I think if you pass a 4-D tensor it will be interpolated spatially by default (so channel and batch dimensions are not affected):
import torch
x = torch.randn(16, 16, 32, 32)
y = torch.nn.functional.interpolate(x, size=(64, 64))
y2 = torch.empty(16, 16, 64, 64)
for n in range(16):
    for c in range(16):
        inp = x[n,c,:,:].reshape(1, 1, 32, 32)
        y2[n,c,:,:] = torch.nn.functional.interpolate(inp, size=(64, 64))
print(torch.all(y == y2))

tensor(True)