torch / torch
torch.randint¶
-
torch.
randint
(low=0, high, size, *, generator=None, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor¶ Returns a tensor filled with random integers generated uniformly between
low
(inclusive) andhigh
(exclusive).The shape of the tensor is defined by the variable argument
size
.- Parameters
- Keyword Arguments
generator (
torch.Generator
, optional) – a pseudorandom number generator for samplingout (Tensor, optional) – the output tensor.
dtype (
torch.dtype
, optional) – the desired data type of returned tensor. Default: ifNone
, uses a global default (seetorch.set_default_tensor_type()
).layout (
torch.layout
, optional) – the desired layout of returned Tensor. Default:torch.strided
.device (
torch.device
, optional) – the desired device of returned tensor. Default: ifNone
, uses the current device for the default tensor type (seetorch.set_default_tensor_type()
).device
will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default:
False
.
Example:
>>> torch.randint(3, 5, (3,)) tensor([4, 3, 4]) >>> torch.randint(10, (2, 2)) tensor([[0, 2], [5, 5]]) >>> torch.randint(3, 10, (2, 2)) tensor([[4, 5], [6, 7]])
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