diff options
Diffstat (limited to 'cnn_v3/training/export_cnn_v3_weights.py')
| -rw-r--r-- | cnn_v3/training/export_cnn_v3_weights.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/cnn_v3/training/export_cnn_v3_weights.py b/cnn_v3/training/export_cnn_v3_weights.py index edf76e2..78f5f25 100644 --- a/cnn_v3/training/export_cnn_v3_weights.py +++ b/cnn_v3/training/export_cnn_v3_weights.py @@ -15,8 +15,8 @@ Outputs <output_dir>/cnn_v3_weights.bin Conv+bias weights for all 5 passes, packed as f16-pairs-in-u32. Matches the format expected by CNNv3Effect::upload_weights(). - Layout: enc0 (724) | enc1 (296) | bottleneck (72) | dec1 (580) | dec0 (292) - = 1964 f16 values = 982 u32 = 3928 bytes. + Layout: enc0 (724) | enc1 (296) | bottleneck (584) | dec1 (580) | dec0 (292) + = 2476 f16 values = 1238 u32 = 4952 bytes. <output_dir>/cnn_v3_film_mlp.bin FiLM MLP weights as raw f32: L0_W (5×16) L0_b (16) L1_W (16×40) L1_b (40). @@ -48,13 +48,13 @@ from train_cnn_v3 import CNNv3 # cnn_v3/src/cnn_v3_effect.cc (kEnc0Weights, kEnc1Weights, …) # cnn_v3/training/gen_test_vectors.py (same constants) # --------------------------------------------------------------------------- -ENC0_WEIGHTS = 20 * 4 * 9 + 4 # Conv(20→4,3×3)+bias = 724 -ENC1_WEIGHTS = 4 * 8 * 9 + 8 # Conv(4→8,3×3)+bias = 296 -BN_WEIGHTS = 8 * 8 * 1 + 8 # Conv(8→8,1×1)+bias = 72 -DEC1_WEIGHTS = 16 * 4 * 9 + 4 # Conv(16→4,3×3)+bias = 580 -DEC0_WEIGHTS = 8 * 4 * 9 + 4 # Conv(8→4,3×3)+bias = 292 +ENC0_WEIGHTS = 20 * 4 * 9 + 4 # Conv(20→4,3×3)+bias = 724 +ENC1_WEIGHTS = 4 * 8 * 9 + 8 # Conv(4→8,3×3)+bias = 296 +BN_WEIGHTS = 8 * 8 * 9 + 8 # Conv(8→8,3×3,dil=2)+bias = 584 +DEC1_WEIGHTS = 16 * 4 * 9 + 4 # Conv(16→4,3×3)+bias = 580 +DEC0_WEIGHTS = 8 * 4 * 9 + 4 # Conv(8→4,3×3)+bias = 292 TOTAL_F16 = ENC0_WEIGHTS + ENC1_WEIGHTS + BN_WEIGHTS + DEC1_WEIGHTS + DEC0_WEIGHTS -# = 1964 +# = 2476 def pack_weights_u32(w_f16: np.ndarray) -> np.ndarray: |