if you are still wondering, it’s been implemented but it should be done properly.

>>> a = torch.rand(64, 20)
>>> b = torch.rand(64, 1)
>>> a/b
tensor([[ 5.0057e-01,  3.5622e-01,  3.1053e-01,  ...,  3.2856e-01,
          1.0888e+00,  9.7678e-01],
        [ 4.7883e+00,  5.7695e+00,  2.8125e+00,  ...,  1.6500e+01,
          3.5257e+00,  1.5637e+01],
        [ 6.8112e-01,  1.8881e+00,  2.0702e+00,  ...,  4.2512e-01,
          1.4803e+00,  8.5795e-01],
        ...,
        [ 4.1682e-01,  9.6458e-01,  1.1828e+00,  ...,  9.9901e-01,
          1.0716e+00,  1.4875e+00],
        [ 1.2503e-01,  1.2347e+00,  6.0802e-01,  ...,  5.0439e-01,
          1.2536e+00,  1.3501e+00],
        [ 9.1765e-01,  6.7741e-01,  1.0928e+00,  ...,  8.1460e-01,
          9.7924e-01,  3.8059e-01]])
>>> torch.div(a,b)
tensor([[ 5.0057e-01,  3.5622e-01,  3.1053e-01,  ...,  3.2856e-01,
          1.0888e+00,  9.7678e-01],
        [ 4.7883e+00,  5.7695e+00,  2.8125e+00,  ...,  1.6500e+01,
          3.5257e+00,  1.5637e+01],
        [ 6.8112e-01,  1.8881e+00,  2.0702e+00,  ...,  4.2512e-01,
          1.4803e+00,  8.5795e-01],
        ...,
        [ 4.1682e-01,  9.6458e-01,  1.1828e+00,  ...,  9.9901e-01,
          1.0716e+00,  1.4875e+00],
        [ 1.2503e-01,  1.2347e+00,  6.0802e-01,  ...,  5.0439e-01,
          1.2536e+00,  1.3501e+00],
        [ 9.1765e-01,  6.7741e-01,  1.0928e+00,  ...,  8.1460e-01,
          9.7924e-01,  3.8059e-01]])


note: b should be of shape (64,1) not (64,) that’s what RuntimeError: The size of tensor a (20) must match the size of tensor b (64) at non-singleton dimension 1 means.