official/cv/EAST/EAST-msadapter/loss.py

@@ -38,5 +38,5 @@ class Loss(nn.Module):
 		iou_loss = torch.sum(iou_loss_map*gt_score) / torch.sum(gt_score)
 		geo_loss = self.weight_angle * angle_loss + iou_loss
 		print('classify loss is {:.8f}, angle loss is {:.8f}, iou loss is {:.8f}'.format(classify_loss, angle_loss, iou_loss))
-		# print('classify loss is {:.8f}, angle loss is {:.8f}, iou loss is {:.8f}'.format(classify_loss, angle_loss, iou_loss))	# for graph mode accelerating
+		# print('classify loss is ', classify_loss, 'angle loss is ', angle_loss, ' iou loss is ', iou_loss)	# for graph mode accelerating, Graph mode don't support format print.
 		return geo_loss + classify_loss

official/cv/EAST/EAST-msadapter/model.py

@@ -33,11 +33,11 @@ class VGG(nn.Module):
 		self.classifier = nn.Sequential(
 			nn.Linear(512 * 7 * 7, 4096),
 			nn.ReLU(True),
-			# nn.ReLU(True),	# for graph mode accelerating
+			# nn.ReLU(False),	# for graph mode accelerating
 			nn.Dropout(),
 			nn.Linear(4096, 4096),
 			nn.ReLU(True),
-			# nn.ReLU(True),	# for graph mode accelerating
+			# nn.ReLU(False),	# for graph mode accelerating
 			nn.Dropout(),
 			nn.Linear(4096, 1000),
 		)