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
             _lowerCamelCase	:		List[str]          =[self.cls_token_id]
             _lowerCamelCase	:		Dict          =[self.sep_token_id]
             return cls + token_ids_a + sep + token_ids_a + sep






      def 	lowerCamelCase	( self						:					List[Any]      ,       lowercase_						:					List[int]      ,       lowercase_						:					Optional[List[int]] = None      ,       lowercase_						:					bool = False			) ->						List[int]:
             """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] + ([0] * len(lowercase_			)) + [1]






      def 	lowerCamelCase	( self						:					Optional[Any]      ,       lowercase_						:					List[int]      ,       lowercase_						:					Optional[List[int]] = None			) ->						List[int]:
             """simple docstring"""




             _lowerCamelCase	:		str          =[self.sep_token_id]
             _lowerCamelCase	:		Optional[int]          =[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			) * [0] + len(token_ids_a + sep			) * [1]






      def 	lowerCamelCase	( self						:					List[Any]      ,       lowercase_						:					Any			) ->						Any:
             """simple docstring"""




             _lowerCamelCase	:		List[Any]          =[]
             for token in re.findall(self.pat      ,       lowercase_			):
                    _lowerCamelCase	:		int          =''.join(
                        self.byte_encoder[b] for b in token.encode('utf-8'			)			)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
                    bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowercase_			).split(' '			)			)
             return bpe_tokens






      def 	lowerCamelCase	( self						:					int      ,       lowercase_						:					Any			) ->						Union[str, Any]:
             """simple docstring"""




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






      def 	lowerCamelCase	( self						:					Any      ,       lowercase_						:					Optional[Any]			) ->						Union[str, Any]:
             """simple docstring"""




             return self.decoder.get(lowercase_			)






      def 	lowerCamelCase	( self						:					Any      ,       lowercase_						:					List[str]			) ->						Tuple:
             """simple docstring"""




             _lowerCamelCase	:		int          =''.join(lowercase_			)
             _lowerCamelCase	:		int          =bytearray([self.byte_decoder[c] for c in text]			).decode('utf-8'      ,       errors=self.errors			)
             return text






      def 	lowerCamelCase	( self						:					List[Any]      ,       lowercase_						:					str      ,       lowercase_						:					Optional[str] = None			) ->						Tuple[str]:
             """simple docstring"""




             if not os.path.isdir(lowercase_			):
                    logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
                    return
             _lowerCamelCase	:		Dict          =os.path.join(
                 lowercase_      ,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)
             _lowerCamelCase	:		Optional[int]          =os.path.join(
                 lowercase_      ,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']			)

             with open(lowercase_      ,       'w'      ,       encoding='utf-8'			) as f:
                    f.write(json.dumps(self.encoder      ,       indent=2      ,       sort_keys=lowercase_      ,       ensure_ascii=lowercase_			) + '\n'			)

             _lowerCamelCase	:		Union[str, Any]          =0
             with open(lowercase_      ,       'w'      ,       encoding='utf-8'			) as writer:
                    writer.write('#version: 0.2\n'			)
                    for bpe_tokens, token_index in sorted(self.bpe_ranks.items()      ,       key=lambda lowercase_			: kv[1]			):
                           if index != token_index:
                                  logger.warning(
                                      F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                                      ' Please check that the tokenizer is not corrupted!'			)
                                  _lowerCamelCase	:		Dict          =token_index
                           writer.write(' '.join(lowercase_			) + '\n'			)
                           index += 1

             return vocab_file, merge_file






      def 	lowerCamelCase	( self						:					str      ,       lowercase_						:					Optional[int]      ,       lowercase_						:					Optional[int]=False      ,       **lowercase_						:					List[str]			) ->						Dict:
             """simple docstring"""




             _lowerCamelCase	:		Tuple          =kwargs.pop('add_prefix_space'      ,       self.add_prefix_space			)
             if (is_split_into_words or add_prefix_space) and (len(lowercase_			) > 0 and not text[0].isspace()):
                    _lowerCamelCase	:		Tuple          =' ' + text
             return (text, kwargs)






      def 	lowerCamelCase	( self						:					Dict      ,       lowercase_						:					"Conversation"			) ->						List[int]:
             """simple docstring"""




             _lowerCamelCase	:		Optional[int]          =[]
             for is_user, text in conversation.iter_texts():
                    input_ids.extend(self.encode(lowercase_      ,       add_special_tokens=lowercase_			) + [self.eos_token_id]			)
             if len(lowercase_			) > self.model_max_length:
                    _lowerCamelCase	:		str          =input_ids[-self.model_max_length :]
             return input_ids






import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

lowerCamelCase						 =	logging.getLogger()




def      a_				(   ):
       '''simple docstring'''





       _lowerCamelCase	:		Any          =argparse.ArgumentParser()
       parser.add_argument('-f'					)
       _lowerCamelCase	:		Optional[Any]          =parser.parse_args()
       return args.f




class A  (       UpperCamelCase_					):






      def 	lowerCamelCase	( self						:					List[Any]			) ->						int:
             """simple docstring"""




             _lowerCamelCase	:		Any          =logging.StreamHandler(sys.stdout			)
             logger.addHandler(lowercase_			)

             _lowerCamelCase	:		Dict          =self.get_auto_remove_tmp_dir()
             _lowerCamelCase	:		int          =F'''
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

             with patch.object(lowercase_      ,       'argv'      ,       lowercase_			):
                    _lowerCamelCase	:		Dict          =run_glue_with_pabee.main()
                    for value in result.values():
                           self.assertGreaterEqual(lowercase_      ,       0.75			)


