feat: utilize a6000

train.py

@@ -1,4 +1,5 @@
 import os
+import torch
 import pytorch_lightning as ptl
 from pytorch_lightning.loggers import TensorBoardLogger
 
@@ -7,6 +8,8 @@ from detector.model import FontDetector, ResNet18Regressor
 from utils import get_current_tag
 
 
+torch.set_float32_matmul_precision('high')
+
 devices = [6, 7]
 
 final_batch_size = 128