add default settings

ml-agents/mlagents/trainers/components/bc/module_torch.py

             settings.demo_path, policy.sequence_length, policy.behavior_spec
         )
 
-        self.batch_size = (
-            settings.batch_size if settings.batch_size else default_batch_size
-        )
-        self.num_epoch = settings.num_epoch if settings.num_epoch else default_num_epoch
+        self.batch_size = settings.batch_size
+        self.num_epoch = settings.num_epoch
         self.n_sequences = max(
             min(self.batch_size, self.demonstration_buffer.num_experiences)
             // policy.sequence_length,

ml-agents/mlagents/trainers/settings.py

     steps: int = 0
     strength: float = 1.0
     samples_per_update: int = 0
-    # Setting either of these to None will allow the Optimizer
-    # to decide these parameters, based on Trainer hyperparams
-    num_epoch: Optional[int] = None
-    batch_size: Optional[int] = None
+    num_epoch: int = 3
+    batch_size: int = 64
 
 
 @attr.s(auto_attribs=True)