Merge pull request #219 from the-database/dev

fix console log rendering

traiNNer/utils/logger.py

@@ -112,8 +112,8 @@ def __call__(self, log_vars: dict[str, Any]) -> None:
         lrs = log_vars.pop("lrs")
 
         # Construct the base message with epoch, iteration, and learning rates
-        message = f"[epoch:{epoch:4,d}, iter:{current_iter:8,d}, lr:("
-        message += ", ".join([f"{v:.3e}" for v in lrs]) + ")] "
+        message = f"[ epoch:{epoch:4,d}, iter:{current_iter:8,d}, lr:("
+        message += ", ".join([f"{v:.3e}" for v in lrs]) + ") ] "
 
         # performance, eta
         if "time" in log_vars.keys():
@@ -125,11 +125,11 @@ def __call__(self, log_vars: dict[str, Any]) -> None:
             eta_sec = time_sec_avg * (self.max_iters - current_iter - 1)
             eta_str = str(datetime.timedelta(seconds=int(eta_sec)))
 
-            message += f"[performance: {iter_time:.3f} it/s] [eta: {eta_str}] "
+            message += f"[ performance: {iter_time:.3f} it/s ] [ eta: {eta_str} ] "
 
         # peak VRAM
         message += (
-            f"[peak VRAM: {torch.cuda.max_memory_allocated() / (1024**3):.2f} GB] "
+            f"[ peak VRAM: {torch.cuda.max_memory_allocated() / (1024**3):.2f} GB ] "
         )
 
         # Log any additional variables (typically losses)
@@ -141,6 +141,7 @@ def __call__(self, log_vars: dict[str, Any]) -> None:
                 self.tb_logger.add_scalar(label, value, current_iter)
 
         # Log the final constructed message
+
         self.logger.info(message)