





"""simple docstring"""






from typing import TYPE_CHECKING

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


A	     =					{'''configuration_mbart''': ['''MBART_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MBartConfig''', '''MBartOnnxConfig''']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					['''MBartTokenizer''']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					['''MBartTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					[
		    '''MBART_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MBartForCausalLM''',
		    '''MBartForConditionalGeneration''',
		    '''MBartForQuestionAnswering''',
		    '''MBartForSequenceClassification''',
		    '''MBartModel''',
		    '''MBartPreTrainedModel''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					[
		    '''TFMBartForConditionalGeneration''',
		    '''TFMBartModel''',
		    '''TFMBartPreTrainedModel''',
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					[
		    '''FlaxMBartForConditionalGeneration''',
		    '''FlaxMBartForQuestionAnswering''',
		    '''FlaxMBartForSequenceClassification''',
		    '''FlaxMBartModel''',
		    '''FlaxMBartPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mbart import MBartTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mbart_fast import MBartTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mbart import (
				    MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MBartForCausalLM,
				    MBartForConditionalGeneration,
				    MBartForQuestionAnswering,
				    MBartForSequenceClassification,
				    MBartModel,
				    MBartPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_mbart import (
				    FlaxMBartForConditionalGeneration,
				    FlaxMBartForQuestionAnswering,
				    FlaxMBartForSequenceClassification,
				    FlaxMBartModel,
				    FlaxMBartPreTrainedModel,
				)

else:
		import sys

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






"""simple docstring"""






def       __A (     a_  :float)						->						float:

				if edge <= 0 or not isinstance(a_				,    a_):
								raise ValueError('''Length must be a positive.''')
				return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)

def       __A (     a_  :float)						->						float:

				if edge <= 0 or not isinstance(a_				,    a_):
								raise ValueError('''Length must be a positive.''')
				return ((15 + (7 * (5 ** (1 / 2)))) / 4) * (edge**3)


if __name__ == "__main__":
		import doctest

		doctest.testmod()