



'''simple docstring'''

from typing import TYPE_CHECKING

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


_UpperCAmelCase				: List[str]							    =				{
    "configuration_whisper": ["WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP", "WhisperConfig", "WhisperOnnxConfig"],
    "feature_extraction_whisper": ["WhisperFeatureExtractor"],
    "processing_whisper": ["WhisperProcessor"],
    "tokenization_whisper": ["WhisperTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: str							    =				["WhisperTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: Any							    =				[
	    "WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "WhisperForConditionalGeneration",
	    "WhisperModel",
	    "WhisperPreTrainedModel",
	    "WhisperForAudioClassification",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: Union[str, Any]							    =				[
	    "TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFWhisperForConditionalGeneration",
	    "TFWhisperModel",
	    "TFWhisperPreTrainedModel",
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: Optional[Any]							    =				[
	    "FlaxWhisperForConditionalGeneration",
	    "FlaxWhisperModel",
	    "FlaxWhisperPreTrainedModel",
	    "FlaxWhisperForAudioClassification",
	]


if TYPE_CHECKING:
	from .configuration_whisper import WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP, WhisperConfig, WhisperOnnxConfig
	from .feature_extraction_whisper import WhisperFeatureExtractor
	from .processing_whisper import WhisperProcessor
	from .tokenization_whisper import WhisperTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_whisper_fast import WhisperTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_whisper import (
		    WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    WhisperForAudioClassification,
		    WhisperForConditionalGeneration,
		    WhisperModel,
		    WhisperPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_whisper import (
		    TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFWhisperForConditionalGeneration,
		    TFWhisperModel,
		    TFWhisperPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_whisper import (
		    FlaxWhisperForAudioClassification,
		    FlaxWhisperForConditionalGeneration,
		    FlaxWhisperModel,
		    FlaxWhisperPreTrainedModel,
		)

else:
	import sys

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





'''simple docstring'''

import requests
from bsa import BeautifulSoup

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase):
						__lowerCAmelCase							       =				BeautifulSoup(requests.get(lowerCamelCase,				params=lowerCamelCase).content,				'''html.parser''')
						__lowerCAmelCase							       =				soup.find('''div''',				attrs={'''class''': '''gs_ri'''})
						__lowerCAmelCase							       =				div.find('''div''',				attrs={'''class''': '''gs_fl'''}).find_all('''a''')
						return anchors[2].get_text()


if __name__ == "__main__":
	_UpperCAmelCase				: Union[str, Any]							    =				{
	    """title""": (
	        """Precisely geometry controlled microsupercapacitors for ultrahigh areal """
	        """capacitance, volumetric capacitance, and energy density"""
	    ),
	    """journal""": """Chem. Mater.""",
	    """volume""": 3_0,
	    """pages""": """3979-3990""",
	    """year""": 2_0_1_8,
	    """hl""": """en""",
	}
	print(get_citation("""https://scholar.google.com/scholar_lookup""", params=params))

