fix duplicated sample gen for every epoch ref #907

train_db.py

@@ -272,13 +272,14 @@ def train(args):
             init_kwargs = toml.load(args.log_tracker_config)
         accelerator.init_trackers("dreambooth" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
 
+    # For --sample_at_first
+    train_util.sample_images(accelerator, args, 0, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
+
     loss_recorder = train_util.LossRecorder()
     for epoch in range(num_train_epochs):
         accelerator.print(f"\nepoch {epoch+1}/{num_train_epochs}")
         current_epoch.value = epoch + 1
 
-        train_util.sample_images(accelerator, args, epoch, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
-
         # 指定したステップ数までText Encoderを学習する：epoch最初の状態
         unet.train()
         # train==True is required to enable gradient_checkpointing