oneflow.linspace

oneflow.linspace(start: float, end: float, steps: int, dtype: oneflow._oneflow_internal.dtype = oneflow.float32, device: Optional[Union[str, oneflow._oneflow_internal.device]] = None, placement: Optional[oneflow._oneflow_internal.placement] = None, sbp: Optional[Union[oneflow._oneflow_internal.sbp.sbp, List[oneflow._oneflow_internal.sbp.sbp]]] = None, requires_grad: bool = False)

Creates a one-dimensional tensor of size steps whose values are evenly spaced from start to end, inclusive. That is, the value are:

\[(\text{start}, \text{start} + \frac{\text{end} - \text{start}}{\text{steps} - 1}, \ldots, \text{start} + (\text{steps} - 2) * \frac{\text{end} - \text{start}}{\text{steps} - 1}, \text{end})\]
Parameters

  • start (float) – the starting value for the set of points

  • end (float) – the ending value for the set of points

  • steps (int) – size of the constructed tensor

Keyword Arguments

  • dtype (flow.dtype, optional) – If dtype is not given, the dtype is inferred to be flow.float32.

  • device (flow.device, optional) – the desired device of returned tensor. Default: if None, uses the current device for the default tensor.

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

For example:

>>> import oneflow as flow

>>> y = flow.linspace(3, 10, steps=5)
>>> y
tensor([ 3.0000,  4.7500,  6.5000,  8.2500, 10.0000], dtype=oneflow.float32)