




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 		__A   (      __lowerCamelCase       ,    unittest.TestCase      ):
						UpperCamelCase      =       ProphetNetTokenizer
						UpperCamelCase      =       False

						def      A__    (		self :Any			):
										'''simple docstring'''

										super().setUp()

										__magic_name__						:						int										=[
										    """[UNK]""",
										    """[CLS]""",
										    """[SEP]""",
										    """[PAD]""",
										    """[MASK]""",
										    """want""",
										    """##want""",
										    """##ed""",
										    """wa""",
										    """un""",
										    """runn""",
										    """##ing""",
										    """,""",
										    """low""",
										    """lowest""",
										]
										__magic_name__						:						List[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      A__    (		self :Union[str, Any]     ,			__snake_case :Optional[int]			):
										'''simple docstring'''

										__magic_name__						:						List[str]										="""UNwant\u00E9d,running"""
										__magic_name__						:						List[str]										="""unwanted, running"""
										return input_text, output_text

						def      A__    (		self :Optional[int]			):
										'''simple docstring'''

										__magic_name__						:						Union[str, Any]										=self.tokenizer_class(self.vocab_file			)

										__magic_name__						:						int										=tokenizer.tokenize("""UNwant\u00E9d,running"""			)
										self.assertListEqual(__snake_case     ,			["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]			)
										self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case			)     ,			[9, 6, 7, 12, 10, 11]			)

						def      A__    (		self :List[str]			):
										'''simple docstring'''

										__magic_name__						:						int										=BasicTokenizer()

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

						def      A__    (		self :Tuple			):
										'''simple docstring'''

										__magic_name__						:						Dict										=BasicTokenizer(do_lower_case=__snake_case			)

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

						def      A__    (		self :List[str]			):
										'''simple docstring'''

										__magic_name__						:						str										=BasicTokenizer(do_lower_case=__snake_case     ,			strip_accents=__snake_case			)

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

						def      A__    (		self :List[str]			):
										'''simple docstring'''

										__magic_name__						:						Optional[Any]										=BasicTokenizer(do_lower_case=__snake_case     ,			strip_accents=__snake_case			)

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

						def      A__    (		self :str			):
										'''simple docstring'''

										__magic_name__						:						Optional[int]										=BasicTokenizer(do_lower_case=__snake_case			)

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

						def      A__    (		self :int			):
										'''simple docstring'''

										__magic_name__						:						List[str]										=BasicTokenizer(do_lower_case=__snake_case			)

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

						def      A__    (		self :Optional[int]			):
										'''simple docstring'''

										__magic_name__						:						List[Any]										=BasicTokenizer(do_lower_case=__snake_case     ,			strip_accents=__snake_case			)

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

						def      A__    (		self :Tuple			):
										'''simple docstring'''

										__magic_name__						:						str										=BasicTokenizer(do_lower_case=__snake_case     ,			strip_accents=__snake_case			)

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

						def      A__    (		self :Optional[int]			):
										'''simple docstring'''

										__magic_name__						:						Optional[Any]										=BasicTokenizer(do_lower_case=__snake_case     ,			never_split=["""[UNK]"""]			)

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

						def      A__    (		self :Tuple			):
										'''simple docstring'''

										__magic_name__						:						Tuple										=["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

										__magic_name__						:						Dict										={}
										for i, token in enumerate(__snake_case			):
														__magic_name__						:						Optional[int]										=i
										__magic_name__						:						Union[str, Any]										=WordpieceTokenizer(vocab=__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      A__    (		self :int			):
										'''simple docstring'''

										__magic_name__						:						Union[str, Any]										=self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased"""			)

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

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

						def      A__    (		self :Optional[Any]			):
										'''simple docstring'''

										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      A__    (		self :Any			):
										'''simple docstring'''

										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      A__    (		self :List[str]			):
										'''simple docstring'''

										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      A__    (		self :Any			):
										'''simple docstring'''

										__magic_name__						:						Tuple										=self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased"""			)

										__magic_name__						:						Optional[Any]										=tokenizer.encode("""sequence builders"""     ,			add_special_tokens=__snake_case			)
										__magic_name__						:						List[Any]										=tokenizer.encode("""multi-sequence build"""     ,			add_special_tokens=__snake_case			)

										__magic_name__						:						Optional[int]										=tokenizer.build_inputs_with_special_tokens(__snake_case			)
										__magic_name__						:						Any										=tokenizer.build_inputs_with_special_tokens(__snake_case     ,			__snake_case			)

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






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCAmelCase					   =       {
    'configuration_bridgetower': [
        'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BridgeTowerConfig',
        'BridgeTowerTextConfig',
        'BridgeTowerVisionConfig',
    ],
    'processing_bridgetower': ['BridgeTowerProcessor'],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase					   =       ['BridgeTowerImageProcessor']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase					   =       [
							    'BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'BridgeTowerForContrastiveLearning',
							    'BridgeTowerForImageAndTextRetrieval',
							    'BridgeTowerForMaskedLM',
							    'BridgeTowerModel',
							    'BridgeTowerPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_bridgetower import (
							    BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    BridgeTowerConfig,
							    BridgeTowerTextConfig,
							    BridgeTowerVisionConfig,
							)
							from .processing_bridgetower import BridgeTowerProcessor

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_bridgetower import BridgeTowerImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bridgetower import (
														    BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BridgeTowerForContrastiveLearning,
														    BridgeTowerForImageAndTextRetrieval,
														    BridgeTowerForMaskedLM,
														    BridgeTowerModel,
														    BridgeTowerPreTrainedModel,
														)


else:
							import sys

							__lowerCAmelCase					   =       _LazyModule(__name__, globals()['__file__'], _import_structure)