update logs

handler.py

@@ -4,27 +4,20 @@ from PIL import Image
 import requests
 from transformers import AutoModelForCausalLM, LlamaTokenizer
 import torch
-from accelerate import (
-    init_empty_weights,
-    infer_auto_device_map,
-    load_checkpoint_and_dispatch,
-)
+# from accelerate import (
+#     init_empty_weights,
+#     infer_auto_device_map,
+#     load_checkpoint_and_dispatch,
+# )
 import os
 
 import logging
-from transformers import logging as hf_logging
+# from transformers import logging as hf_logging
+# hf_logging.set_verbosity_debug()
 
 logging.basicConfig(level=logging.INFO)
-hf_logging.set_verbosity_debug()
 
 
-def list_files(directory, depth, max_depth=5):
-    # Lists all files and directories in the given directory
-    for filename in os.listdir(directory):
-        print(os.path.join(directory, filename))
-        if not os.path.isfile(filename) and depth < max_depth:
-            list_files(os.path.join(directory, filename), depth + 1, max_depth)
-
 
 class EndpointHandler:
     def __init__(self, path=""):
@@ -122,9 +115,9 @@ class EndpointHandler:
 
         with torch.no_grad():
             outputs = self.model.generate(**inputs, **gen_kwargs)
-            print("OUTPUTS 1: ", outputs)
+            logging.info(f"OUTPUTS 1: {outputs}")
             outputs = outputs[:, inputs["input_ids"].shape[1] :]
-            print("OUTPUTS 2: ", outputs)
+            logging.info(f"OUTPUTS 2: {outputs}")
             response = self.tokenizer.decode(outputs[0])
             return response