
import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_rjieba
@require_tokenizers
class        SCREAMING_SNAKE_CASE__    (							SCREAMING_SNAKE_CASE_   ,		unittest.TestCase    ):

							"""simple docstring"""






							_snake_case     		=  RoFormerTokenizer
							_snake_case     		=  RoFormerTokenizerFast
							_snake_case     		=  True
							_snake_case     		=  True



							def     A__		(  self			)->   Optional[Any]:





													'''simple docstring'''






													super().setUp()



							def     A__		(  self     ,	**SCREAMING_SNAKE_CASE_			)->   List[str]:





													'''simple docstring'''






													return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''     ,	**SCREAMING_SNAKE_CASE_			)



							def     A__		(  self     ,	**SCREAMING_SNAKE_CASE_			)->   Dict:





													'''simple docstring'''






													return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''     ,	**SCREAMING_SNAKE_CASE_			)



							def     A__		(  self			)->   List[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			'''永和服装饰品有限公司,今天天气非常好'''
													__UpperCamelCase       =			'''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
													return input_text, output_text



							def     A__		(  self			)->   List[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			self.get_tokenizer()
													__UpperCamelCase  ,							__UpperCamelCase       =			self.get_chinese_input_output_texts()
													__UpperCamelCase       =			tokenizer.tokenize(SCREAMING_SNAKE_CASE_			)

													self.assertListEqual(SCREAMING_SNAKE_CASE_     ,	output_text.split()			)

													__UpperCamelCase       =			tokens + [tokenizer.unk_token]
													__UpperCamelCase       =			[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_			)     ,	SCREAMING_SNAKE_CASE_			)



							def     A__		(  self			)->   Union[str, Any]:





													'''simple docstring'''






													__UpperCamelCase       =			self.get_rust_tokenizer()
													__UpperCamelCase  ,							__UpperCamelCase       =			self.get_chinese_input_output_texts()
													__UpperCamelCase       =			tokenizer.tokenize(SCREAMING_SNAKE_CASE_			)
													self.assertListEqual(SCREAMING_SNAKE_CASE_     ,	output_text.split()			)
													__UpperCamelCase       =			tokens + [tokenizer.unk_token]
													__UpperCamelCase       =			[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_			)     ,	SCREAMING_SNAKE_CASE_			)



							def     A__		(  self			)->   Dict:





													'''simple docstring'''






													pass



							def     A__		(  self			)->   List[str]:





													'''simple docstring'''






													pass



							def     A__		(  self			)->   Optional[int]:





													'''simple docstring'''






													pass






from typing import TYPE_CHECKING

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


lowercase__							:							Dict									=			{"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig", "ViTOnnxConfig"]}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							Tuple									=			["ViTFeatureExtractor"]
				lowercase__							:							str									=			["ViTImageProcessor"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							List[str]									=			[
				    "VIT_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "ViTForImageClassification",
				    "ViTForMaskedImageModeling",
				    "ViTModel",
				    "ViTPreTrainedModel",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							Tuple									=			[
				    "TFViTForImageClassification",
				    "TFViTModel",
				    "TFViTPreTrainedModel",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							List[Any]									=			[
				    "FlaxViTForImageClassification",
				    "FlaxViTModel",
				    "FlaxViTPreTrainedModel",
				]

if TYPE_CHECKING:
				from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_vit import ViTFeatureExtractor
								from .image_processing_vit import ViTImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_vit import (
								    VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ViTForImageClassification,
								    ViTForMaskedImageModeling,
								    ViTModel,
								    ViTPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
				import sys

				lowercase__							:							List[Any]									=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




