import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin



class 			SCREAMING_SNAKE_CASE_			(       _lowerCamelCase ,    unittest.TestCase      ):
  '''simple docstring'''


  lowercase		:  Union[str, Any]							  =					ProphetNetTokenizer
  lowercase		:  List[str]							  =					False







  def 		SCREAMING_SNAKE_CASE_		(					self     :       str  )     ->					Tuple:
         super().setUp()

         A    :  Union[str, Any]								=[
             '[UNK]',
             '[CLS]',
             '[SEP]',
             '[PAD]',
             '[MASK]',
             'want',
             '##want',
             '##ed',
             'wa',
             'un',
             'runn',
             '##ing',
             ',',
             'low',
             'lowest',
         ]
         A    :  Optional[Any]								=os.path.join(self.tmpdirname   ,						VOCAB_FILES_NAMES['vocab_file']  )
         with open(self.vocab_file   ,						'w'   ,						encoding='utf-8'  ) as vocab_writer:
                vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]  )  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Tuple   ,						SCREAMING_SNAKE_CASE__     :       List[Any]  )     ->					str:
         A    :  Any								='UNwant\u00E9d,running'
         A    :  Tuple								='unwanted, running'
         return input_text, output_text







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[Any]  )     ->					Union[str, Any]:
         A    :  Optional[Any]								=self.tokenizer_class(self.vocab_file  )

         A    :  Any								=tokenizer.tokenize('UNwant\u00E9d,running'  )
         self.assertListEqual(_SCREAMING_SNAKE_CASE   ,						['un', '##want', '##ed', ',', 'runn', '##ing']  )
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE  )   ,						[9, 6, 7, 12, 10, 11]  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       int  )     ->					int:
         A    :  Optional[int]								=BasicTokenizer()

         self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz'  )   ,						['ah', '\u535A', '\u63A8', 'zz']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       List[str]  )     ->					Optional[int]:
         A    :  int								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '  )   ,						['hello', '!', 'how', 'are', 'you', '?']  )
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )   ,						['hello']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Any  )     ->					Optional[Any]:
         A    :  Optional[int]								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE   ,						strip_accents=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )   ,						['hällo', '!', 'how', 'are', 'you', '?']  )
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )   ,						['h\u00E9llo']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Any  )     ->					List[str]:
         A    :  Optional[Any]								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE   ,						strip_accents=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )   ,						['hallo', '!', 'how', 'are', 'you', '?']  )
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )   ,						['hello']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Union[str, Any]  )     ->					List[Any]:
         A    :  int								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )   ,						['hallo', '!', 'how', 'are', 'you', '?']  )
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo'  )   ,						['hello']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[int]  )     ->					Optional[int]:
         A    :  Tuple								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '  )   ,						['HeLLo', '!', 'how', 'Are', 'yoU', '?']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       int  )     ->					Union[str, Any]:
         A    :  List[Any]								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE   ,						strip_accents=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )   ,						['HäLLo', '!', 'how', 'Are', 'yoU', '?']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       List[str]  )     ->					Tuple:
         A    :  Optional[Any]								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE   ,						strip_accents=_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '  )   ,						['HaLLo', '!', 'how', 'Are', 'yoU', '?']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Any  )     ->					Union[str, Any]:
         A    :  Optional[int]								=BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE   ,						never_split=['[UNK]']  )

         self.assertListEqual(
             tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]'  )   ,						['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       List[Any]  )     ->					str:
         A    :  Tuple								=['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

         A    :  List[Any]								={}
         for i, token in enumerate(_SCREAMING_SNAKE_CASE  ):
                A    :  List[Any]								=i
         A    :  Union[str, Any]								=WordpieceTokenizer(vocab=_SCREAMING_SNAKE_CASE   ,						unk_token='[UNK]'  )

         self.assertListEqual(tokenizer.tokenize(''  )   ,						[]  )

         self.assertListEqual(tokenizer.tokenize('unwanted running'  )   ,						['un', '##want', '##ed', 'runn', '##ing']  )

         self.assertListEqual(tokenizer.tokenize('unwantedX running'  )   ,						['[UNK]', 'runn', '##ing']  )







  @require_torch
  def 		SCREAMING_SNAKE_CASE_		(					self     :       Any  )     ->					Optional[int]:
         A    :  Tuple								=self.tokenizer_class.from_pretrained('microsoft/prophetnet-large-uncased'  )

         A    :  int								=['A long paragraph for summarization.', 'Another paragraph for summarization.']
         A    :  str								=[10_37, 21_46, 2_04_23, 20_05, 76_80, 78_49, 39_89, 10_12, 1_02]
         A    :  Any								=tokenizer(_SCREAMING_SNAKE_CASE   ,						padding=_SCREAMING_SNAKE_CASE   ,						return_tensors='pt'  )
         self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE  )
         A    :  Tuple								=list(batch.input_ids.numpy()[0]  )
         self.assertListEqual(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE  )

         self.assertEqual((2, 9)   ,						batch.input_ids.shape  )
         self.assertEqual((2, 9)   ,						batch.attention_mask.shape  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Union[str, Any]  )     ->					Tuple:
         self.assertTrue(_is_whitespace(' '  )  )
         self.assertTrue(_is_whitespace('\t'  )  )
         self.assertTrue(_is_whitespace('\r'  )  )
         self.assertTrue(_is_whitespace('\n'  )  )
         self.assertTrue(_is_whitespace('\u00A0'  )  )

         self.assertFalse(_is_whitespace('A'  )  )
         self.assertFalse(_is_whitespace('-'  )  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       int  )     ->					Optional[int]:
         self.assertTrue(_is_control('\u0005'  )  )

         self.assertFalse(_is_control('A'  )  )
         self.assertFalse(_is_control(' '  )  )
         self.assertFalse(_is_control('\t'  )  )
         self.assertFalse(_is_control('\r'  )  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Tuple  )     ->					List[Any]:
         self.assertTrue(_is_punctuation('-'  )  )
         self.assertTrue(_is_punctuation('$'  )  )
         self.assertTrue(_is_punctuation('`'  )  )
         self.assertTrue(_is_punctuation('.'  )  )

         self.assertFalse(_is_punctuation('A'  )  )
         self.assertFalse(_is_punctuation(' '  )  )







  @slow
  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[int]  )     ->					Dict:
         A    :  Any								=self.tokenizer_class.from_pretrained('microsoft/prophetnet-large-uncased'  )

         A    :  Optional[Any]								=tokenizer.encode('sequence builders'   ,						add_special_tokens=_SCREAMING_SNAKE_CASE  )
         A    :  List[Any]								=tokenizer.encode('multi-sequence build'   ,						add_special_tokens=_SCREAMING_SNAKE_CASE  )

         A    :  Any								=tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE  )
         A    :  List[str]								=tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE  )

         assert encoded_sentence == text + [1_02]
         assert encoded_pair == text + [1_02] + text_a + [1_02]











"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


A_						:    Optional[int]				=      {
    'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LlamaConfig'],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    int				=      ['LlamaTokenizer']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    List[str]				=      ['LlamaTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    List[str]				=      [
							    'LlamaForCausalLM',
							    'LlamaModel',
							    'LlamaPreTrainedModel',
							    'LlamaForSequenceClassification',
							]


if TYPE_CHECKING:
							from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama import LlamaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama_fast import LlamaTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
							import sys

							A_						:    str				=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





