fix(cnn_v3/training): fix defaults and help strings across py tools

- train_cnn_v3.py: enc-channels 4,8→8,16; checkpoint-every 50→100;
  add help strings for epochs/batch-size/lr/checkpoint-dir
- gen_test_vectors.py: add help strings for --W/--H/--seed
- export_cnn_v3_weights.py: fix --output help string (export/→export)

1 files changed, 13 insertions, 8 deletions

diff --git a/cnn_v3/training/train_cnn_v3.py b/cnn_v3/training/train_cnn_v3.py
index 5b6a0be..e48f684 100644
--- a/cnn_v3/training/train_cnn_v3.py
+++ b/cnn_v3/training/train_cnn_v3.py
@@ -21,6 +21,7 @@ Weight budget: ~15.3 KB conv f16 (7828 f16); total with MLP ~17.9 KB
 Training improvements:
   --edge-loss-weight   Sobel edge loss alongside MSE (default 0.1)
   --film-warmup-epochs Train U-Net only for N epochs before unfreezing FiLM MLP (default 50)
+  --checkpoint-every   Save checkpoint every N epochs (default 100)
 """
 
 import argparse
@@ -309,18 +310,22 @@ def main():
                    help='Search ±N px in target to minimise grayscale MSE (default 0=disabled)')
 
     # Model
-    p.add_argument('--enc-channels', default='4,8',
-                   help='Encoder channels, comma-separated (default 4,8)')
+    p.add_argument('--enc-channels', default='8,16',
+                   help='Encoder channels, comma-separated (default 8,16)')
     p.add_argument('--film-cond-dim', type=int, default=5,
                    help='FiLM conditioning input dim (default 5)')
 
     # Training
-    p.add_argument('--epochs',           type=int,   default=200)
-    p.add_argument('--batch-size',       type=int,   default=16)
-    p.add_argument('--lr',               type=float, default=1e-3)
-    p.add_argument('--checkpoint-dir',   default='checkpoints')
-    p.add_argument('--checkpoint-every', type=int,   default=50,
-                   help='Save checkpoint every N epochs (0=disable)')
+    p.add_argument('--epochs',           type=int,   default=200,
+                   help='Total training epochs (default 200)')
+    p.add_argument('--batch-size',       type=int,   default=16,
+                   help='Batch size (default 16)')
+    p.add_argument('--lr',               type=float, default=1e-3,
+                   help='Learning rate (default 1e-3)')
+    p.add_argument('--checkpoint-dir',   default='checkpoints',
+                   help='Directory to save checkpoints (default checkpoints)')
+    p.add_argument('--checkpoint-every', type=int,   default=100,
+                   help='Save checkpoint every N epochs (default 100; 0=disable)')
     p.add_argument('--resume', default='', metavar='CKPT',
                    help='Resume from checkpoint path; if path missing, use latest in --checkpoint-dir')
     p.add_argument('--edge-loss-weight', type=float, default=0.1,