rename variables

tests/unit_tests/test_pytorch_model.py

@@ -102,34 +102,33 @@ def test_save_load(remove_checkpoint):
     sim1 = Simulator()
     sim2 = Simulator()
 
-    fe = learn_to_pick.PyTorchFeatureEmbedder()
     first_model_path = f"{CHECKPOINT_DIR}/first.checkpoint"
 
     torch.manual_seed(0)
-    first_byom = learn_to_pick.PyTorchPolicy(feature_embedder=fe)
-    second_byom = learn_to_pick.PyTorchPolicy(feature_embedder=fe)
+    first_policy = learn_to_pick.PyTorchPolicy()
+    other_policy = learn_to_pick.PyTorchPolicy()
 
     torch.manual_seed(0)
 
     first_picker = learn_to_pick.PickBest.create(
-        policy=first_byom, selection_scorer=CustomSelectionScorer()
+        policy=first_policy, selection_scorer=CustomSelectionScorer()
     )
     sim1.run(first_picker, 5)
-    first_byom.save(first_model_path)
+    first_policy.save(first_model_path)
 
-    second_byom.load(first_model_path)
-    second_picker = learn_to_pick.PickBest.create(
-        policy=second_byom, selection_scorer=CustomSelectionScorer()
+    other_policy.load(first_model_path)
+    other_picker = learn_to_pick.PickBest.create(
+        policy=other_policy, selection_scorer=CustomSelectionScorer()
     )
-    sim1.run(second_picker, 5)
+    sim1.run(other_picker, 5)
 
     torch.manual_seed(0)
-    all_byom = learn_to_pick.PyTorchPolicy(feature_embedder=fe)
+    all_policy = learn_to_pick.PyTorchPolicy()
     torch.manual_seed(0)
     all_picker = learn_to_pick.PickBest.create(
-        policy=all_byom, selection_scorer=CustomSelectionScorer()
+        policy=all_policy, selection_scorer=CustomSelectionScorer()
     )
     sim2.run(all_picker, 10)
 
-    verify_same_models(second_byom.workspace, all_byom.workspace)
-    verify_same_optimizers(second_byom.workspace.optim, all_byom.workspace.optim)
+    verify_same_models(other_policy.workspace, all_policy.workspace)
+    verify_same_optimizers(other_policy.workspace.optim, all_policy.workspace.optim)