less noisy

model.py

@@ -410,9 +410,9 @@ def disable_dropout(model: torch.nn.Module):
     dropout_modules = [m for m in model.modules() if isinstance(m, torch.nn.Dropout)]
     for m in dropout_modules:
         m.p = 0.0
-    print0(
-        f"Disabled {len(dropout_modules)} dropout modules from model type {type(model)}"
-    )
+    #print0(
+    #    f"Disabled {len(dropout_modules)} dropout modules from model type {type(model)}"
+    #)
 
 
 def disable_causality(model: torch.nn.Module):
@@ -793,7 +793,7 @@ class DatasetConditionedBiencoder(transformers.PreTrainedModel, ContextualModelM
                 if hasattr(module, "rotary_emb_dim"):
                     module.rotary_start_pos = rotary_start_pos
                     rotary_disabled += 1
-            print0(f"modified {rotary_disabled} rotary modules – set rotary_start_pos to {rotary_start_pos}")
+            # print0(f"modified {rotary_disabled} rotary modules – set rotary_start_pos to {rotary_start_pos}")
     
     def forward(
             self,