Randint_like
torch_randint_like(
input,
low,
high,
dtype = NULL,
layout = torch_strided(),
device = NULL,
requires_grad = FALSE
)
(Tensor) the size of input
will determine size of the output tensor.
(int, optional) Lowest integer to be drawn from the distribution. Default: 0.
(int) One above the highest integer to be drawn from the distribution.
(torch.dtype
, optional) the desired data type of returned Tensor. Default: if NULL
, defaults to the dtype of input
.
(torch.layout
, optional) the desired layout of returned tensor. Default: if NULL
, defaults to the layout of input
.
(torch.device
, optional) the desired device of returned tensor. Default: if NULL
, defaults to the device of input
.
(bool, optional) If autograd should record operations on the returned tensor. Default: FALSE
.
memory_format=torch.preserve_format) -> Tensor
Returns a tensor with the same shape as Tensor input
filled with
random integers generated uniformly between low
(inclusive) and
high
(exclusive).
.. note:
With the global dtype default (torch_float32
), this function returns
a tensor with dtype torch_int64
.