
'''simple docstring'''


from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap



def  __snake_case     (    _UpperCAmelCase					:       int):
   return getitem, k



def  __snake_case     (    _UpperCAmelCase					:       str,      _UpperCAmelCase					:       Optional[int]):
   return setitem, k, v



def  __snake_case     (    _UpperCAmelCase					:       Union[str, Any]):
   return delitem, k



def  __snake_case     (    _UpperCAmelCase					:       int,      _UpperCAmelCase					:       Dict,      *_UpperCAmelCase					:       Optional[int]):
   try:
      return fun(_UpperCAmelCase,      *_UpperCAmelCase), None
   except Exception as e:
      return None, e


snake_case_ :  Dict     =					(
    _set('key_a', 'val_a'),
    _set('key_b', 'val_b'),
)

snake_case_ :  Dict     =					[
    _set('key_a', 'val_a'),
    _set('key_a', 'val_b'),
]

snake_case_ :  List[str]     =					[
    _set('key_a', 'val_a'),
    _set('key_b', 'val_b'),
    _del('key_a'),
    _del('key_b'),
    _set('key_a', 'val_a'),
    _del('key_a'),
]

snake_case_ :  str     =					[
    _get('key_a'),
    _del('key_a'),
    _set('key_a', 'val_a'),
    _del('key_a'),
    _del('key_a'),
    _get('key_a'),
]

snake_case_ :  Dict     =					[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

snake_case_ :  int     =					[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set('key_a', 'val_b'),
]



@pytest.mark.parametrize(
    '''operations''',      (
        pytest.param(_add_items,      id='''add items'''),
        pytest.param(_overwrite_items,      id='''overwrite items'''),
        pytest.param(_delete_items,      id='''delete items'''),
        pytest.param(_access_absent_items,      id='''access absent items'''),
        pytest.param(_add_with_resize_up,      id='''add with resize up'''),
        pytest.param(_add_with_resize_down,      id='''add with resize down'''),
    ),      )
def  __snake_case     (    _UpperCAmelCase					:       Union[str, Any]):
   UpperCamelCase       =  HashMap(initial_block_size=4)
   UpperCamelCase       =  {}
   for _, (fun, *args) in enumerate(_UpperCAmelCase):
      UpperCamelCase     , UpperCamelCase       =  _run_operation(_UpperCAmelCase,      _UpperCAmelCase,      *_UpperCAmelCase)
      UpperCamelCase     , UpperCamelCase       =  _run_operation(_UpperCAmelCase,      _UpperCAmelCase,      *_UpperCAmelCase)
      assert my_res == py_res
      assert str(_UpperCAmelCase) == str(_UpperCAmelCase)
      assert set(_UpperCAmelCase) == set(_UpperCAmelCase)
      assert len(_UpperCAmelCase) == len(_UpperCAmelCase)
      assert set(my.items()) == set(py.items())



def  __snake_case     (    ):
   def is_public(_UpperCAmelCase					:       str) -> bool:
      return not name.startswith('''_''')

   UpperCamelCase       =  {name for name in dir({}) if is_public(_UpperCAmelCase)}
   UpperCamelCase       =  {name for name in dir(HashMap()) if is_public(_UpperCAmelCase)}

   assert dict_public_names > hash_public_names







'''simple docstring'''


import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp



def  __snake_case     (    ):
   UpperCamelCase       =  ArgumentParser(
       description=(
           '''PyTorch TPU distributed training launch '''
           '''helper utility that will spawn up '''
           '''multiple distributed processes'''
       ))

   # Optional arguments for the launch helper
   parser.add_argument('''--num_cores''',      type=_UpperCAmelCase,      default=1,      help='''Number of TPU cores to use (1 or 8).''')

   # positional
   parser.add_argument(
       '''training_script''',      type=_UpperCAmelCase,      help=(
           '''The full path to the single TPU training '''
           '''program/script to be launched in parallel, '''
           '''followed by all the arguments for the '''
           '''training script'''
       ),      )

   # rest from the training program
   parser.add_argument('''training_script_args''',      nargs=_UpperCAmelCase)

   return parser.parse_args()



def  __snake_case     (    ):
   UpperCamelCase       =  parse_args()

   # Import training_script as a module.
   UpperCamelCase       =  Path(args.training_script)
   sys.path.append(str(script_fpath.parent.resolve()))
   UpperCamelCase       =  script_fpath.stem
   UpperCamelCase       =  importlib.import_module(_UpperCAmelCase)

   # Patch sys.argv
   UpperCamelCase       =  [args.training_script] + args.training_script_args + ['''--tpu_num_cores''', str(args.num_cores)]
   xmp.spawn(mod._mp_fn,      args=(),      nprocs=args.num_cores)


if __name__ == "__main__":
   main()





