



"""simple docstring"""






from typing import TYPE_CHECKING

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


lowerCamelCase				:     Union[str, Any]								=  {
    """configuration_bart""": ["""BART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BartConfig""", """BartOnnxConfig"""],
    """tokenization_bart""": ["""BartTokenizer"""],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase				:     Dict								=  ["""BartTokenizerFast"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase				:     List[Any]								=  [
        """BART_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """BartForCausalLM""",
        """BartForConditionalGeneration""",
        """BartForQuestionAnswering""",
        """BartForSequenceClassification""",
        """BartModel""",
        """BartPretrainedModel""",
        """PretrainedBartModel""",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase				:     Any								=  [
        """TFBartForConditionalGeneration""",
        """TFBartForSequenceClassification""",
        """TFBartModel""",
        """TFBartPretrainedModel""",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase				:     str								=  [
        """FlaxBartDecoderPreTrainedModel""",
        """FlaxBartForCausalLM""",
        """FlaxBartForConditionalGeneration""",
        """FlaxBartForQuestionAnswering""",
        """FlaxBartForSequenceClassification""",
        """FlaxBartModel""",
        """FlaxBartPreTrainedModel""",
    ]

if TYPE_CHECKING:
    from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
    from .tokenization_bart import BartTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_bart_fast import BartTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_bart import (
            BART_PRETRAINED_MODEL_ARCHIVE_LIST,
            BartForCausalLM,
            BartForConditionalGeneration,
            BartForQuestionAnswering,
            BartForSequenceClassification,
            BartModel,
            BartPretrainedModel,
            PretrainedBartModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_bart import (
            TFBartForConditionalGeneration,
            TFBartForSequenceClassification,
            TFBartModel,
            TFBartPretrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_bart import (
            FlaxBartDecoderPreTrainedModel,
            FlaxBartForCausalLM,
            FlaxBartForConditionalGeneration,
            FlaxBartForQuestionAnswering,
            FlaxBartForSequenceClassification,
            FlaxBartModel,
            FlaxBartPreTrainedModel,
        )

else:
    import sys

    lowerCamelCase				:     Tuple								=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




"""simple docstring"""
import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput



@dataclass
class      _UpperCAmelCase					(				__snake_case							):






		'''simple docstring'''

		lowerCamelCase__           =42
		lowerCamelCase__           =None
		lowerCamelCase__           =None



class      _UpperCAmelCase					(				unittest.TestCase							):






		'''simple docstring'''

		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Union[str, Any]         =							ModelOutputTest(a=30   )
			self.assertEqual(x.a							,			30   )
			self.assertIsNone(x.b   )
			self.assertIsNone(x.c   )
			with self.assertRaises(a_   ):
				__snake_case      :		str         =							x.d



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Union[str, Any]         =							ModelOutputTest(a=30							,			b=10   )
			self.assertEqual(x[0]							,			30   )
			self.assertEqual(x[1]							,			10   )
			self.assertEqual(x[:2]							,			(30, 10)   )
			self.assertEqual(x[:]							,			(30, 10)   )

			__snake_case      :		List[Any]         =							ModelOutputTest(a=30							,			c=10   )
			self.assertEqual(x[0]							,			30   )
			self.assertEqual(x[1]							,			10   )
			self.assertEqual(x[:2]							,			(30, 10)   )
			self.assertEqual(x[:]							,			(30, 10)   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Optional[int]         =							ModelOutputTest(a=30							,			b=10   )
			self.assertEqual(x['''a''']							,			30   )
			self.assertEqual(x['''b''']							,			10   )
			with self.assertRaises(a_   ):
				__snake_case      :		Optional[int]         =							x['''c''']

			__snake_case      :		Any         =							ModelOutputTest(a=30							,			c=10   )
			self.assertEqual(x['''a''']							,			30   )
			self.assertEqual(x['''c''']							,			10   )
			with self.assertRaises(a_   ):
				__snake_case      :		Optional[int]         =							x['''b''']



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Optional[int]         =							ModelOutputTest(a=30   )
			self.assertEqual(list(x.keys()   )							,			['''a''']   )
			self.assertEqual(list(x.values()   )							,			[30]   )
			self.assertEqual(list(x.items()   )							,			[('''a''', 30)]   )
			self.assertEqual(list(a_   )							,			['''a''']   )

			__snake_case      :		Optional[int]         =							ModelOutputTest(a=30							,			b=10   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''b''']   )
			self.assertEqual(list(x.values()   )							,			[30, 10]   )
			self.assertEqual(list(x.items()   )							,			[('''a''', 30), ('''b''', 10)]   )
			self.assertEqual(list(a_   )							,			['''a''', '''b''']   )

			__snake_case      :		Optional[Any]         =							ModelOutputTest(a=30							,			c=10   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''c''']   )
			self.assertEqual(list(x.values()   )							,			[30, 10]   )
			self.assertEqual(list(x.items()   )							,			[('''a''', 30), ('''c''', 10)]   )
			self.assertEqual(list(a_   )							,			['''a''', '''c''']   )

			with self.assertRaises(a_   ):
				__snake_case      :		Optional[int]         =							x.update({'''d''': 20}   )
			with self.assertRaises(a_   ):
				del x["a"]
			with self.assertRaises(a_   ):
				__snake_case      :		Union[str, Any]         =							x.pop('''a'''   )
			with self.assertRaises(a_   ):
				__snake_case      :		Optional[Any]         =							x.setdefault('''d'''							,			32   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[str]         =							ModelOutputTest(a=30   )
			__snake_case      :		Tuple         =							10
			self.assertEqual(x.a							,			10   )
			self.assertEqual(x['''a''']							,			10   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[str]         =							ModelOutputTest(a=30   )
			__snake_case      :		Any         =							10
			self.assertEqual(x.a							,			10   )
			self.assertEqual(x['''a''']							,			10   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		int         =							ModelOutputTest({'''a''': 30, '''b''': 10}   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''b''']   )
			self.assertEqual(x.a							,			30   )
			self.assertEqual(x.b							,			10   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Any         =							ModelOutputTest([('''a''', 30), ('''b''', 10)]   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''b''']   )
			self.assertEqual(x.a							,			30   )
			self.assertEqual(x.b							,			10   )

			with self.assertRaises(a_   ):
				__snake_case      :		List[Any]         =							ModelOutputTest([('''a''', 30), (10, 10)]   )

			__snake_case      :		Union[str, Any]         =							ModelOutputTest(a=(30, 30)   )
			self.assertEqual(list(x.keys()   )							,			['''a''']   )
			self.assertEqual(x.a							,			(30, 30)   )





