Solved by SreenivasVRao in post #2 
              
              
                Looks like it is. 
import torch, torch.nn.functional as F
x = torch.rand([5, 6, 3, 30, 50]) # B C T H W
z = F.upsample(x, size=(3, 60, 100), mode='trilinear') # 5 6 3 60 100

z2 =  []
for t in range(3):
   x_t  = x[:, :, t, :, :]
   z2.append(F.upsample(x_t, size=(60, 100), mode='bilinear')) # 5 6 6…