
'''simple docstring'''







from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
					lowercase					:							str   =      input("Enter image url: ").strip()
					print(F'''Downloading image from {url} ...''')
					lowercase					:							Union[str, Any]   =      BeautifulSoup(requests.get(url).content, "html.parser")
					# The image URL is in the content field of the first meta tag with property og:image
					lowercase					:							List[Any]   =      soup.find("meta", {"property": "og:image"})["content"]
					lowercase					:							List[Any]   =      requests.get(image_url).content
					lowercase					:							List[str]   =      F'''{datetime.now():%Y-%m-%d_%H:%M:%S}.jpg'''
					with open(file_name, "wb") as fp:
										fp.write(image_data)
					print(F'''Done. Image saved to disk as {file_name}.''')



'''simple docstring'''







from typing import TYPE_CHECKING

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


lowercase					:							str   =      {
    "configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase					:							Any   =      [
					    "NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "NezhaForNextSentencePrediction",
					    "NezhaForMaskedLM",
					    "NezhaForPreTraining",
					    "NezhaForMultipleChoice",
					    "NezhaForQuestionAnswering",
					    "NezhaForSequenceClassification",
					    "NezhaForTokenClassification",
					    "NezhaModel",
					    "NezhaPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_nezha import (
										    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
										    NezhaForMaskedLM,
										    NezhaForMultipleChoice,
										    NezhaForNextSentencePrediction,
										    NezhaForPreTraining,
										    NezhaForQuestionAnswering,
										    NezhaForSequenceClassification,
										    NezhaForTokenClassification,
										    NezhaModel,
										    NezhaPreTrainedModel,
										)


else:
					import sys

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

