done

Author: Hangzhi

tests/teleprompt/test_bootstrap_finetune.py

@@ -7,7 +7,6 @@
 
 # Define a simple metric function for testing
 def simple_metric(example, prediction, trace=None):
-    # Simplified metric for testing: true if prediction matches expected output
     return example.output == prediction.output
 
 
@@ -41,20 +40,15 @@ def test_compile_with_predict_instances_no_explicit_lm():
     from unittest.mock import patch
 
     # Create student and teacher modules without explicit LMs in predictors
-    # This tests the fix: lm = pred.lm or settings.lm
     student = SimpleModule("input -> output")
     teacher = SimpleModule("input -> output")
 
-    # Set up LM in settings - this will be the fallback
     lm = DummyLM(["Initial thoughts", "Finish[blue]"])
     original_lm = dspy.settings.lm
     dspy.settings.configure(lm=lm)
 
-
     # Verify that the predictor doesn't have an explicit LM
     assert student.predictor.lm is None
-
-    # Initialize BootstrapFinetune - this should work without AttributeError
     bootstrap = BootstrapFinetune(metric=simple_metric)
 
     # Mock all the components that would fail without proper setup
@@ -64,14 +58,12 @@ def test_compile_with_predict_instances_no_explicit_lm():
             patch.object(bootstrap, '_prepare_finetune_data', return_value=([], 'openai')), \
             patch.object(bootstrap, 'finetune_lms') as mock_finetune_lms:
 
-        # Mock the finetune_lms to return a mapping from training key to LM
         mock_finetune_lms.return_value = {(lm, None): lm}
 
         # This should not raise AttributeError due to the fix
         compiled_student = bootstrap.compile(student, teacher=teacher, trainset=trainset)
 
         assert compiled_student is not None, "Failed to compile student"
-        # Verify that finetune_lms was called
         mock_finetune_lms.assert_called_once()