"""simple docstring"""






from transformers.models.cpm.tokenization_cpm import CpmTokenizer
from transformers.testing_utils import custom_tokenizers

from ..xlnet.test_modeling_xlnet import XLNetModelTest
@custom_tokenizers
class   UpperCAmelCase__				(    __lowerCamelCase			):


	"""simple docstring"""







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE )    ->	Tuple:
							return True







	def       A    (			self )    ->	List[str]:
							a_							:			Any     		=					CpmTokenizer.from_pretrained("TsinghuaAI/CPM-Generate" )
							a_							:			str     		=					"Hugging Face大法好，谁用谁知道。"
							a_							:			Dict     		=					"Hugging Face大法好,谁用谁知道。<unk>"
							a_							:			List[Any]     		=					"▁Hu gg ing ▁ ▂ ▁F ace ▁大法 ▁好 ▁ , ▁谁 ▁用 ▁谁 ▁知 道 ▁ 。".split()

							a_							:			Optional[Any]     		=					tokenizer.tokenize(_SCREAMING_SNAKE_CASE )
							self.assertListEqual(_SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE )

							a_							:			int     		=					tokens + [tokenizer.unk_token]

							a_							:			int     		=					[1_3_7_8_9, 1_3_2_8_3, 1_4_2_1, 8, 1_0, 1_1_6_4, 1_3_6_0_8, 1_6_5_2_8, 6_3, 8, 9, 4_4_0, 1_0_8, 4_4_0, 1_2_1, 9_0, 8, 1_2, 0]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE )       ,     _SCREAMING_SNAKE_CASE )

							a_							:			Optional[int]     		=					tokenizer.decode(_SCREAMING_SNAKE_CASE )
							self.assertEqual(_SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE )





"""simple docstring"""






from typing import TYPE_CHECKING

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


UpperCamelCase     					=     {'configuration_levit': ['LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LevitConfig', 'LevitOnnxConfig']}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase     					=     ['LevitFeatureExtractor']
				UpperCamelCase     					=     ['LevitImageProcessor']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase     					=     [
				    'LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'LevitForImageClassification',
				    'LevitForImageClassificationWithTeacher',
				    'LevitModel',
				    'LevitPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig, LevitOnnxConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_levit import LevitFeatureExtractor
								from .image_processing_levit import LevitImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_levit import (
								    LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    LevitForImageClassification,
								    LevitForImageClassificationWithTeacher,
								    LevitModel,
								    LevitPreTrainedModel,
								)
else:
				import sys

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




