better logging

code/inference.py

@@ -8,18 +8,23 @@ JSON_CONTENT_TYPE = 'application/json'
 
 
 def model_fn(model_dir):
-    logger.info(f"model_dir: {model_dir}")
+    logging.info('[### model_fn ###] Loading model from {}'.format(model_dir))
     model = QAGeneratorPipeline(model_dir=model_dir, use_cuda=True)
     return model
 
 
 def predict_fn(input_data, model):
+    logging.info('[### predict_fn ###] Entering predict_fn() method')
     logger.info("input text: {}".format(input_data))
     prediction = model(input_data)
     logger.info("prediction: {}".format(input_data))
 
 
 def input_fn(serialized_input_data, content_type=JSON_CONTENT_TYPE):
+    logging.info('[### input_fn ###] Entering input_fn() method')
+    logging.info('[### input_fn ###] request_content_type: {}'.format(content_type))
+    logging.info('[### input_fn ###] request_body: {}'.format(type(serialized_input_data)))
+
     if content_type == JSON_CONTENT_TYPE:
         input_data = json.loads(serialized_input_data)
         return input_data
@@ -28,6 +33,8 @@ def input_fn(serialized_input_data, content_type=JSON_CONTENT_TYPE):
 
 
 def output_fn(prediction_output, accept=JSON_CONTENT_TYPE):
+    logging.info('[### output_fn ###] Entering output_fn() method')
+    logging.info('[### output_fn ###] prediction: {}'.format(prediction_output))
     if accept == JSON_CONTENT_TYPE:
         return json.dumps(prediction_output), accept
     raise Exception('Unsupported Content Type')