The error message might be a bit weird, but it refers to an input of shape [batch_size, channels, *addidional_dims].
Given that you provide a “1D” input with a length of 4.
Here would be an example using an image tensor:
batch_size, c, h, w = 1, 3, 4, 4
x  = torch.randn(batch_size, c, h, w)
x = F.interpolate(x, scale_factor=(2,1))
print(x.shape)
> torch.Size([1, 3, 8, 4])

As you can see, the batch size as well as the channels won’t be manipulated, just the spatial dimensions.