RFE: replace print() with logging in core runtime modules

dexbotic/client.py

@@ -1,10 +1,13 @@
 from collections import deque
+import logging
 import requests
 import math
 
 import numpy as np
 import cv2
 
+logger = logging.getLogger(__name__)
+
 
 class DexClient:
     def __init__(self,
@@ -86,4 +89,4 @@ def delta_action(self, last_action, delta_action):
         action = client.act(
             observation,
             "What action should the robot take to put both moka pots on the stove?")
-        print("Action taken:", action)
+        logger.info("Action taken: %s", action)

dexbotic/rl/_embodied_cli.py

@@ -1,11 +1,14 @@
 from __future__ import annotations
 
 import json
+import logging
 import os
 
 import torch.multiprocessing as mp
 from omegaconf import OmegaConf
 
+logger = logging.getLogger(__name__)
+
 from rlinf.config import validate_cfg
 from rlinf.runners.embodied_runner import EmbodiedRunner
 from rlinf.scheduler import Cluster
@@ -25,12 +28,10 @@ def run_embodied_rl(cfg) -> None:
 
     register_all()
 
-    print(
-        "[Dexbotic RL] Launching from Dexbotic entrypoint with RLinf as backend."
-    )
+    logger.info("[Dexbotic RL] Launching from Dexbotic entrypoint with RLinf as backend.")
 
     cfg = validate_cfg(cfg)
-    print(json.dumps(OmegaConf.to_container(cfg, resolve=True), indent=2))
+    logger.info(json.dumps(OmegaConf.to_container(cfg, resolve=True), indent=2))
 
     cluster = Cluster(
         cluster_cfg=cfg.cluster, distributed_log_dir=cfg.runner.per_worker_log_path

playground/example_navila_exp.py

@@ -6,11 +6,14 @@
 
 """
 import argparse
+import logging
 from collections import deque
 from dataclasses import dataclass, field
 from datetime import datetime
 from typing import Optional
 
+logger = logging.getLogger(__name__)
+
 from dexbotic.data.dataset.transform.common import Pipeline, ToDict, ToList, ToNumpy
 from dexbotic.data.dataset.transform.multimodal import LoadMultiModal
 from dexbotic.exp.navila_exp import (
@@ -139,7 +142,7 @@ def inference_single(
             with open(image_path, "rb") as f:
                 image_bytes = f.read()
         except FileNotFoundError:
-            print(f"Error: image file not found {image_path}")
+            logger.error("Error: image file not found %s", image_path)
             return None
 
         images_list = self.inference_config._prepare_images(image_bytes)
@@ -150,7 +153,7 @@ def inference_single(
             text=prompt,
             images=images_list,
         )
-        print(f"Inference result: {result}")
+        logger.info("Inference result: %s", result)
         return result