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torch.rand_like
- 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 inputthat is filled with random numbers from a uniform distribution on the interval .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 inputwill determine size of the output tensor.
- Keyword Arguments
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      - dtype (torch.dtype, optional) – the desired data type of returned Tensor. Default: ifNone, defaults to the dtype ofinput.
- layout (torch.layout, optional) – the desired layout of returned tensor. Default: ifNone, defaults to the layout ofinput.
- device (torch.device, optional) – the desired device of returned tensor. Default: ifNone, defaults to the device ofinput.
- 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.
 
- dtype (
 
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 https://pytorch.org/docs/2.1/generated/torch.rand_like.html