change : ray conf

image_ref/main_ray.py

@@ -18,11 +18,19 @@ from ray.tune.schedulers import ASHAScheduler
 
 def train_model(config,args):
     # load data
+
+    if config['res_count_thr']=='none':
+        ref_dir = '/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/img_ref'
+    elif config['res_count_thr']=='10':
+        ref_dir = '/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/img_ref_count_th_10'
+    else :
+        ref_dir = '/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/img_ref_count_th_5'
+
     data_train, data_val_batch, _ = load_data_duo(base_dir_train=args.dataset_train_dir,
                                                   base_dir_val=args.dataset_val_dir,
                                                   base_dir_test=args.dataset_test_dir,
                                                   batch_size=args.batch_size,
-                                                  ref_dir=args.dataset_ref_dir,
+                                                  ref_dir=ref_dir,
                                                   noise_threshold=config['noise'],
                                                   positive_prop=config['p_prop'], sampler=config['sampler'])
 
@@ -149,12 +157,20 @@ def train_model(config,args):
 
 
 def test_model(best_result, args):
+
+    if best_result.config['res_count_thr']=='none':
+        ref_dir = '/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/img_ref'
+    elif best_result.config['res_count_thr']=='10':
+        ref_dir = '/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/img_ref_count_th_10'
+    else :
+        ref_dir = '/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/img_ref_count_th_5'
+
     # load data
     _, data_val_batch, _ = load_data_duo(base_dir_train=args.dataset_train_dir,
                                          base_dir_val=args.dataset_val_dir,
                                          base_dir_test=args.dataset_test_dir,
                                          batch_size=args.batch_size,
-                                         ref_dir=args.dataset_ref_dir,
+                                         ref_dir=ref_dir,
                                          noise_threshold=best_result.config['noise'],
                                          positive_prop=best_result.config['p_prop'], sampler=best_result.config['sampler'])
 
@@ -217,6 +233,7 @@ def main(args, gpus_per_trial=1):
         "p_prop": tune.uniform(5, 95),
         "optimizer": tune.choice(['Adam', 'SGD']), #adam plus efficace ?
         "sampler": tune.choice(['random', 'balanced']),
+        "ref_count_thr" : tune.choice(['none', '10', '5'])
     }
     scheduler = ASHAScheduler(
         max_t=100,
@@ -235,13 +252,13 @@ def main(args, gpus_per_trial=1):
             time_budget_s=3600 * 19.5,
             search_alg=algo,
             scheduler=scheduler,
-            num_samples=50,
+            num_samples=-1,
             metric="val loss",
             mode='min',
 
         ),
         run_config=RunConfig(storage_path="/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/image_ref/ray_results_test",
-                             name="weight_val_loss_experiment"
+                             name="ref_count_threshold_experiment"
                              ),
         param_space=config