clarify source and fix verbose

Signed-off-by: mihara-bot <1147220090@qq.com>

Author: mihara-bot

emerging_optimizers/orthogonalized_optimizers/muon_utils.py

@@ -56,8 +56,9 @@
         (1.8750, -1.2500, 0.3750),
     ],
     "cans": [
+        # CANS from: http://arxiv.org/abs/2506.10935
         # CANS iteration (Remez + adaptive interval) based coefficients.
-        # Source (generation): accelerating_orthogonalization/polynomials.py
+        # Source (for generating CANS coefficients): https://github.com/GrishKate/accelerating_orthogonalization/blob/main/polynomials.py
         (8.4703, -25.1081, 18.6293),
         (4.1828, -3.1087, 0.5806),
         (3.9619, -2.9541, 0.5630),

tests/test_muon_utils.py

@@ -247,10 +247,7 @@ def test_get_cans_9steps_close_to_reference(self, dim1, dim2):
         out_cans9 = muon_utils.newton_schulz(x, steps=9, coefficient_type="cans")
         coeff = deepcopy(muon_utils._COEFFICIENT_SETS["cans"])
         # CANS uses repeat_last, so repeat the last tuple for remaining steps.
-        coeff.append(coeff[-1])
-        coeff.append(coeff[-1])
-        coeff.append(coeff[-1])
-        coeff.append(coeff[-1])
+        coeff.extend([coeff[-1]] * 4)
         out_ref = newton_schulz_ref(x, coefficient_sets=coeff)
         torch.testing.assert_close(out_cans9, out_ref, atol=2e-6, rtol=1e-7)