[README] - document entity.py L1/L2 and image.py normalize fixes

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/tests/README.md

@@ -86,6 +86,18 @@ Same two bugs as `cd_gaussian_binary`: noise was added to `data_neg` before comp
 - `label2vec_onehot` returned a Python list instead of a stacked array — now uses `np.stack()`.
 - `vec2label_onehot` was unimplemented (returned `None`) — now uses `np.argmax()`.
 
+#### `entity.py` — L1 and L2 regularisation gradients wrong
+
+`grad_compute` computed scalar norms and multiplied by `W`, giving gradients that scaled with the total weight magnitude rather than the correct per-element derivatives:
+- **L1**: gradient should be `λ·sign(W)`, not `λ·‖W‖₁·W`
+- **L2**: gradient should be `2λ·W`, not `λ·‖W‖₂²·W`
+
+The combined `(l1+l2)·W` term also incorrectly mixed both penalties into one. Fixed to apply each gradient independently. `weight_decay` (the correct `λW` form of L2) is kept as a separate term.
+
+#### `image.py` — `normalize()` fragile and verbose
+
+The `repeat`/`reshape` approach was replaced with `keepdims=True` broadcasting and a `std < 1e-8` guard to prevent NaN on constant patches. The duplicate normalization logic in `test_faces_sub_image.py:load_image_patches` was removed in favour of calling `normalize()` directly.
+
 ---
 
 ## RBM type reference