remove comments

python/mlx/optimizers/optimizers.py

@@ -902,11 +902,9 @@ class Muon(Optimizer):
         if transpose_needed:
             X = X.T
 
-        # Ensure spectral norm is at most 1
         norm = mx.sqrt(mx.sum(X * X, axis=(-2, -1), keepdims=True) + 1e-7)
         X = X / norm
 
-        # Perform the NS iterations
         for _ in range(steps):
             A = X @ X.T
             B = mx.addmm(b * A, A, A, beta=1.0, alpha=c)
@@ -931,12 +929,10 @@ class Muon(Optimizer):
         else:
             effective_grad = v
 
-        # For tensors with fewer than 2 dimensions, skip Newton-Schulz
         if effective_grad.ndim < 2:
             orthogonalized_grad = effective_grad
             scale_factor = 1.0
         else:
-            # Save original shape for 4D conv filters
             original_shape = effective_grad.shape
             reshape_needed = effective_grad.ndim > 2