del swanlab

diffsynth/trainers/text_to_image.py

@@ -250,18 +250,6 @@ def add_general_parsers(parser):
         default=None,
         help="Pretrained LoRA path. Required if the training is resumed.",
     )
-    parser.add_argument(
-        "--use_swanlab",
-        default=False,
-        action="store_true",
-        help="Whether to use SwanLab logger.",
-    )
-    parser.add_argument(
-        "--swanlab_mode",
-        default=None,
-        help="SwanLab mode (cloud or local).",
-    )
-    
     return parser
 
 
@@ -282,22 +270,6 @@ def launch_training_task(model, args):
         num_workers=args.dataloader_num_workers
     )
 
-    # set swanlab logger
-    if args.use_swanlab:
-        from swanlab.integration.pytorch_lightning import SwanLabLogger
-        swanlab_config = {"UPPERFRAMEWORK": "DiffSynth-Studio"}
-        swanlab_config.update(vars(args))
-        swanlab_logger = SwanLabLogger(
-            project="diffsynth_studio", 
-            name="diffsynth_studio",
-            config=swanlab_config,
-            mode=args.swanlab_mode,
-            logdir=args.output_path,
-        )
-        logger = [swanlab_config]
-    else:
-        logger = []
-
     # train
     trainer = pl.Trainer(
         max_epochs=args.max_epochs,
@@ -308,7 +280,6 @@ def launch_training_task(model, args):
         default_root_dir=args.output_path,
         accumulate_grad_batches=args.accumulate_grad_batches,
         callbacks=[pl.pytorch.callbacks.ModelCheckpoint(save_top_k=-1)],
-        logger=logger,
     )
     trainer.fit(model=model, train_dataloaders=train_loader)