





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase__  :     Tuple   			=logging.get_logger(__name__)

UpperCAmelCase__  :     str   			={
    '''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve/main/config.json''',
    '''funnel-transformer/small-base''': '''https://huggingface.co/funnel-transformer/small-base/resolve/main/config.json''',
    '''funnel-transformer/medium''': '''https://huggingface.co/funnel-transformer/medium/resolve/main/config.json''',
    '''funnel-transformer/medium-base''': '''https://huggingface.co/funnel-transformer/medium-base/resolve/main/config.json''',
    '''funnel-transformer/intermediate''': (
        '''https://huggingface.co/funnel-transformer/intermediate/resolve/main/config.json'''
    ),
    '''funnel-transformer/intermediate-base''': (
        '''https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/config.json'''
    ),
    '''funnel-transformer/large''': '''https://huggingface.co/funnel-transformer/large/resolve/main/config.json''',
    '''funnel-transformer/large-base''': '''https://huggingface.co/funnel-transformer/large-base/resolve/main/config.json''',
    '''funnel-transformer/xlarge''': '''https://huggingface.co/funnel-transformer/xlarge/resolve/main/config.json''',
    '''funnel-transformer/xlarge-base''': '''https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/config.json''',
}

class  __lowercase       (  _a      ):
				__A								=			"""funnel"""
				__A								=			{
				    """hidden_size""": """d_model""",
				    """num_attention_heads""": """n_head""",
				}


				def __init__(						self				,	UpperCAmelCase_=30522				,	UpperCAmelCase_=[4, 4, 4]				,	UpperCAmelCase_=None				,	UpperCAmelCase_=2				,	UpperCAmelCase_=768				,	UpperCAmelCase_=12				,	UpperCAmelCase_=64				,	UpperCAmelCase_=3072				,	UpperCAmelCase_="gelu_new"				,	UpperCAmelCase_=0.1				,	UpperCAmelCase_=0.1				,	UpperCAmelCase_=0.0				,	UpperCAmelCase_=0.1				,	UpperCAmelCase_=None				,	UpperCAmelCase_=1E-9				,	UpperCAmelCase_="mean"				,	UpperCAmelCase_="relative_shift"				,	UpperCAmelCase_=True				,	UpperCAmelCase_=True				,	UpperCAmelCase_=True				,	**UpperCAmelCase_				,	):
								lowerCamelCase			=vocab_size
								lowerCamelCase			=block_sizes
								lowerCamelCase			=[1] * len(__lowerCAmelCase							) if block_repeats is None else block_repeats
								assert len(__lowerCAmelCase							) == len(
								    self.block_repeats							), "`block_sizes` and `block_repeats` should have the same length."
								lowerCamelCase			=num_decoder_layers
								lowerCamelCase			=d_model
								lowerCamelCase			=n_head
								lowerCamelCase			=d_head
								lowerCamelCase			=d_inner
								lowerCamelCase			=hidden_act
								lowerCamelCase			=hidden_dropout
								lowerCamelCase			=attention_dropout
								lowerCamelCase			=activation_dropout
								lowerCamelCase			=initializer_range
								lowerCamelCase			=initializer_std
								lowerCamelCase			=layer_norm_eps
								assert pooling_type in [
								    "mean",
								    "max",
								], f"""Got {pooling_type} for `pooling_type` but only 'mean' and 'max' are supported."""
								lowerCamelCase			=pooling_type
								assert attention_type in [
								    "relative_shift",
								    "factorized",
								], f"""Got {attention_type} for `attention_type` but only 'relative_shift' and 'factorized' are supported."""
								lowerCamelCase			=attention_type
								lowerCamelCase			=separate_cls
								lowerCamelCase			=truncate_seq
								lowerCamelCase			=pool_q_only

								super().__init__(**__lowerCAmelCase							)


				@property
				def _snake_case    (						self							):
								return sum(self.block_sizes							)


				@num_hidden_layers.setter
				def _snake_case    (						self				,	UpperCAmelCase_							):
								raise NotImplementedError(
								    """This model does not support the setting of `num_hidden_layers`. Please set `block_sizes`."""							)


				@property
				def _snake_case    (						self							):
								return len(self.block_sizes							)


				@num_blocks.setter
				def _snake_case    (						self				,	UpperCAmelCase_							):
								raise NotImplementedError("""This model does not support the setting of `num_blocks`. Please set `block_sizes`."""							)












from json import JSONDecodeError  # Workaround for requests.exceptions.JSONDecodeError

import requests





def        _lowercase   (  _UpperCAmelCase = "isbn/0140328726"			)  ->					dict:
				lowerCamelCase			=olid.strip().strip("""/"""			)  # Remove leading/trailing whitespace & slashes
				if new_olid.count("""/"""			) != 1:
								lowerCamelCase			=F"""{olid} is not a valid Open Library olid"""
								raise ValueError(_UpperCAmelCase			)
				return requests.get(F"""https://openlibrary.org/{new_olid}.json"""			).json()





def        _lowercase   (  _UpperCAmelCase			)  ->					dict:
				lowerCamelCase			={
				    """title""": """Title""",
				    """publish_date""": """Publish date""",
				    """authors""": """Authors""",
				    """number_of_pages""": """Number of pages:""",
				    """first_sentence""": """First sentence""",
				    """isbn_10""": """ISBN (10)""",
				    """isbn_13""": """ISBN (13)""",
				}
				lowerCamelCase			={better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
				lowerCamelCase			=[
				    get_openlibrary_data(author["""key"""]			)["""name"""] for author in data["""Authors"""]
				]
				lowerCamelCase			=data["""First sentence"""]["""value"""]
				for key, value in data.items():
								if isinstance(_UpperCAmelCase     , _UpperCAmelCase			):
												lowerCamelCase			=""", """.join(_UpperCAmelCase			)
				return data


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							while True:
														UpperCAmelCase__  :     List[str]   			=input('''\nEnter the ISBN code to search (or \'quit\' to stop): ''').strip()
														if isbn.lower() in ("", "q", "quit", "exit", "stop"):
																					break

														if len(isbn) not in (10, 13) or not isbn.isdigit():
																					print(F"Sorry, {isbn} is not a valid ISBN.  Please, input a valid ISBN.")
																					continue

														print(F"\nSearching Open Library for ISBN: {isbn}...\n")

														try:
																					UpperCAmelCase__  :     Dict   			=summarize_book(get_openlibrary_data(F"isbn/{isbn}"))
																					print('''\n'''.join(F"{key}: {value}" for key, value in book_summary.items()))
														except JSONDecodeError:  # Workaround for requests.exceptions.RequestException:
																					print(F"Sorry, there are no results for ISBN: {isbn}.")





