"""simple docstring"""






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

import requests



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



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							{
				    '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)',
				}
				UpperCAmelCase__             =							{better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
				UpperCAmelCase__             =							[
				    get_openlibrary_data(author['key']       )['name'] for author in data['Authors']
				]
				UpperCAmelCase__             =							data['First sentence']['value']
				for key, value in data.items():
								if isinstance(lowerCamelCase					,			lowerCamelCase       ):
												UpperCAmelCase__             =							', '.join(lowerCamelCase       )
				return data


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						while True:
												lowerCAmelCase__  :  int						     =	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:
																		lowerCAmelCase__  :  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}.""")




"""simple docstring"""






import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

lowerCAmelCase__  :  Optional[Any]						     =	logging.getLogger()



def   a_						(					):
				UpperCAmelCase__             =							argparse.ArgumentParser()
				parser.add_argument('-f'       )
				UpperCAmelCase__             =							parser.parse_args()
				return args.f







class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	int			):
									UpperCAmelCase__             =							logging.StreamHandler(sys.stdout			)
									logger.addHandler(lowerCamelCase__			)







					def 		__lowerCAmelCase						(				self   :	Optional[Any]    ,lowerCamelCase__   :	Union[str, Any]			):
									UpperCAmelCase__             =							get_gpu_count()

									if n_gpu > 1:
													pass
													# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
													# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
													# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
													# cmd = [sys.executable] + distributed_args + args
													# execute_subprocess_async(cmd, env=self.get_env())
													# XXX: test the results - need to save them first into .json file
									else:
													args.insert(0    ,'run_glue_deebert.py'			)
													with patch.object(lowerCamelCase__    ,'argv'    ,lowerCamelCase__			):
																	UpperCAmelCase__             =							run_glue_deebert.main()
																	for value in result.values():
																					self.assertGreaterEqual(lowerCamelCase__    ,0.6_6_6			)







					@slow
					@require_torch_non_multi_gpu
					def 		__lowerCAmelCase						(				self   :	List[str]			):
									UpperCAmelCase__             =							'\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            '.split()
									self.run_and_check(lowerCamelCase__			)

									UpperCAmelCase__             =							'\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --eval_each_highway\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
									self.run_and_check(lowerCamelCase__			)

									UpperCAmelCase__             =							'\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --early_exit_entropy 0.1\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
									self.run_and_check(lowerCamelCase__			)



