



'''simple docstring'''





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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation


__snake_case		:Union[str, Any]   	=  logging.get_logger(__name__)

__snake_case		:Optional[int]   	=  {'''tokenizer_file''': '''tokenizer.json'''}

__snake_case		:Optional[int]   	=  {
    '''tokenizer_file''': {
        '''bigscience/tokenizer''': '''https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json''',
        '''bigscience/bloom-560m''': '''https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b1''': '''https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b7''': '''https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json''',
        '''bigscience/bloom-3b''': '''https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json''',
        '''bigscience/bloom-7b1''': '''https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json''',
        '''bigscience/bloom''': '''https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json''',
    },
}

class 					_A (			__UpperCAmelCase					):
       UpperCamelCase__						:					Any		      =		VOCAB_FILES_NAMES
       UpperCamelCase__						:					Optional[Any]		      =		PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase__						:					str		      =		['''input_ids''', '''attention_mask''']
       UpperCamelCase__						:					Optional[Any]		      =		None



       def __init__(	self							:  int  ,	__SCREAMING_SNAKE_CASE							:  str=None  ,	__SCREAMING_SNAKE_CASE							:  List[Any]=None  ,	__SCREAMING_SNAKE_CASE							:  List[str]=None  ,	__SCREAMING_SNAKE_CASE							:  List[Any]="<unk>"  ,	__SCREAMING_SNAKE_CASE							:  List[str]="<s>"  ,	__SCREAMING_SNAKE_CASE							:  Union[str, Any]="</s>"  ,	__SCREAMING_SNAKE_CASE							:  Dict="<pad>"  ,	__SCREAMING_SNAKE_CASE							:  str=False  ,	__SCREAMING_SNAKE_CASE							:  Optional[int]=False  ,	**__SCREAMING_SNAKE_CASE							:  Union[str, Any]  ,	):


           '''simple docstring'''

           super().__init__(
               __SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE  ,	tokenizer_file=__SCREAMING_SNAKE_CASE  ,	unk_token=__SCREAMING_SNAKE_CASE  ,	bos_token=__SCREAMING_SNAKE_CASE  ,	eos_token=__SCREAMING_SNAKE_CASE  ,	pad_token=__SCREAMING_SNAKE_CASE  ,	add_prefix_space=__SCREAMING_SNAKE_CASE  ,	clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE  ,	**__SCREAMING_SNAKE_CASE  ,	)
           __a		 =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
           if pre_tok_state.get('''add_prefix_space'''  ,	__SCREAMING_SNAKE_CASE) != add_prefix_space:
               __a		 =       getattr(__SCREAMING_SNAKE_CASE  ,	pre_tok_state.pop('''type'''))
               __a		 =       add_prefix_space
               __a		 =       pre_tok_class(**__SCREAMING_SNAKE_CASE)

           __a		 =       add_prefix_space



       def 	_lowerCamelCase    (	self							:  Dict  ,	*__SCREAMING_SNAKE_CASE							:  str  ,	**__SCREAMING_SNAKE_CASE							:  Tuple):


           '''simple docstring'''

           __a		 =       kwargs.get('''is_split_into_words'''  ,	__SCREAMING_SNAKE_CASE)
           if not (self.add_prefix_space or not is_split_into_words):
               raise Exception(
                   F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'
                   ''' pretokenized inputs.''')

           return super()._batch_encode_plus(*__SCREAMING_SNAKE_CASE  ,	**__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  str  ,	*__SCREAMING_SNAKE_CASE							:  List[Any]  ,	**__SCREAMING_SNAKE_CASE							:  Union[str, Any]):


           '''simple docstring'''

           __a		 =       kwargs.get('''is_split_into_words'''  ,	__SCREAMING_SNAKE_CASE)

           if not (self.add_prefix_space or not is_split_into_words):
               raise Exception(
                   F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'
                   ''' pretokenized inputs.''')

           return super()._encode_plus(*__SCREAMING_SNAKE_CASE  ,	**__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  Any  ,	__SCREAMING_SNAKE_CASE							:  str  ,	__SCREAMING_SNAKE_CASE							:  Optional[str] = None):


           '''simple docstring'''

           __a		 =       self._tokenizer.model.save(__SCREAMING_SNAKE_CASE  ,	name=__SCREAMING_SNAKE_CASE)
           return tuple(__SCREAMING_SNAKE_CASE)





       def 	_lowerCamelCase    (	self							:  Any  ,	__SCREAMING_SNAKE_CASE							:  "Conversation"):


           '''simple docstring'''

           __a		 =       []
           for is_user, text in conversation.iter_texts():
               input_ids.extend(self.encode(__SCREAMING_SNAKE_CASE  ,	add_special_tokens=__SCREAMING_SNAKE_CASE) + [self.eos_token_id])

           if len(__SCREAMING_SNAKE_CASE) > self.model_max_length:
               __a		 =       input_ids[-self.model_max_length :]
           return input_ids










import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__snake_case		:Dict   	=  get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model''')

@require_sentencepiece
@require_tokenizers
class 					_A (			__UpperCAmelCase   ,unittest.TestCase					):
       UpperCamelCase__						:					List[str]		      =		GPTSwaTokenizer
       UpperCamelCase__						:					Dict		      =		False
       UpperCamelCase__						:					int		      =		True
       UpperCamelCase__						:					List[Any]		      =		False



       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           super().setUp()

           # We have a SentencePiece fixture for testing
           __a		 =       GPTSwaTokenizer(__SCREAMING_SNAKE_CASE  ,	eos_token='''<unk>'''  ,	bos_token='''<unk>'''  ,	pad_token='''<unk>''')

           tokenizer.save_pretrained(self.tmpdirname)



       def 	_lowerCamelCase    (	self							:  Tuple  ,	__SCREAMING_SNAKE_CASE							:  int):


           '''simple docstring'''

           __a		 =       '''This is a test'''
           __a		 =       '''This is a test'''
           return input_text, output_text



       def 	_lowerCamelCase    (	self							:  Dict):


           '''simple docstring'''

           __a		 =       '''<s>'''
           __a		 =       1

           self.assertEqual(self.get_tokenizer()._convert_token_to_id(__SCREAMING_SNAKE_CASE)  ,	__SCREAMING_SNAKE_CASE)
           self.assertEqual(self.get_tokenizer()._convert_id_to_token(__SCREAMING_SNAKE_CASE)  ,	__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           __a		 =       list(self.get_tokenizer().get_vocab().keys())

           self.assertEqual(vocab_keys[0]  ,	'''<unk>''')
           self.assertEqual(vocab_keys[1]  ,	'''<s>''')
           self.assertEqual(vocab_keys[-1]  ,	'''j''')
           self.assertEqual(len(__SCREAMING_SNAKE_CASE)  ,	2_000)



       def 	_lowerCamelCase    (	self							:  Dict):


           '''simple docstring'''

           self.assertEqual(self.get_tokenizer().vocab_size  ,	2_000)



       def 	_lowerCamelCase    (	self							:  List[str]):


           '''simple docstring'''

           __a		 =       GPTSwaTokenizer(__SCREAMING_SNAKE_CASE)

           __a		 =       tokenizer.tokenize('''This is a test''')
           self.assertListEqual(__SCREAMING_SNAKE_CASE  ,	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est'''])

           self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE)  ,	[465, 287, 265, 631, 842])

           __a		 =       tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
           # fmt: off
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE  ,	['''▁I''', '''▁was''', '''▁bor''', '''n''', '''▁in''', '''▁''', '''<0x39>''', '''2''', '''0''', '''0''', '''0''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁f''', '''al''', '''s''', '''<0xC3>''', '''<0xA9>''', '''.''']  ,	)
           # fmt: on

           __a		 =       tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE)
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE  ,	[262, 272, 1_525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260]  ,	)

           __a		 =       tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE)
           # fmt: off
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE  ,	['''▁I''', '''▁was''', '''▁bor''', '''n''', '''▁in''', '''▁''', '''<0x39>''', '''2''', '''0''', '''0''', '''0''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁f''', '''al''', '''s''', '''<0xC3>''', '''<0xA9>''', '''.'''])
           # fmt: on



       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       GPTSwaTokenizer(__SCREAMING_SNAKE_CASE)
           __a		 =       ['''This is a test''', '''I was born in 92000, and this is falsé.''']
           __a		 =       [
               [465, 287, 265, 631, 842],
               [262, 272, 1_525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
           ]

           # Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
           for text, expected_ids in zip(__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE):
               self.assertListEqual(tokenizer.encode_fast(__SCREAMING_SNAKE_CASE)  ,	__SCREAMING_SNAKE_CASE)

           # Test that decode_fast returns the input text
           for text, token_ids in zip(__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE):
               self.assertEqual(tokenizer.decode_fast(__SCREAMING_SNAKE_CASE)  ,	__SCREAMING_SNAKE_CASE)





       @slow
       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       [
               '''<|python|>def fibonacci(n)\n    if n < 0:\n        print(\'Incorrect input\')''',
               '''Hey there, how are you doing this fine day?''',
               '''This is a text with a trailing spaces followed by a dot     .''',
               '''Häj sväjs lillebrör! =)''',
               '''Det är inget fel på Mr. Cool''',
           ]

           # fmt: off
           __a		 =       {'''input_ids''': [[63_423, 5, 6_811, 14_954, 282, 816, 3_821, 63_466, 63_425, 63_462, 18, 63_978, 678, 301, 1_320, 63_423, 63_455, 63_458, 18, 63_982, 4_246, 3_940, 1_901, 47_789, 5_547, 18_994], [19_630, 1_100, 63_446, 1_342, 633, 544, 4_488, 593, 5_102, 2_416, 63_495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1_652, 428, 268, 1_936, 515, 268, 58_593, 22_413, 9_106, 546, 268, 33_213, 63_979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [55_130, 63_450, 924, 63_449, 2_249, 4_062, 1_558, 318, 63_504, 21_498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2_827, 2_559, 332, 6_575, 63_443, 26_801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
           # fmt: on
           self.tokenizer_integration_test_util(
               expected_encoding=__SCREAMING_SNAKE_CASE  ,	model_name='''AI-Sweden/gpt-sw3-126m'''  ,	sequences=__SCREAMING_SNAKE_CASE  ,	)





