'''simple docstring'''

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			(						_SCREAMING_SNAKE_CASE    ,			unittest.TestCase):







		"""simple docstring"""
		lowercase   :      Dict       =							ProphetNetTokenizer
		lowercase   :      Tuple       =							False






		def 		UpperCamelCase__       (   self				) ->     Optional[Any]:
								super().setUp()

								_lowerCAmelCase										=[
								    '[UNK]',
								    '[CLS]',
								    '[SEP]',
								    '[PAD]',
								    '[MASK]',
								    'want',
								    '##want',
								    '##ed',
								    'wa',
								    'un',
								    'runn',
								    '##ing',
								    ',',
								    'low',
								    'lowest',
								]
								_lowerCAmelCase										=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 		UpperCamelCase__       (   self		,						__A				) ->     Any:
								_lowerCAmelCase										='UNwant\u00E9d,running'
								_lowerCAmelCase										='unwanted, running'
								return input_text, output_text






		def 		UpperCamelCase__       (   self				) ->     str:
								_lowerCAmelCase										=self.tokenizer_class(self.vocab_file				)

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






		def 		UpperCamelCase__       (   self				) ->     Union[str, Any]:
								_lowerCAmelCase										=BasicTokenizer()

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






		def 		UpperCamelCase__       (   self				) ->     Union[str, Any]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     List[str]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_		,						strip_accents=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     Optional[int]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_		,						strip_accents=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     List[Any]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     Union[str, Any]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     Dict:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_		,						strip_accents=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     List[Any]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_		,						strip_accents=A_				)

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






		def 		UpperCamelCase__       (   self				) ->     List[str]:
								_lowerCAmelCase										=BasicTokenizer(do_lower_case=A_		,						never_split=['[UNK]']				)

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






		def 		UpperCamelCase__       (   self				) ->     Optional[Any]:
								_lowerCAmelCase										=['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

								_lowerCAmelCase										={}
								for i, token in enumerate(A_				):
														_lowerCAmelCase										=i
								_lowerCAmelCase										=WordpieceTokenizer(vocab=A_		,						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 		UpperCamelCase__       (   self				) ->     int:
								_lowerCAmelCase										=self.tokenizer_class.from_pretrained('microsoft/prophetnet-large-uncased'				)

								_lowerCAmelCase										=['A long paragraph for summarization.', 'Another paragraph for summarization.']
								_lowerCAmelCase										=[1037, 2146, 2_0423, 2005, 7680, 7849, 3989, 1012, 102]
								_lowerCAmelCase										=tokenizer(A_		,						padding=A_		,						return_tensors='pt'				)
								self.assertIsInstance(A_		,						A_				)
								_lowerCAmelCase										=list(batch.input_ids.numpy()[0]				)
								self.assertListEqual(A_		,						A_				)

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






		def 		UpperCamelCase__       (   self				) ->     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 		UpperCamelCase__       (   self				) ->     Tuple:
								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 		UpperCamelCase__       (   self				) ->     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 		UpperCamelCase__       (   self				) ->     Dict:
								_lowerCAmelCase										=self.tokenizer_class.from_pretrained('microsoft/prophetnet-large-uncased'				)

								_lowerCAmelCase										=tokenizer.encode('sequence builders'		,						add_special_tokens=A_				)
								_lowerCAmelCase										=tokenizer.encode('multi-sequence build'		,						add_special_tokens=A_				)

								_lowerCAmelCase										=tokenizer.build_inputs_with_special_tokens(A_				)
								_lowerCAmelCase										=tokenizer.build_inputs_with_special_tokens(A_		,						A_				)

								assert encoded_sentence == text + [102]
								assert encoded_pair == text + [102] + text_a + [102]






'''simple docstring'''

from . import __version__

# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
    CLOUDFRONT_DISTRIB_PREFIX,
    CONFIG_NAME,
    DISABLE_TELEMETRY,
    DUMMY_INPUTS,
    DUMMY_MASK,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    FEATURE_EXTRACTOR_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    MODEL_CARD_NAME,
    MULTIPLE_CHOICE_DUMMY_INPUTS,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    SENTENCEPIECE_UNDERLINE,
    SPIECE_UNDERLINE,
    TF2_WEIGHTS_NAME,
    TF_WEIGHTS_NAME,
    TORCH_FX_REQUIRED_VERSION,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    WEIGHTS_INDEX_NAME,
    WEIGHTS_NAME,
    ContextManagers,
    DummyObject,
    EntryNotFoundError,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    TensorType,
    _LazyModule,
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    cached_property,
    copy_func,
    default_cache_path,
    define_sagemaker_information,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    get_torch_version,
    has_file,
    http_user_agent,
    is_apex_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_datasets_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_librosa_available,
    is_offline_mode,
    is_onnx_available,
    is_pandas_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_tensor,
    is_tensorflow_probability_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    replace_return_docstrings,
    requires_backends,
    to_numpy,
    to_py_obj,
    torch_only_method,
)





