






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

import requests



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	str = "isbn/0140328726"    )  ->			dict:

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



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	dict    )  ->			dict:

   """simple docstring"""
   __a				     =    {
       '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)',
   }
   __a				     =    {better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
   __a				     =    [
       get_openlibrary_data(author['key']    )['name'] for author in data['Authors']
   ]
   __a				     =    data['First sentence']['value']
   for key, value in data.items():
      if isinstance(_A,					_A    ):
         __a				     =    ', '.join(_A    )
   return data


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 while True:
  __UpperCamelCase      :       Optional[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:
   __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}.""")







'''simple docstring'''



from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
 import torch

if is_torch_tpu_available(check_device=False):
 import torch_xla.core.xla_model as xm


__UpperCamelCase      :       Optional[Any]      			=      logging.get_logger(__name__)
@dataclass
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):
      __a  					=[
          "no_inference",
          "no_cuda",
          "no_tpu",
          "no_speed",
          "no_memory",
          "no_env_print",
          "no_multi_process",
      ]




      def __init__(  self ,   **lowerCamelCase      )							->List[Any]:



         '''simple docstring'''
         for deprecated_arg in self.deprecated_args:
            if deprecated_arg in kwargs:
               __a				     =    deprecated_arg[3:]
               setattr(self ,   lowerCamelCase ,   not kwargs.pop(lowerCamelCase      )      )
               logger.warning(
                   F"""{deprecated_arg} is depreciated. Please use --no_{positive_arg} or"""
                   F""" {positive_arg}={kwargs[positive_arg]}"""      )

         __a				     =    kwargs.pop('torchscript' ,   self.torchscript      )
         __a				     =    kwargs.pop('torch_xla_tpu_print_metrics' ,   self.torch_xla_tpu_print_metrics      )
         __a				     =    kwargs.pop('fp16_opt_level' ,   self.fpaa_opt_level      )
         super().__init__(**lowerCamelCase      )

      __a  					=field(default=_lowerCAmelCase      ,      metadata={"help": "Trace the models using torchscript"}     )
      __a  					=field(default=_lowerCAmelCase      ,      metadata={"help": "Print Xla/PyTorch tpu metrics"}     )
      __a  					=field(
          default="O1"      ,      metadata={
              "help": (
                  "For fp16: Apex AMP optimization level selected in ['O0', 'O1', 'O2', and 'O3']. "
                  "See details at https://nvidia.github.io/apex/amp.html"
              )
          }      ,      )




      @cached_property
      def  __UpperCamelCase							(  self      )							->Tuple["torch.device", int]:



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         logger.info('PyTorch: setting up devices'      )
         if not self.cuda:
            __a				     =    torch.device('cpu'      )
            __a				     =    0
         elif is_torch_tpu_available():
            __a				     =    xm.xla_device()
            __a				     =    0
         else:
            __a				     =    torch.device('cuda' if torch.cuda.is_available() else 'cpu'      )
            __a				     =    torch.cuda.device_count()
         return device, n_gpu




      @property
      def  __UpperCamelCase							(  self      )							->Optional[Any]:



         '''simple docstring'''
         return is_torch_tpu_available() and self.tpu




      @property
      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         # TODO(PVP): currently only single GPU is supported
         return torch.cuda.current_device()




      @property
      def  __UpperCamelCase							(  self      )							->"torch.device":



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         return self._setup_devices[0]




      @property
      def  __UpperCamelCase							(  self      )							->List[Any]:



         '''simple docstring'''
         requires_backends(self ,   ['torch']      )
         return self._setup_devices[1]






      @property
      def  __UpperCamelCase							(  self      )							->List[str]:



         '''simple docstring'''
         return self.n_gpu > 0