Add files using upload-large-folder tool

configs/config.py

@@ -74,6 +74,20 @@ parser.add_argument("--frame_n", type=int, default=10, help="Frame num of each v
 parser.add_argument("--text_max_len", type=int, default=25, help="Maximum textual reference length.")
 parser.add_argument("--max_eval_rows", type=int, default=-1, help="Max samples per split during eval; -1 = all.")
 parser.add_argument("--eval_split", type=str, default="test_u", help="Which split to evaluate: test_s, test_u, test_n.")
+parser.add_argument("--gate_only", action="store_true", help="Train only A-min referent gate parameters.")
+parser.add_argument("--init_from_saved_model", action="store_true", help="Initialize training from --saved_model before updates.")
+parser.add_argument("--max_steps", type=int, default=-1, help="Max optimizer steps during training; -1 = full schedule.")
+parser.add_argument("--overfit_samples", type=int, default=-1, help="Train on the first N train samples for overfit probes; -1 = full train set.")
+parser.add_argument("--log_gate_stats_every", type=int, default=-1, help="Log A-min gate/proj stats every N optimizer steps; -1 = disabled.")
+parser.add_argument("--skip_eval_after_train", action="store_true", help="Save checkpoint and exit without post-train evaluation.")
+parser.add_argument("--eval_train_only", action="store_true", help="After training, evaluate only the training subset and skip test splits.")
+parser.add_argument("--cache_root", type=str, default="/workspace/SimToken/cache_q", help="Root directory for cached q features.")
+parser.add_argument("--cache_split", type=str, default="train", help="Dataset split to cache or read cached q features from.")
+parser.add_argument("--overwrite_cache", action="store_true", help="Overwrite existing cached q feature files.")
+parser.add_argument("--eval_only", action="store_true", help="Only evaluate in cached-gate scripts; do not train.")
+parser.add_argument("--disable_gate", action="store_true", help="Force A-min gate to identity for cached pipeline baseline checks.")
+parser.add_argument("--gate_checkpoint", type=str, default="", help="Optional referent-gate-only checkpoint to overlay after loading --saved_model.")
+parser.add_argument("--save_gate_only", action="store_true", help="In cached-gate training, save only referent_gate parameters.")