oneflow.arange¶
-
oneflow.
arange
(start: int = 0, end, step: int = 1, dtype: Optional[oneflow._oneflow_internal.dtype] = None, device: Optional[Union[oneflow._oneflow_internal.device, str]] = 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)¶ Returns a 1-D tensor of size \(\left\lfloor \frac{\text{end} - \text{start}}{\text{step}} \right\rfloor + 1\) with values from
start
toend
with stepstep
. Step is the gap between two values in the tensor.\[\text{out}_{i+1} = \text{out}_i + \text{step}.\]- Parameters
start (int) – the starting value for the set of points. Default:
0
.end (int) – the ending value for the set of points
step (int) – the gap between each pair of adjacent points. Default:
1
.
- Keyword Arguments
dtype (flow.dtype, optional) – If dtype is not given, infer the dtype from the other input arguments. If any of start, end, or step are floating-point, the dtype is inferred to be the floating-point data type. Otherwise, the dtype is inferred to be flow.int64.
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.arange(0, 5) >>> y tensor([0, 1, 2, 3, 4], dtype=oneflow.int64)