From 8f232a2103cd12a62568b65d0eb6b810d587fd3c Mon Sep 17 00:00:00 2001
From: mckay <wchpub@163.com>
Date: Sat, 23 Nov 2024 20:29:53 +0800
Subject: [PATCH] =?UTF-8?q?refactor:=20=E5=9C=A8networks=E6=96=87=E4=BB=B6?=
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---
 brep2sdf/networks/network.py | 33 +--------------------------------
 1 file changed, 1 insertion(+), 32 deletions(-)

diff --git a/brep2sdf/networks/network.py b/brep2sdf/networks/network.py
index 21279bc..889d61d 100644
--- a/brep2sdf/networks/network.py
+++ b/brep2sdf/networks/network.py
@@ -119,38 +119,7 @@ class BRepToSDF(nn.Module):
             logger.error(f"    query_points: {query_points.shape}")
             raise
 
-def sdf_loss(pred_sdf, gt_sdf, points, grad_weight: float = 0.1):
-    """SDF损失函数"""
-    # 确保points需要梯度
-    if not points.requires_grad:
-        points = points.detach().requires_grad_(True)
-    
-    # L1损失
-    l1_loss = F.l1_loss(pred_sdf, gt_sdf)
-    
-    try:
-        # 梯度约束损失
-        grad = torch.autograd.grad(
-            pred_sdf.sum(), 
-            points,
-            create_graph=True,
-            retain_graph=True,
-            allow_unused=True
-        )[0]
-        
-        if grad is not None:
-            grad_constraint = F.mse_loss(
-                torch.norm(grad, dim=-1),
-                torch.ones_like(pred_sdf.squeeze(-1))
-            )
-        else:
-            grad_constraint = torch.tensor(0.0, device=pred_sdf.device)
-            
-    except Exception as e:
-        logger.warning(f"Gradient computation failed: {str(e)}")
-        grad_constraint = torch.tensor(0.0, device=pred_sdf.device)
-    
-    return l1_loss + grad_weight * grad_constraint
+
 
 def main():
     # 获取配置