In the absence of 1D specific methods you could always use the 2D and unsqueeze + squeeze.
a = torch.randn(batch_size, num_chan, 10)
a = a.unsqueeze(dim=3)
a_up = F.upsample(Variable(a), size=(20, 1), mode='bilinear').squeeze(dim=3)