


"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase						:				Optional[Any]             =      {
    "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Tuple             =      ["ConvNextFeatureExtractor"]
	UpperCamelCase						:				List[str]             =      ["ConvNextImageProcessor"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Optional[int]             =      [
	    "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "ConvNextForImageClassification",
	    "ConvNextModel",
	    "ConvNextPreTrainedModel",
	    "ConvNextBackbone",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Any             =      [
	    "TFConvNextForImageClassification",
	    "TFConvNextModel",
	    "TFConvNextPreTrainedModel",
	]

if TYPE_CHECKING:
	from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_convnext import ConvNextFeatureExtractor
		from .image_processing_convnext import ConvNextImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_convnext import (
		    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ConvNextBackbone,
		    ConvNextForImageClassification,
		    ConvNextModel,
		    ConvNextPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
	import sys

	UpperCamelCase						:				Optional[int]             =      _LazyModule(__name__, globals()["__file__"], _import_structure)









"""simple docstring"""


import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class 			lowerCamelCase__						(   UpperCAmelCase_							,    unittest.TestCase			):
						lowerCAmelCase       =     TransfoXLTokenizer
						lowerCAmelCase       =     False
						lowerCAmelCase       =     False







						def __a						(							self   :    Union[str, Any]		):
								super().setUp()

								A					       = [
								    '<unk>',
								    '[CLS]',
								    '[SEP]',
								    'want',
								    'unwanted',
								    'wa',
								    'un',
								    'running',
								    ',',
								    'low',
								    'l',
								]
								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 __a						(							self   :    int			,			**_lowercase   :    List[str]		):
								A					       = True
								return TransfoXLTokenizer.from_pretrained(self.tmpdirname			,			**_lowercase		)







						def __a						(							self   :    int			,			_lowercase   :    List[Any]		):
								A					       = '<unk> UNwanted , running'
								A					       = '<unk> unwanted, running'
								return input_text, output_text







						def __a						(							self   :    List[str]		):
								A					       = TransfoXLTokenizer(vocab_file=self.vocab_file			,			lower_case=_lowercase		)

								A					       = tokenizer.tokenize('<unk> UNwanted , running'		)
								self.assertListEqual(_lowercase			,			['<unk>', 'unwanted', ',', 'running']		)

								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase		)			,			[0, 4, 8, 7]		)







						def __a						(							self   :    int		):
								A					       = TransfoXLTokenizer(lower_case=_lowercase		)

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







						def __a						(							self   :    Optional[Any]		):
								A					       = TransfoXLTokenizer(lower_case=_lowercase		)

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







						def __a						(							self   :    str		):
								A					       = TransfoXLTokenizer(lower_case=_lowercase		)
								A					       = 'Hello (bracket) and side-scrolled [and] Henry\'s $5,000 with 3.34 m. What\'s up!?'
								A					       = [
								    'Hello',
								    '(',
								    'bracket',
								    ')',
								    'and',
								    'side',
								    '@-@',
								    'scrolled',
								    '[',
								    'and',
								    ']',
								    'Henry',
								    '\'s',
								    '$',
								    '5',
								    '@,@',
								    '000',
								    'with',
								    '3',
								    '@.@',
								    '34',
								    'm',
								    '.',
								    'What',
								    '\'s',
								    'up',
								    '!',
								    '?',
								]

								self.assertListEqual(tokenizer.tokenize(_lowercase		)			,			_lowercase		)

								self.assertEqual(tokenizer.convert_tokens_to_string(_lowercase		)			,			_lowercase		)







						def __a						(							self   :    Dict		):
								A					       = self.get_tokenizer()
								A					       = len(_lowercase		)

								tokenizer.add_tokens(['new1', 'new2']		)
								tokenizer.move_added_token('new1'			,			1		)

								# Check that moved token is not copied (duplicate)
								self.assertEqual(len(_lowercase		)			,			original_len + 2		)
								# Check that token is moved to specified id
								self.assertEqual(tokenizer.encode('new1'		)			,			[1]		)
								self.assertEqual(tokenizer.decode([1]		)			,			'new1'		)





