I cannot reproduce the issue using:
torch.FloatTensor(torch.randn(10))

but in any case you shouldn’t use torch.FloatTensor as its usage is deprecated and undocumented due to its unintuitive behavior.
E.g. passing a scalar to it will return a FloatTensor with scalar elements using uninitialized memory, while passing a list would return a FloatTensor which contains the passed values:
torch.FloatTensor(10)
> tensor([-1.3895e+28,  3.0778e-41, -1.3954e+28,  3.0778e-41,  4.9870e-17,
           4.5729e-41, -6.7316e+36,  3.0778e-41,  1.4013e-45,  0.0000e+00])
torch.FloatTensor([10])
> tensor([10.])

Use the factory methods (torch.randn, torch.empty etc.) or transform the dtypes via to() or the direct call e.g. tensor.float().