I recently wanted to do the same thing. In case anyone is interested, the following is my solution:
import torch


n_batch = 8
n_feat = 11

rand = torch.rand(n_batch, n_feat)
batch_rand_perm = rand.argsort(dim=1)
print(batch_rand_perm)

tensor([[ 1,  2,  4,  6,  0,  9,  3,  7,  8,  5, 10],
        [10,  6,  9,  2,  7,  4,  3,  5,  1,  0,  8],
        [ 8,  7,  4,  6,  0,  1,  9, 10,  2,  5,  3],
        [ 1,  3,  5,  4,  6,  8,  2,  9,  0,  7, 10],
        [ 3, 10,  7,  1,  4,  5,  0,  8,  9,  6,  2],
        [ 2, 10,  0,  1,  6,  8,  7,  9,  5,  3,  4],
        [ 5,  9,  8, 10,  0,  1,  6,  7,  4,  2,  3],
        [ 0,  9,  8,  4,  1,  3,  2,  7,  5, 10,  6]])