'''simple docstring'''


import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
 # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
 # setup instructions, if using on-demand hardware

 # If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
 # If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
 # Throw an error if user passes both BYO and on-demand cluster args
 # Otherwise, use default values
 snake_case__					:      List[Any]				      =  argparse.ArgumentParser()
 parser.add_argument('''--user''', type=str, default='''ubuntu''')
 parser.add_argument('''--host''', type=str, default='''localhost''')
 parser.add_argument('''--key_path''', type=str, default=None)
 parser.add_argument('''--instance''', type=str, default='''V100:1''')
 parser.add_argument('''--provider''', type=str, default='''cheapest''')
 parser.add_argument('''--use_spot''', type=bool, default=False)
 parser.add_argument('''--example''', type=str, default='''pytorch/text-generation/run_generation.py''')
 snake_case__					:      Optional[Any]				      =  parser.parse_known_args()
 if args.host != "localhost":
  if args.instance != "V100:1" or args.provider != "cheapest":
   raise ValueError('''Cannot specify both BYO and on-demand cluster args''')
  snake_case__					:      Optional[int]				      =  rh.cluster(
      name='''rh-cluster''', ips=[args.host], ssh_creds={'''ssh_user''': args.user, '''ssh_private_key''': args.key_path}
  )
 else:
  snake_case__					:      List[Any]				      =  rh.cluster(
      name='''rh-cluster''', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
  )
 snake_case__					:      str				      =  args.example.rsplit('''/''', 1)[0]

 # Set up remote environment
 cluster.install_packages(['''pip:./'''])  # Installs transformers from local source
 # Note transformers is copied into the home directory on the remote machine, so we can install from there
 cluster.run([f'''pip install -r transformers/examples/{example_dir}/requirements.txt'''])
 cluster.run(['''pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117'''])

 # Run example. You can bypass the CLI wrapper and paste your own code here.
 cluster.run([f'''python transformers/examples/{args.example} {" ".join(shlex.quote(arg) for arg in unknown)}'''])

 # Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
 # from my_script... import train
 # reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
 # launch_train_gpu = rh.function(fn=train,
 #                                system=gpu,
 #                                reqs=reqs,
 #                                name='train_bert_glue')
 #
 # We can pass in arguments just like we would to a function:
 # launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
 #                  stream_logs=True)



'''simple docstring'''


snake_case__					:      Optional[Any]				      =  tuple[float, float, float]
snake_case__					:      Tuple				      =  tuple[float, float, float]


def  _lowerCamelCase   (				lowerCamelCase_ :							Pointad     ,					lowerCamelCase_ :							Pointad       ):



     """simple docstring"""





     UpperCAmelCase_							:       Any       =				end_pointa[0] - end_pointa[0]
     UpperCAmelCase_							:       Optional[Any]       =				end_pointa[1] - end_pointa[1]
     UpperCAmelCase_							:       Any       =				end_pointa[2] - end_pointa[2]
     return (x, y, z)


def  _lowerCamelCase   (				lowerCamelCase_ :							Vectorad     ,					lowerCamelCase_ :							Vectorad       ):



     """simple docstring"""





     UpperCAmelCase_							:       Optional[Any]       =				ab[1] * ac[2] - ab[2] * ac[1]  # *i
     UpperCAmelCase_							:       Optional[Any]       =				(ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
     UpperCAmelCase_							:       Dict       =				ab[0] * ac[1] - ab[1] * ac[0]  # *k
     return (x, y, z)


def  _lowerCamelCase   (				lowerCamelCase_ :							Vectorad     ,					lowerCamelCase_ :							int       ):



     """simple docstring"""





     return tuple(round(lowerCamelCase_     ,					lowerCamelCase_       ) for x in vector       ) == (0, 0, 0)





def  _lowerCamelCase   (				lowerCamelCase_ :							Pointad     ,					lowerCamelCase_ :							Pointad     ,					lowerCamelCase_ :							Pointad     ,					lowerCamelCase_ :							int = 10       ):



     """simple docstring"""





     UpperCAmelCase_							:       List[str]       =				create_vector(lowerCamelCase_     ,					lowerCamelCase_       )
     UpperCAmelCase_							:       List[Any]       =				create_vector(lowerCamelCase_     ,					lowerCamelCase_       )
     return is_zero_vector(get_ad_vectors_cross(lowerCamelCase_     ,					lowerCamelCase_       )     ,					lowerCamelCase_       )






