refactor: remove assert statement from non-test files

scripts/ci/model_compression_test.py

@@ -122,8 +122,10 @@ def test_model_compression():
         compression_ratio = original_size / compressed_size
         logger.info("Compression ratio: {compression_ratio:.2f}x")
 
-        assert compressed_size < original_size, "Model should be smaller after compression"
-        assert compression_ratio > 1.0, "Compression ratio should be greater than 1"
+        if compressed_size >= original_size:
+            raise AssertionError("Model should be smaller after compression")
+        if compression_ratio <= 1.0:
+            raise AssertionError("Compression ratio should be greater than 1")
 
         with tempfile.NamedTemporaryFile(suffix=".pt", delete=True) as temp_file:
             torch.save(quantized_model.state_dict(), temp_file.name)

scripts/ci/model_monitoring_test.py

@@ -121,10 +121,14 @@ def test_model_performance_monitoring():
         logger.info("Recall: {metrics['recall']:.4f}")
         logger.info("F1 Score: {metrics['f1_score']:.4f}")
 
-        assert 0 <= metrics['accuracy'] <= 1, "Accuracy should be between 0 and 1"
-        assert 0 <= metrics['precision'] <= 1, "Precision should be between 0 and 1"
-        assert 0 <= metrics['recall'] <= 1, "Recall should be between 0 and 1"
-        assert 0 <= metrics['f1_score'] <= 1, "F1 score should be between 0 and 1"
+        if not 0 <= metrics['accuracy'] <= 1:
+            raise AssertionError("Accuracy should be between 0 and 1")
+        if not 0 <= metrics['precision'] <= 1:
+            raise AssertionError("Precision should be between 0 and 1")
+        if not 0 <= metrics['recall'] <= 1:
+            raise AssertionError("Recall should be between 0 and 1")
+        if not 0 <= metrics['f1_score'] <= 1:
+            raise AssertionError("F1 score should be between 0 and 1")
 
         logger.info("✅ Model performance monitoring test passed")
         return True
@@ -162,8 +166,10 @@ def test_model_drift_detection():
         logger.info("Accuracy drift: {accuracy_drift:.4f}")
         logger.info("F1 score drift: {f1_drift:.4f}")
 
-        assert accuracy_drift >= 0, "Drift should be non-negative"
-        assert f1_drift >= 0, "Drift should be non-negative"
+        if accuracy_drift < 0:
+            raise AssertionError("Drift should be non-negative")
+        if f1_drift < 0:
+            raise AssertionError("Drift should be non-negative")
 
         logger.info("✅ Model drift detection test passed")
         return True
@@ -196,10 +202,14 @@ def test_monitoring_logging():
 
         logger.info("Monitoring log entry: {log_entry}")
 
-        assert 'timestamp' in log_entry, "Log entry should have timestamp"
-        assert 'model_version' in log_entry, "Log entry should have model version"
-        assert 'metrics' in log_entry, "Log entry should have metrics"
-        assert 'status' in log_entry, "Log entry should have status"
+        if 'timestamp' not in log_entry:
+            raise AssertionError("Log entry should have timestamp")
+        if 'model_version' not in log_entry:
+            raise AssertionError("Log entry should have model version")
+        if 'metrics' not in log_entry:
+            raise AssertionError("Log entry should have metrics")
+        if 'status' not in log_entry:
+            raise AssertionError("Log entry should have status")
 
         logger.info("✅ Monitoring logging test passed")
         return True

scripts/ci/t5_summarization_test.py

@@ -39,9 +39,12 @@ def test_t5_model_loading():
         logger.info("✅ T5 model initialized successfully")
 
         # Test basic model properties
-        assert hasattr(model, "model"), "Model should have 'model' attribute"
-        assert hasattr(model, "tokenizer"), "Model should have 'tokenizer' attribute"
-        assert hasattr(model, "device"), "Model should have 'device' attribute"
+        if not hasattr(model, "model"):
+            raise AssertionError("Model should have 'model' attribute")
+        if not hasattr(model, "tokenizer"):
+            raise AssertionError("Model should have 'tokenizer' attribute")
+        if not hasattr(model, "device"):
+            raise AssertionError("Model should have 'device' attribute")
 
         logger.info("✅ Model attributes validation passed")
 
@@ -83,7 +86,8 @@ def test_t5_summarization():
 
         # Validate summary
         assert isinstance(summary, str), "Summary should be a string"
-        assert len(summary) > 0, "Summary should not be empty"
+        if len(summary) <= 0:
+            raise AssertionError("Summary should not be empty")
         assert len(summary) < len(test_text), "Summary should be shorter than input"
 
         logger.info("✅ Summary validation passed")