



'''simple docstring'''



import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

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


lowerCamelCase	 =       logging.get_logger(__name__)

lowerCamelCase	 =       """▁"""

lowerCamelCase	 =       {"""vocab_file""": """prophetnet.tokenizer"""}

lowerCamelCase	 =       {
    """vocab_file""": {
        """microsoft/xprophetnet-large-wiki100-cased""": (
            """https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/prophetnet.tokenizer"""
        ),
    }
}

lowerCamelCase	 =       {
    """microsoft/xprophetnet-large-wiki100-cased""": {"""do_lower_case""": False},
}

lowerCamelCase	 =       {
    """microsoft/xprophetnet-large-wiki100-cased""": 512,
}



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=collections.OrderedDict()
							with open(_lowerCAmelCase  ,   'r'  ,   encoding='utf-8'					) as reader:
														__lowercase       	=reader.readlines()
							for index, token in enumerate(_lowerCAmelCase					):
														__lowercase       	=token.rstrip('\n'					)
														__lowercase       	=index
							return vocab





class _UpperCamelCase		(     A		):





				'''simple docstring'''





				lowerCAmelCase__					    =    VOCAB_FILES_NAMES
				lowerCAmelCase__					    =    PRETRAINED_VOCAB_FILES_MAP
				lowerCAmelCase__					    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCAmelCase__					    =    ["""input_ids""", """attention_mask"""]

				def __init__(							self  :  Optional[int]  ,       _lowerCAmelCase  :  int  ,       _lowerCAmelCase  :  Dict="[SEP]"  ,       _lowerCAmelCase  :  Dict="[SEP]"  ,       _lowerCAmelCase  :  Union[str, Any]="[SEP]"  ,       _lowerCAmelCase  :  List[Any]="[UNK]"  ,       _lowerCAmelCase  :  Any="[PAD]"  ,       _lowerCAmelCase  :  List[Any]="[CLS]"  ,       _lowerCAmelCase  :  List[str]="[MASK]"  ,       _lowerCAmelCase  :  Optional[Dict[str, Any]] = None  ,       **_lowerCAmelCase  :  List[str]  ,       ):







											'''simple docstring'''

											__lowercase       	={} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    bos_token=_lowerCAmelCase  ,       eos_token=_lowerCAmelCase  ,       sep_token=_lowerCAmelCase  ,       unk_token=_lowerCAmelCase  ,       pad_token=_lowerCAmelCase  ,       cls_token=_lowerCAmelCase  ,       mask_token=_lowerCAmelCase  ,       sp_model_kwargs=self.sp_model_kwargs  ,       **_lowerCAmelCase  ,       )

											try:
																		import sentencepiece as spm
											except ImportError:
																		logger.warning(
																		    'You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece'
																		    ' pip install sentencepiece')
																		raise

											__lowercase       	=spm.SentencePieceProcessor(**self.sp_model_kwargs)
											self.sp_model.Load(str(_lowerCAmelCase))
											__lowercase       	=vocab_file

											# Original fairseq vocab and spm vocab must be "aligned":
											# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
											# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
											# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
											# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

											# put special tokens and [unused] tokens into the vocab
											__lowercase       	={'[PAD]': 0, '[CLS]': 1, '[SEP]': 2, '[UNK]': 3, '[MASK]': 4}

											for i in range(1_0):
																		__lowercase       	=f"""[unused{i}]"""
																		__lowercase       	=5 + i

											# The first "real" token "," has position 15 in the embedding vocab and position 3 in the spm vocab
											__lowercase       	=1_2
											__lowercase       	={v: k for k, v in self.fairseq_tokens_to_ids.items()}
											for k in self.fairseq_tokens_to_ids.keys():
																		self.unique_no_split_tokens.append(_lowerCAmelCase)

				def __getstate__(							self  :  Optional[int]):







											'''simple docstring'''

											__lowercase       	=self.__dict__.copy()
											__lowercase       	=None
											return state

				def __setstate__(							self  :  Dict  ,       _lowerCAmelCase  :  Union[str, Any]):







											'''simple docstring'''

											__lowercase       	=d
											try:
																		import sentencepiece as spm
											except ImportError:
																		logger.warning(
																		    'You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece'
																		    ' pip install sentencepiece')
																		raise

											# for backward compatibility
											if not hasattr(self  ,       'sp_model_kwargs'):
																		__lowercase       	={}

											__lowercase       	=spm.SentencePieceProcessor(**self.sp_model_kwargs)
											self.sp_model.Load(self.vocab_file)

				def 				__lowerCamelCase     (							self  :  Tuple  ,       _lowerCAmelCase  :  List[int]  ,       _lowerCAmelCase  :  Optional[List[int]] = None  ,       _lowerCAmelCase  :  bool = False):







											'''simple docstring'''

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

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

				def 				__lowerCamelCase     (							self  :  List[str]  ,       _lowerCAmelCase  :  List[int]  ,       _lowerCAmelCase  :  Optional[List[int]] = None):







											'''simple docstring'''

											__lowercase       	=[self.sep_token_id]

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

				@property
				def 				__lowerCamelCase     (							self  :  str):







											'''simple docstring'''

											return len(self.sp_model) + self.fairseq_offset

				def 				__lowerCamelCase     (							self  :  List[str]):







											'''simple docstring'''

											__lowercase       	={self.convert_ids_to_tokens(_lowerCAmelCase): i for i in range(self.vocab_size)}
											vocab.update(self.added_tokens_encoder)
											return vocab

				def 				__lowerCamelCase     (							self  :  str  ,       _lowerCAmelCase  :  str):







											'''simple docstring'''

											return self.sp_model.encode(_lowerCAmelCase  ,       out_type=_lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  List[Any]  ,       _lowerCAmelCase  :  Tuple):







											'''simple docstring'''

											if token in self.fairseq_tokens_to_ids:
																		return self.fairseq_tokens_to_ids[token]
											__lowercase       	=self.sp_model.PieceToId(_lowerCAmelCase)

											# Need to return unknown token if the SP model returned 0
											return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

				def 				__lowerCamelCase     (							self  :  Tuple  ,       _lowerCAmelCase  :  Optional[Any]):







											'''simple docstring'''

											if index in self.fairseq_ids_to_tokens:
																		return self.fairseq_ids_to_tokens[index]
											return self.sp_model.IdToPiece(index - self.fairseq_offset)

				def 				__lowerCamelCase     (							self  :  Dict  ,       _lowerCAmelCase  :  Tuple):







											'''simple docstring'''

											__lowercase       	=''.join(_lowerCAmelCase).replace(_lowerCAmelCase  ,       ' ').strip()
											return out_string

				def 				__lowerCamelCase     (							self  :  List[Any]  ,       _lowerCAmelCase  :  str  ,       _lowerCAmelCase  :  Optional[str] = None):







											'''simple docstring'''

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

											if os.path.abspath(self.vocab_file) != os.path.abspath(_lowerCAmelCase) and os.path.isfile(self.vocab_file):
																		copyfile(self.vocab_file  ,       _lowerCAmelCase)
											elif not os.path.isfile(self.vocab_file):
																		with open(_lowerCAmelCase  ,       'wb') as fi:
																									__lowercase       	=self.sp_model.serialized_model_proto()
																									fi.write(_lowerCAmelCase)

											return (out_vocab_file,)

				def 				__lowerCamelCase     (							self  :  int  ,       _lowerCAmelCase  :  List[int]  ,       _lowerCAmelCase  :  Optional[List[int]] = None):







											'''simple docstring'''

											if token_ids_a is None:
																		return token_ids_a + [self.sep_token_id]
											__lowercase       	=[self.sep_token_id]
											return token_ids_a + sep + token_ids_a + sep








'''simple docstring'''



import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin





class _UpperCamelCase		(     A      ,       unittest.TestCase		):





				'''simple docstring'''





				lowerCAmelCase__					    =    BlenderbotSmallTokenizer
				lowerCAmelCase__					    =    False

				def 				__lowerCamelCase     (							self  :  str):







											'''simple docstring'''

											super().setUp()

											__lowercase       	=['__start__', 'adapt', 'act', 'ap@@', 'te', '__end__', '__unk__']
											__lowercase       	=dict(zip(_lowerCAmelCase  ,       range(len(_lowerCAmelCase))))

											__lowercase       	=['#version: 0.2', 'a p', 't e</w>', 'ap t</w>', 'a d', 'ad apt</w>', 'a c', 'ac t</w>', '']
											__lowercase       	={'unk_token': '__unk__', 'bos_token': '__start__', 'eos_token': '__end__'}

											__lowercase       	=os.path.join(self.tmpdirname  ,       VOCAB_FILES_NAMES['vocab_file'])
											__lowercase       	=os.path.join(self.tmpdirname  ,       VOCAB_FILES_NAMES['merges_file'])
											with open(self.vocab_file  ,       'w'  ,       encoding='utf-8') as fp:
																		fp.write(json.dumps(_lowerCAmelCase) + '\n')
											with open(self.merges_file  ,       'w'  ,       encoding='utf-8') as fp:
																		fp.write('\n'.join(_lowerCAmelCase))

				def 				__lowerCamelCase     (							self  :  int  ,       **_lowerCAmelCase  :  Tuple):







											'''simple docstring'''

											kwargs.update(self.special_tokens_map)
											return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname  ,       **_lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  Tuple  ,       _lowerCAmelCase  :  Any):







											'''simple docstring'''

											__lowercase       	='adapt act apte'
											__lowercase       	='adapt act apte'
											return input_text, output_text

				def 				__lowerCamelCase     (							self  :  Union[str, Any]):







											'''simple docstring'''

											__lowercase       	=BlenderbotSmallTokenizer(self.vocab_file  ,       self.merges_file  ,       **self.special_tokens_map)
											__lowercase       	='adapt act apte'
											__lowercase       	=['adapt', 'act', 'ap@@', 'te']
											__lowercase       	=tokenizer.tokenize(_lowerCAmelCase)
											self.assertListEqual(_lowerCAmelCase  ,       _lowerCAmelCase)

											__lowercase       	=[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

											__lowercase       	=[0, 1, 2, 3, 4, 5]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase)  ,       _lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  Union[str, Any]):







											'''simple docstring'''

											__lowercase       	=BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M')
											assert tok('sam').input_ids == [1_3_8_4]
											__lowercase       	='I am a small frog.'
											__lowercase       	=tok([src_text]  ,       padding=_lowerCAmelCase  ,       truncation=_lowerCAmelCase)['input_ids']
											__lowercase       	=tok.batch_decode(_lowerCAmelCase  ,       skip_special_tokens=_lowerCAmelCase  ,       clean_up_tokenization_spaces=_lowerCAmelCase)[0]
											assert src_text != decoded  # I wish it did!
											assert decoded == "i am a small frog ."

				def 				__lowerCamelCase     (							self  :  str):







											'''simple docstring'''

											__lowercase       	=BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M')
											__lowercase       	='I am a small frog .'
											__lowercase       	='.'
											__lowercase       	=tok(_lowerCAmelCase)['input_ids']
											__lowercase       	=tok(_lowerCAmelCase)['input_ids']

											assert encoded[-1] == encoded_dot[0]



