torch.rand_like — PyTorch 2.7 documentation (original) (raw)

torch.rand_like(input, *, dtype=None, layout=None, device=None, requires_grad=False, memory_format=torch.preserve_format) → Tensor¶

Returns a tensor with the same size as input that is filled with random numbers from a uniform distribution on the interval [0,1)[0, 1).torch.rand_like(input) is equivalent totorch.rand(input.size(), dtype=input.dtype, layout=input.layout, device=input.device).

Parameters

input (Tensor) – the size of input will determine size of the output tensor.

Keyword Arguments

• dtype (torch.dtype, optional) – the desired data type of returned Tensor. Default: if None, defaults to the dtype of input.
• layout (torch.layout, optional) – the desired layout of returned tensor. Default: if None, defaults to the layout of input.
• device (torch.device, optional) – the desired device of returned tensor. Default: if None, defaults to the device of input.
• requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default: False.
• memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format.