Update.

[mygptrnn.git] / main.py

diff --git a/main.py b/main.py
index 04e5652..3aa696b 100755 (executable)
--- a/main.py
+++ b/main.py
@@ -99,7 +99,11 @@ parser.add_argument("--nb_lines", type=int, default=None)
 
 parser.add_argument("--caterpillar_height", type=int, default=None)
 
-parser.add_argument("--rho", type=float, default=0.0)
+parser.add_argument("--gate_dropout_proba", type=float, default=0.0)
+
+parser.add_argument("--gate_dropout_sync", type=bool, default=False)
+
+parser.add_argument("--rho_inner_loss", type=float, default=0.0)
 
 parser.add_argument("--nb_blocks", type=int, default=None)
 
@@ -133,6 +137,10 @@ parser.add_argument("--rpl_no_prog", action="store_true", default=False)
 
 parser.add_argument("--grid_size", type=int, default=6)
 
+parser.add_argument("--grid_nb_colors", type=int, default=6)
+
+parser.add_argument("--grid_nb_shapes", type=int, default=6)
+
 ##############################
 # picoclvr options
 
@@ -701,6 +709,8 @@ elif args.task == "grid":
         nb_test_samples=args.nb_test_samples,
         batch_size=args.batch_size,
         size=args.grid_size,
+        nb_shapes=args.grid_nb_shapes,
+        nb_colors=args.grid_nb_colors,
         logger=log_string,
         device=device_data,
     )
@@ -741,7 +751,7 @@ model = mygpt.MyGPT(
     dropout=args.dropout,
     attention_layer=args.attention,
     logger=log_string,
-    **sup_args,
+    args=args,
 )
 
 model.to(device)
@@ -835,21 +845,22 @@ if args.max_percents_of_test_in_train >= 0:
 
 ##############################
 
-for input in task.batches(split="train", desc="calibrate"):
-    input = input.to(device)
-    output = model(mygpt.BracketedSequence(input)).x
+if "calibrate" in sup_args:
+    for input in task.batches(split="train", desc="calibrate"):
+        input = input.to(device)
+        output = model(mygpt.BracketedSequence(input)).x
 
-for n, m in model.named_modules():
-    for a in dir(m):
-        x = getattr(m, a)
-        if isinstance(x, mygpt.Calibrator):
-            print(f"####### ${n} | ${a} ########################")
-            mean, std = x.moments()
-            print("mean\n", mean, "\n")
-            print("std\n", std, "\n")
-            print(f"############################################\n\n")
+    for n, m in model.named_modules():
+        for a in dir(m):
+            x = getattr(m, a)
+            if isinstance(x, mygpt.Calibrator):
+                print(f"####### ${n} | ${a} ########################")
+                mean, std = x.moments()
+                print("mean\n", mean, "\n")
+                print("std\n", std, "\n")
+                print(f"############################################\n\n")
 
-exit(0)
+    exit(0)
 
 ##############################
 
@@ -898,7 +909,9 @@ for n_epoch in range(nb_epochs_finished, nb_epochs):
         nb_train_samples += input.size(0)
         nb_samples_seen += input.size(0)
 
-        total_loss = loss + (args.rho * inner_loss if args.rho > 0 else 0.0)
+        total_loss = loss + (
+            args.rho_inner_loss * inner_loss if args.rho_inner_loss > 0 else 0.0
+        )
 
         it += 1
         lr = get_lr(n_epoch, it)