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
inputwill 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.
>>> 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 False >>> placement = flow.placement("cpu", ranks=) >>> sbp = flow.sbp.broadcast >>> z = flow.randn_like(y, placement=placement, sbp=sbp) # construct global tensor >>> z.is_global True