



from datetime import datetime

import requests


def A						(       __UpperCamelCase					)						->      bytes:
			A__       =    'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
			A__       =    requests.get(base_url + url					).json()[0]['urls'][0]['src']
			return requests.get(__UpperCamelCase					).content


if __name__ == "__main__":
							SCREAMING_SNAKE_CASE__       =      input('''Enter Video/IGTV url: ''').strip()
							SCREAMING_SNAKE_CASE__       =      f'{datetime.now():%Y-%m-%d_%H:%M:%S}.mp4'
							with open(file_name, '''wb''') as fp:
														fp.write(download_video(url))
							print(f'Done. Video saved to disk as {file_name}.')









from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType


class      __lowerCAmelCase     (		UpperCAmelCase_      ):
					"""simple docstring"""






					A__				:		Union[str, Any]			       =    ["image_processor", "tokenizer"]
					A__				:		Optional[Any]			       =    "BridgeTowerImageProcessor"
					A__				:		List[Any]			       =    ("RobertaTokenizer", "RobertaTokenizerFast")



					def __init__(     self					:       List[Any]				,					_snake_case					:       Optional[Any]				,					_snake_case					:       Optional[int]					):






								"""simple docstring"""


								super().__init__(_snake_case				,					_snake_case					)



					def __call__(     self					:       List[Any]				,					_snake_case					:       int				,					_snake_case					:       Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None				,					_snake_case					:       bool = True				,					_snake_case					:       Union[bool, str, PaddingStrategy] = False				,					_snake_case					:       Union[bool, str, TruncationStrategy] = None				,					_snake_case					:       Optional[int] = None				,					_snake_case					:       int = 0				,					_snake_case					:       Optional[int] = None				,					_snake_case					:       Optional[bool] = None				,					_snake_case					:       Optional[bool] = None				,					_snake_case					:       bool = False				,					_snake_case					:       bool = False				,					_snake_case					:       bool = False				,					_snake_case					:       bool = False				,					_snake_case					:       bool = True				,					_snake_case					:       Optional[Union[str, TensorType]] = None				,					**_snake_case					:       Optional[int]				,					):






								"""simple docstring"""


								A__       =    self.tokenizer(
								    text=_snake_case				,					add_special_tokens=_snake_case				,					padding=_snake_case				,					truncation=_snake_case				,					max_length=_snake_case				,					stride=_snake_case				,					pad_to_multiple_of=_snake_case				,					return_token_type_ids=_snake_case				,					return_attention_mask=_snake_case				,					return_overflowing_tokens=_snake_case				,					return_special_tokens_mask=_snake_case				,					return_offsets_mapping=_snake_case				,					return_length=_snake_case				,					verbose=_snake_case				,					return_tensors=_snake_case				,					**_snake_case				,					)
								# add pixel_values + pixel_mask
								A__       =    self.image_processor(
								    _snake_case				,					return_tensors=_snake_case				,					do_normalize=_snake_case				,					do_center_crop=_snake_case				,					**_snake_case					)
								encoding.update(_snake_case					)

								return encoding



					def     _a							(     self					:       Any				,					*_snake_case					:       Tuple				,					**_snake_case					:       List[Any]					):






								"""simple docstring"""


								return self.tokenizer.batch_decode(*_snake_case				,					**_snake_case					)



					def     _a							(     self					:       Dict				,					*_snake_case					:       Dict				,					**_snake_case					:       List[str]					):






								"""simple docstring"""


								return self.tokenizer.decode(*_snake_case				,					**_snake_case					)



					@property
					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


								A__       =    self.tokenizer.model_input_names
								A__       =    self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names					)					)




