F.intepolate would need to use mode='bilinear' for 4D inputs and could only interpolate the spatial dimensions.
To interpolate in the channel dimension, you could permute the input and output as shown here:
B = 2
x =  torch.randn([B, 64, 256, 384])
x = x.permute(0, 2, 1, 3)
out = F.interpolate(x, [256, 384], mode='bilinear')
out = out.permute(0, 2, 1, 3)