



import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class    SCREAMING_SNAKE_CASE			(							_snake_case			,      unittest.TestCase					):
							__lowerCamelCase	:	Optional[Any]    =LayoutLMTokenizer
							__lowerCamelCase	:	List[Any]    =LayoutLMTokenizerFast
							__lowerCamelCase	:	str    =True
							__lowerCamelCase	:	List[str]    =True





							def 						UpperCamelCase_					(   self		:		Optional[Any]	):

											'''simple docstring'''
											super().setUp()

											__a       =		[
											    "[UNK]",
											    "[CLS]",
											    "[SEP]",
											    "want",
											    "##want",
											    "##ed",
											    "wa",
											    "un",
											    "runn",
											    "##ing",
											    ",",
											    "low",
											    "lowest",
											]
											__a       =		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		:		List[Any]      ,				**__lowercase		:		List[Any]	):

											'''simple docstring'''
											return LayoutLMTokenizer.from_pretrained(self.tmpdirname      ,				**snake_case_	)





							def 						UpperCamelCase_					(   self		:		List[Any]      ,				__lowercase		:		List[Any]	):

											'''simple docstring'''
											__a       =		"UNwant\u00E9d,running"
											__a       =		"unwanted, running"
											return input_text, output_text





							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											__a       =		self.tokenizer_class(self.vocab_file	)

											__a       =		tokenizer.tokenize("""UNwant\u00E9d,running"""	)
											self.assertListEqual(snake_case_      ,				["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]	)
											self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_	)      ,				[7, 4, 5, 10, 8, 9]	)







							def 						UpperCamelCase_					(   self		:		Optional[Any]	):

											'''simple docstring'''
											pass





from typing import TYPE_CHECKING

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


lowerCamelCase__			= {"""configuration_mbart""": ["""MBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MBartConfig""", """MBartOnnxConfig"""]}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= ["""MBartTokenizer"""]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= ["""MBartTokenizerFast"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= [
						    """MBART_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """MBartForCausalLM""",
						    """MBartForConditionalGeneration""",
						    """MBartForQuestionAnswering""",
						    """MBartForSequenceClassification""",
						    """MBartModel""",
						    """MBartPreTrainedModel""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= [
						    """TFMBartForConditionalGeneration""",
						    """TFMBartModel""",
						    """TFMBartPreTrainedModel""",
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= [
						    """FlaxMBartForConditionalGeneration""",
						    """FlaxMBartForQuestionAnswering""",
						    """FlaxMBartForSequenceClassification""",
						    """FlaxMBartModel""",
						    """FlaxMBartPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_mbart import MBartTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_mbart_fast import MBartTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mbart import (
												    MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MBartForCausalLM,
												    MBartForConditionalGeneration,
												    MBartForQuestionAnswering,
												    MBartForSequenceClassification,
												    MBartModel,
												    MBartPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_mbart import (
												    FlaxMBartForConditionalGeneration,
												    FlaxMBartForQuestionAnswering,
												    FlaxMBartForSequenceClassification,
												    FlaxMBartModel,
												    FlaxMBartPreTrainedModel,
												)

else:
						import sys

						lowerCamelCase__			= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
