v0.1.3

robogauge/utils/helpers.py

@@ -14,7 +14,7 @@ from argparse import ArgumentParser
 from pathlib import Path
 from robogauge import ROBOGAUGE_ROOT_DIR
 
-def pares_path(path):
+def parse_path(path):
     if "{ROBOGAUGE_ROOT_DIR}" in str(path):
         path = str(path).replace("{ROBOGAUGE_ROOT_DIR}", ROBOGAUGE_ROOT_DIR)
     return path
@@ -47,10 +47,13 @@ def parse_args():
     parser = ArgumentParser()
     parameters = [
         {"name": "--task-name", "type": str, "default": "base", "help": "Name of the task to run."},
-        {"name": "--experiment-name", "type": str, "default": "base", "help": "Name of the experiment to run."},
+        {"name": "--experiment-name", "type": str, "help": "Name of the experiment to run."},
         {"name": "--headless", "action": "store_true", "default": False, "help": "Run in headless mode."},
         {"name": "--save-video", "action": "store_true", "default": False, "help": "Save video output."},
     ]
     for param in parameters:
         parser.add_argument(param['name'], **{k: v for k, v in param.items() if k != 'name'})
-    return parser.parse_args()
+    args = parser.parse_args()
+    if args.experiment_name is None:
+        args.experiment_name = f"{args.task_name}_exp"
+    return args

robogauge/utils/logger.py

@@ -14,6 +14,7 @@ import time
 import logging
 from pathlib import Path
 from robogauge import ROBOGAUGE_ROOT_DIR
+from torch.utils.tensorboard import SummaryWriter
 
 class LogColor:
     """ ANSI color codes """
@@ -49,6 +50,10 @@ class ColorFormatter(logging.Formatter):
 
 
 class Logger:
+    logger: logging.Logger = None
+    log_dir: Path = None
+    writer: SummaryWriter = None
+
     def create(self,
         experiment_name,
         console_output=True, color_output=True,
@@ -93,6 +98,12 @@ class Logger:
             fh = logging.FileHandler(path_log_file, mode=save_file_mode, encoding='utf-8')
             fh.setFormatter(file_formatter)
             self.logger.addHandler(fh)
+    
+    def create_tensorboard(self, run_name: str):
+        if self.writer is not None:
+            self.writer.close()
+        self.writer = SummaryWriter(str(self.log_dir / run_name))
+        self.info(f"Tensorboard writer created at: {self.log_dir / run_name}")
 
     def debug(self, msg, *args, **kwargs):
         self.logger.debug(msg, *args, **kwargs, stacklevel=2)
@@ -108,6 +119,19 @@ class Logger:
 
     def critical(self, msg, *args, **kwargs):
         self.logger.critical(msg, *args, **kwargs, stacklevel=2)
+    
+    def log(self, value, tag, step):
+        """ Log scalar value to tensorboard
+
+        Args:
+            value (float): scalar value
+            tag (str): tag name
+            step (int): step number
+        """
+        if self.writer is not None:
+            self.writer.add_scalar(tag, value, step)
+        else:
+            self.warning("Tensorboard writer is not initialized, skipping log.")
 
 logger = Logger()
 

robogauge/utils/task_register.py

@@ -33,7 +33,7 @@ class TaskRegister():
         robot_cfg = self.robot_cfgs[name]
         return sim_cfg, gauger_cfg, robot_cfg
     
-    def make_pipeline(self, name, args=None, sim_cfg=None, gauger_cfg=None, robot_cfg=None):
+    def make_pipeline(self, name, args=None, sim_cfg=None, gauger_cfg=None, robot_cfg=None, run_name='0'):
         default_cfgs = self.get_cfgs(name)
         if sim_cfg is None:
             sim_cfg = default_cfgs[0]
@@ -44,7 +44,7 @@ class TaskRegister():
         if args is not None:
             self.update_args_to_cfg(sim_cfg, gauger_cfg, robot_cfg, args)
         pipeline_class = self.get_pipeline_class(name)
-        return pipeline_class(sim_cfg, robot_cfg, gauger_cfg)
+        return pipeline_class(run_name, sim_cfg, robot_cfg, gauger_cfg)
 
     def update_args_to_cfg(self, sim_cfg, gauger_cfg, robot_cfg, args):
         if args.headless is not None: