torch.from_numpy
torch.from_numpy(ndarray) -> Tensor
Creates a "Tensor" from a "numpy.ndarray".
The returned tensor and "ndarray" share the same memory.
   Modifications to the tensor will be reflected in the "ndarray" and
   vice versa. The returned tensor is not resizable.
It currently accepts "ndarray" with dtypes of "numpy.float64",
   "numpy.float32", "numpy.float16", "numpy.complex64",
   "numpy.complex128", "numpy.int64", "numpy.int32", "numpy.int16",
   "numpy.int8", "numpy.uint8", and "numpy.bool".
Warning:
 Writing to a tensor created from a read-only NumPy array is not
 supported and will result in undefined behavior.

Example:
  >>> a = numpy.array([1, 2, 3])
  >>> t = torch.from_numpy(a)
  >>> t
  tensor([ 1,  2,  3])
  >>> t[0] = -1
  >>> a
  array([-1,  2,  3])
