diff --git a/data/src/auto/heatmap.ts b/data/src/auto/heatmap.ts
index 2a27844..40876fe 100644
--- a/data/src/auto/heatmap.ts
+++ b/data/src/auto/heatmap.ts
@@ -20,9 +20,9 @@ export function generateHeatmap(
     for (let y = 0; y < height; y++) {
         for (let x = 0; x < width; x++) {
             const left = Math.max(0, x - radius);
-            const right = Math.min(width, x + radius);
+            const right = Math.min(width, x + radius + 1);
             const top = Math.max(0, y - radius);
-            const bottom = Math.min(height, y + radius);
+            const bottom = Math.min(height, y + radius + 1);
             const size = (right - left) * (bottom - top);
             let num = 0;
             for (let ky = top; ky < bottom; ky++) {
@@ -54,9 +54,9 @@ export function gaussainHeatmap(map: number[][], sigma: number = 1) {
     for (let y = 0; y < height; y++) {
         for (let x = 0; x < width; x++) {
             const left = Math.max(0, x - radius);
-            const right = Math.min(width - 1, x + radius);
+            const right = Math.min(width - 1, x + radius + 1);
             const top = Math.max(0, y - radius);
-            const bottom = Math.min(height - 1, y + radius);
+            const bottom = Math.min(height - 1, y + radius + 1);
             let res = 0;
             for (let ky = top; ky < bottom; ky++) {
                 for (let kx = left; kx < right; kx++) {
diff --git a/data/src/auto/info.ts b/data/src/auto/info.ts
index eebb302..3e3495b 100644
--- a/data/src/auto/info.ts
+++ b/data/src/auto/info.ts
@@ -229,15 +229,17 @@ export function parseFloorInfo(tower: ITowerInfo, map: number[][]): IFloorInfo {
         fishCount,
         hasUselessBranch,
         wallDensityStd: computeWallDensityStd(map, wallTiles, 5),
-        wallHeatmap: gaussainHeatmap(generateHeatmap(map, wallTiles)),
-        enemyHeatmap: gaussainHeatmap(generateHeatmap(map, enemyTiles)),
-        resourceHeatmap: gaussainHeatmap(generateHeatmap(map, resourceTiles)),
-        potionHeatmap: gaussainHeatmap(generateHeatmap(map, potionTiles)),
-        gemHeatmap: gaussainHeatmap(generateHeatmap(map, gemTiles)),
-        keyHeatmap: gaussainHeatmap(generateHeatmap(map, keyTiles)),
-        itemHeatmap: gaussainHeatmap(generateHeatmap(map, itemTiles)),
-        entryHeatmap: gaussainHeatmap(generateHeatmap(map, entryTiles)),
-        doorHeatmap: gaussainHeatmap(generateHeatmap(map, doorTiles))
+        wallHeatmap: gaussainHeatmap(generateHeatmap(map, wallTiles, 1)),
+        enemyHeatmap: gaussainHeatmap(generateHeatmap(map, enemyTiles, 1)),
+        resourceHeatmap: gaussainHeatmap(
+            generateHeatmap(map, resourceTiles, 1)
+        ),
+        potionHeatmap: gaussainHeatmap(generateHeatmap(map, potionTiles, 1)),
+        gemHeatmap: gaussainHeatmap(generateHeatmap(map, gemTiles, 1)),
+        keyHeatmap: gaussainHeatmap(generateHeatmap(map, keyTiles, 1)),
+        itemHeatmap: gaussainHeatmap(generateHeatmap(map, itemTiles, 1)),
+        entryHeatmap: gaussainHeatmap(generateHeatmap(map, entryTiles, 1)),
+        doorHeatmap: gaussainHeatmap(generateHeatmap(map, doorTiles, 1))
     };
 
     return floorInfo;
diff --git a/ginka/train_maskGIT.py b/ginka/train_maskGIT.py
index 26d0df7..15a02d2 100644
--- a/ginka/train_maskGIT.py
+++ b/ginka/train_maskGIT.py
@@ -43,6 +43,7 @@ MASK_TOKEN = 15
 GENERATE_STEP = 8
 MAP_SIZE = 13 * 13
 HEATMAP_CHANNEL = 9
+LABEL_SMOOTHING = 0.1
 MASK_PROBS = [0.5, 0.5] # 纯随机，分块随机
 
 device = torch.device(
@@ -129,7 +130,7 @@ def train():
             
             logits = model(masked_input, cond, heatmap)
             
-            loss = F.cross_entropy(logits.permute(0, 2, 1), target_map, reduction='none', label_smoothing=0.1)
+            loss = F.cross_entropy(logits.permute(0, 2, 1), target_map, reduction='none', label_smoothing=LABEL_SMOOTHING)
             loss = (loss * mask).sum() / (mask.sum() + 1e-6)
             
             optimizer.zero_grad()
@@ -181,7 +182,7 @@ def train():
                     
                     logits = model(masked_input, cond, heatmap)
                     
-                    loss = F.cross_entropy(logits.permute(0, 2, 1), target_map, reduction='none', label_smoothing=0.1)
+                    loss = F.cross_entropy(logits.permute(0, 2, 1), target_map, reduction='none', label_smoothing=LABEL_SMOOTHING)
                     loss = (loss * mask).sum() / (mask.sum() + 1e-6)
                     
                     val_loss_total += loss.detach()