Tensor.type(dtype=None, non_blocking=False, **kwargs)str or Tensor

Returns the type if dtype is not provided, else casts this object to the specified type.

If this is already of the correct type, no copy is performed and the original object is returned.

  • dtype (oneflow.dtype or oneflow.tensortype or string, optional) – The desired type.

  • non_blocking (bool) – (Not Implemented yet) If True, and the source is in pinned memory and destination is on the GPU or vice versa, the copy is performed asynchronously with respect to the host. Otherwise, the argument has no effect.

For example:

>>> import oneflow as flow
>>> a = flow.tensor([1, 2], dtype=flow.float32)
>>> a.type()
>>> a.type(flow.int8)  # dtype input
tensor([1, 2], dtype=oneflow.int8)
>>> a.type(flow.cuda.DoubleTensor)  # tensortype input
tensor([1., 2.], device='cuda:0', dtype=oneflow.float64)
>>> a.type("oneflow.HalfTensor")  # string input
tensor([1., 2.], dtype=oneflow.float16)