refactor: remove block-sequential gate path and gate_block knob (algo #6)

config/train_videomme.yaml 同时收录待入库的实验配置变更(run_id v2 /
concurrency 32 / batch_size 40)。tests/integration/test_v3_contract_e2e.py
的 run_id 断言按 Task 5 显式契约同步修正(原断言依赖旧隐式实例注入)。

config/default.yaml

@@ -42,7 +42,6 @@ harness:
   gate_delta_min: 0.02
   gate_lambda_dir: -0.642
   gate_e_rollback: 10.0
-  gate_block: 8
   gate_n_max: 40
   gate_p_low: 0.05
   gate_p_high: 0.95

config/question_gen_180_补.yaml

@@ -39,7 +39,6 @@ harness:
   gate_delta_min: 0.02
   gate_lambda_dir: -0.642
   gate_e_rollback: 10.0
-  gate_block: 8
   gate_n_max: 40
   gate_p_low: 0.05
   gate_p_high: 0.95

config/question_gen_360.yaml

@@ -42,7 +42,6 @@ harness:
   gate_delta_min: 0.02
   gate_lambda_dir: -0.642
   gate_e_rollback: 10.0
-  gate_block: 8
   gate_n_max: 40
   gate_p_low: 0.05
   gate_p_high: 0.95

config/train_action_recognition.yaml

@@ -22,7 +22,6 @@ harness:
   gate_delta_min: 0.02
   gate_lambda_dir: -0.642
   gate_e_rollback: 10.0
-  gate_block: 8
   gate_n_max: 40
   gate_p_low: 0.05
   gate_p_high: 0.95

config/train_ar30.yaml

@@ -23,7 +23,6 @@ harness:
   gate_delta_min: 0.02
   gate_lambda_dir: -0.642
   gate_e_rollback: 10.0
-  gate_block: 8
   gate_n_max: 40
   gate_p_low: 0.05
   gate_p_high: 0.95

config/train_videomme.yaml

@@ -10,8 +10,8 @@ harness:
   workspace_dir: "workspaces/train-videomme"
   store_dir: store
   mode: train
-  run_id: train_videomme_v1
-  concurrency: 24
+  run_id: train_videomme_v2
+  concurrency: 32
   max_steps: 40
   skill_mode: auto
   n_samples: 0
@@ -26,7 +26,6 @@ harness:
   gate_delta_min: 0.02
   gate_lambda_dir: -0.642
   gate_e_rollback: 10.0
-  gate_block: 8
   gate_n_max: 40
   gate_p_low: 0.05
   gate_p_high: 0.95
@@ -51,8 +50,10 @@ harness:
   # 可训练性预检（WP3）：val 单元 < eval_min_per_class 或 非test单元 < trainable_min_units 的题型剔除
   eval_min_per_class: 2
   trainable_min_units: 8
-  # mini-batch
-  batch_size: 10
+  # mini-batch —— 对齐 TRM4 正式实验 batch=40（sh --batch-size 40 覆盖 yaml 15 的最终生效值）：
+  # 8 可训题型 × 每型约 5 题/step，保住题型级诊断信号；同时 steps/epoch 180/40≈5，
+  # 进化/gate 验证轮数比 batch=10 少 4 倍。
+  batch_size: 40
   min_class_per_batch: 2
   batch_correct_ratio: 0.5
   momentum_samples: 20