


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
   SCREAMING_SNAKE_CASE       :		Optional[int]         =				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")
   SCREAMING_SNAKE_CASE     ,		SCREAMING_SNAKE_CASE       :		List[str]         =				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")
      SCREAMING_SNAKE_CASE       :		List[Any]         =				rh.cluster(
          name="rh-cluster", ips=[args.host], ssh_creds={"ssh_user": args.user, "ssh_private_key": args.key_path}
      )
   else:
      SCREAMING_SNAKE_CASE       :		Dict         =				rh.cluster(
          name="rh-cluster", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
      )
   SCREAMING_SNAKE_CASE       :		Tuple         =				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)





def     UpperCamelCase    (      _a       ,		_a       ,		_a		)					->							int:
     '''simple docstring'''





     def count_of_possible_combinations(_a		) -> int:
          if target < 0:
               return 0
          if target == 0:
               return 1
          return sum(count_of_possible_combinations(target - item		) for item in array		)

     return count_of_possible_combinations(_a		)




def     UpperCamelCase    (      _a       ,		_a       ,		_a		)					->							int:
     '''simple docstring'''





     def count_of_possible_combinations_with_dp_array(
         _a       ,		_a		) -> int:
          if target < 0:
               return 0
          if target == 0:
               return 1
          if dp_array[target] != -1:
               return dp_array[target]
          lowercase_       :Optional[int]     =       sum(
              count_of_possible_combinations_with_dp_array(target - item       ,		_a		)
              for item in array		)
          lowercase_       :List[Any]     =       answer
          return answer

     lowercase_       :Dict     =       [-1] * (target + 1)
     return count_of_possible_combinations_with_dp_array(_a       ,		_a		)




def     UpperCamelCase    (      _a       ,		_a       ,		_a		)					->							int:
     '''simple docstring'''





     lowercase_       :Optional[int]     =       [0] * (target + 1)
     lowercase_       :int     =       1

     for i in range(1       ,		target + 1		):
          for j in range(_a		):
               if i - array[j] >= 0:
                    dp_array[i] += dp_array[i - array[j]]

     return dp_array[target]


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   SCREAMING_SNAKE_CASE       :		Optional[Any]         =				3
   SCREAMING_SNAKE_CASE       :		Tuple         =				5
   SCREAMING_SNAKE_CASE       :		List[Any]         =				[1, 2, 5]
   print(combination_sum_iv(n, array, target))

