





'''simple docstring'''






from typing import TYPE_CHECKING

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


lowerCAmelCase									=   {
    """configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase									=   ["""BloomTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase									=   [
					    """BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """BloomForCausalLM""",
					    """BloomModel""",
					    """BloomPreTrainedModel""",
					    """BloomForSequenceClassification""",
					    """BloomForTokenClassification""",
					    """BloomForQuestionAnswering""",
					]

if TYPE_CHECKING:
					from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_bloom_fast import BloomTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_bloom import (
										    BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BloomForCausalLM,
										    BloomForQuestionAnswering,
										    BloomForSequenceClassification,
										    BloomForTokenClassification,
										    BloomModel,
										    BloomPreTrainedModel,
										)

else:
					import sys

					lowerCAmelCase									=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)











"""simple docstring"""
from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
			lowerCAmelCase__    						=			input('Enter image url: ').strip()
			print(F'Downloading image from {url} ...')
			lowerCAmelCase__    						=			BeautifulSoup(requests.get(url).content, 'html.parser')
			# The image URL is in the content field of the first meta tag with property og:image
			lowerCAmelCase__    						=			soup.find('meta', {'property': 'og:image'})['content']
			lowerCAmelCase__    						=			requests.get(image_url).content
			lowerCAmelCase__    						=			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}.')

