






import importlib.metadata
import subprocess
import sys






def     lowerCamelCase__				(   __lowerCamelCase      :					bool = False		):
  __UpperCAmelCase							:     List[str]									=  False
  if "IPython" in sys.modules:
    __UpperCAmelCase							:     Optional[Any]									=  '''google.colab''' in str(sys.modules["""IPython"""].get_ipython()		)

  if in_colab:
    if upgrade:
      __UpperCAmelCase							:     List[Any]									=  ['''pip''', '''install''', '''-U''', '''torch''']
      subprocess.run(_lowerCAmelCase  ,		check=_lowerCAmelCase		)
    # get the current version of torch
    __UpperCAmelCase							:     Dict									=  importlib.metadata.version("""torch"""		)
    __UpperCAmelCase							:     int									=  torch_version[: torch_version.rindex("""."""		)]
    __UpperCAmelCase							:     Any									=  f"""https://storage.googleapis.com/tpu-pytorch/wheels/colab/torch_xla-{torch_version_trunc}-cp37-cp37m-linux_x86_64.whl"""
    __UpperCAmelCase							:     List[str]									=  ['''pip''', '''install''', xla_wheel]
    subprocess.run(_lowerCAmelCase  ,		check=_lowerCAmelCase		)
  else:
    raise RuntimeError("""`install_xla` utility works only on google colab."""		)










from sklearn.neural_network import MLPClassifier

a		:	int      					=			[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
a		:	List[str]      					=			[0, 1, 0, 0]


a		:	str      					=			MLPClassifier(
    solver="lbfgs", alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


a		:	Union[str, Any]      					=			[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
a		:	Optional[int]      					=			clf.predict(test)






def     lowerCamelCase__				(   __lowerCamelCase      :					Dict		):
  return list(__lowerCamelCase		)


if __name__ == "__main__":
       import doctest

       doctest.testmod()


