




"""simple docstring"""







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__					(					_a						,				unittest.TestCase					):
						_a    						=						LayoutLMTokenizer
						_a    						=						LayoutLMTokenizerFast
						_a    						=						True
						_a    						=						True


						def   __lowercase (							self				:			List[Any]					):
										super().setUp()

										lowerCAmelCase  =				[
										    """[UNK]""",
										    """[CLS]""",
										    """[SEP]""",
										    """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   __lowercase (							self				:			Tuple						,						**lowerCAmelCase				:			Optional[Any]					):
										return LayoutLMTokenizer.from_pretrained(self.tmpdirname						,						**lowerCAmelCase					)


						def   __lowercase (							self				:			Optional[int]						,						lowerCAmelCase				:			List[str]					):
										lowerCAmelCase  =				"""UNwant\u00E9d,running"""
										lowerCAmelCase  =				"""unwanted, running"""
										return input_text, output_text


						def   __lowercase (							self				:			Optional[Any]					):
										lowerCAmelCase  =				self.tokenizer_class(self.vocab_file					)

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




						def   __lowercase (							self				:			List[Any]					):
										pass











"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a      =							{
    'configuration_time_series_transformer': [
        'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TimeSeriesTransformerConfig',
    ],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a      =							[
		    'TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TimeSeriesTransformerForPrediction',
		    'TimeSeriesTransformerModel',
		    'TimeSeriesTransformerPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_time_series_transformer import (
		    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    TimeSeriesTransformerConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_time_series_transformer import (
				    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TimeSeriesTransformerForPrediction,
				    TimeSeriesTransformerModel,
				    TimeSeriesTransformerPreTrainedModel,
				)

else:
		import sys

		a      =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





