oneflow.randn_like(input, *, dtype=None, generator=None, device=None, placement=None, sbp=None, requires_grad=False)Tensor

Returns a tensor with the same size as input that is filled with random numbers from a normal distribution with mean 0 and variance 1. flow.randn_like(input) is equivalent to flow.randn(input.size(), dtype=input.dtype, device=input.device).

  • input (oneflow.Tensor) – the size of input will determine size of the output tensor.

  • dtype (flow.dtype, optional) – The desired data type of returned tensor. defaults to the dtype of input.

  • generator (flow.Generator, optional) – a pseudorandom number generator for sampling

  • device (flow.device, optional) – The desired device of returned local tensor. If None, defaults to the device of input.

  • placement (flow.placement, optional) – The desired device of returned global tensor. If None, will construct local tensor.

  • sbp (flow.sbp, optional) – The desired sbp of returned global tensor. It must be equal with the numbers of placement, If None, will construct local tensor.

  • requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default: False.

For example:

>>> import oneflow as flow
>>> x = flow.randn(3,3) # construct local tensor
>>> y = flow.randn_like(x)
>>> y.shape
oneflow.Size([3, 3])
>>> y.is_global
>>> placement = flow.placement("cpu", ranks=[0])
>>> sbp = flow.sbp.broadcast
>>> z = flow.randn_like(y, placement=placement, sbp=sbp) # construct global tensor
>>> z.is_global