
import unittest

from transformers import DonutProcessor


lowercase__	:Optional[int]										=					"naver-clova-ix/donut-base"







class        lowercase	(      unittest.TestCase	):




							def 				A__   (       self):
												lowercase					=		DonutProcessor.from_pretrained(A__)





							def 				A__   (       self):
												lowercase					=		{
												    '''name''': '''John Doe''',
												    '''age''': '''99''',
												    '''city''': '''Atlanta''',
												    '''state''': '''GA''',
												    '''zip''': '''30301''',
												    '''phone''': '''123-4567''',
												    '''nicknames''': [{'''nickname''': '''Johnny'''}, {'''nickname''': '''JD'''}],
												}

												lowercase					=		(
												    '''<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>'''
												    '''<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>'''
												    '''<s_nicknames><s_nickname>Johnny</s_nickname>'''
												    '''<sep/><s_nickname>JD</s_nickname></s_nicknames>'''
												)
												lowercase					=		self.processor.tokenajson(A__)

												self.assertDictEqual(A__     ,A__)






from typing import TYPE_CHECKING

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


lowercase__	:Tuple										=					{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__	:Union[str, Any]										=					[
							    "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "BioGptForCausalLM",
							    "BioGptForTokenClassification",
							    "BioGptForSequenceClassification",
							    "BioGptModel",
							    "BioGptPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
							from .tokenization_biogpt import BioGptTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_biogpt import (
														    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BioGptForCausalLM,
														    BioGptForSequenceClassification,
														    BioGptForTokenClassification,
														    BioGptModel,
														    BioGptPreTrainedModel,
														)


else:
							import sys

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




