修复17个样本的NaN问题：移除test_compiler中的-inf特殊处理，修复样本model.py中的-inf使用

- 从test_compiler.py移除-inf修复代码（通用组件不应包含特定算子处理）
- 修复IDEA-Research_grounding-dino-base和fushh7_llmdet_swin_tiny_hf的model.py，将-inf替换为-1e6
- 验证所有17个问题样本在inductor和nope后端均不再出现NaN
- 修复方案：仅在样本层面修复-inf问题，不修改通用组件

Author: Dayuxiaoshui

graph_net/torch/test_compiler.py

@@ -61,48 +61,6 @@ def load_class_from_file(
 
     with open(file_path, "r", encoding="utf-8") as f:
         model_code = f.read()
-    # Replace -inf with -1e6 in masked_fill and torch.full to prevent NaN issues
-    # This applies the same fix as apply_templates for already-generated model.py files
-    import re
-
-    # Pattern for masked_fill(..., -inf)
-    model_code = re.sub(
-        r"(masked_fill\([^,)]+,\s*)-inf(\s*\))", r"\1-1e6\2", model_code
-    )
-    # For torch.full, use a context-aware replacement
-    # Find torch.full(...) blocks and replace -inf within them
-    # Use a balanced bracket matcher approach
-    parts = []
-    i = 0
-    while i < len(model_code):
-        if model_code[i:].startswith("torch.full("):
-            # Find the matching closing parenthesis
-            depth = 0
-            start = i
-            j = i + len("torch.full(")
-            while j < len(model_code):
-                if model_code[j] == "(":
-                    depth += 1
-                elif model_code[j] == ")":
-                    if depth == 0:
-                        # Found the matching closing paren
-                        full_block = model_code[start : j + 1]
-                        # Replace -inf with -1e6 in this block
-                        full_block = full_block.replace("-inf", "-1e6")
-                        parts.append(full_block)
-                        i = j + 1
-                        break
-                    depth -= 1
-                j += 1
-            else:
-                # Didn't find closing paren, just append rest
-                parts.append(model_code[i:])
-                break
-        else:
-            parts.append(model_code[i])
-            i += 1
-    if parts:
-        model_code = "".join(parts)
     model_code = utils.modify_code_by_device(model_code, device)
     spec = importlib.util.spec_from_loader(module_name, loader=None)
     module = importlib.util.module_from_spec(spec)

samples/transformers-auto-model/IDEA-Research_grounding-dino-base/model.py

@@ -46,10 +46,10 @@ def forward(
         bool_1 = None
         invert = ~getitem_1
         getitem_1 = None
-        output_1 = output.masked_fill(invert, -inf)
+        output_1 = output.masked_fill(invert, -1e6)
         output = invert = None
         new_output = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output[(Ellipsis, slice(None, 7, None))] = output_1
         setitem = new_output
@@ -95,10 +95,10 @@ def forward(
         bool_2 = None
         invert_1 = ~getitem_5
         getitem_5 = None
-        output_3 = output_2.masked_fill(invert_1, -inf)
+        output_3 = output_2.masked_fill(invert_1, -1e6)
         output_2 = invert_1 = None
         new_output_1 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_1[(Ellipsis, slice(None, 7, None))] = output_3
         setitem_1 = new_output_1
@@ -144,10 +144,10 @@ def forward(
         bool_3 = None
         invert_2 = ~getitem_9
         getitem_9 = None
-        output_5 = output_4.masked_fill(invert_2, -inf)
+        output_5 = output_4.masked_fill(invert_2, -1e6)
         output_4 = invert_2 = None
         new_output_2 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_2[(Ellipsis, slice(None, 7, None))] = output_5
         setitem_2 = new_output_2
@@ -193,10 +193,10 @@ def forward(
         bool_4 = None
         invert_3 = ~getitem_13
         getitem_13 = None
-        output_7 = output_6.masked_fill(invert_3, -inf)
+        output_7 = output_6.masked_fill(invert_3, -1e6)
         output_6 = invert_3 = None
         new_output_3 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_3[(Ellipsis, slice(None, 7, None))] = output_7
         setitem_3 = new_output_3
@@ -242,10 +242,10 @@ def forward(
         bool_5 = None
         invert_4 = ~getitem_17
         getitem_17 = None
-        output_9 = output_8.masked_fill(invert_4, -inf)
+        output_9 = output_8.masked_fill(invert_4, -1e6)
         output_8 = invert_4 = None
         new_output_4 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_4[(Ellipsis, slice(None, 7, None))] = output_9
         setitem_4 = new_output_4
@@ -294,10 +294,10 @@ def forward(
         bool_6 = None
         invert_5 = ~getitem_21
         getitem_21 = None
-        output_11 = output_10.masked_fill(invert_5, -inf)
+        output_11 = output_10.masked_fill(invert_5, -1e6)
         output_10 = invert_5 = None
         new_output_5 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_5[(Ellipsis, slice(None, 7, None))] = output_11
         setitem_5 = new_output_5

samples/transformers-auto-model/fushh7_llmdet_swin_tiny_hf/model.py

@@ -106,10 +106,10 @@ def forward(
         bool_1 = None
         invert = ~getitem_1
         getitem_1 = None
-        output_1 = output.masked_fill(invert, -inf)
+        output_1 = output.masked_fill(invert, -1e6)
         output = invert = None
         new_output = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output[(Ellipsis, slice(None, 7, None))] = output_1
         setitem = new_output
@@ -155,10 +155,10 @@ def forward(
         bool_2 = None
         invert_1 = ~getitem_5
         getitem_5 = None
-        output_3 = output_2.masked_fill(invert_1, -inf)
+        output_3 = output_2.masked_fill(invert_1, -1e6)
         output_2 = invert_1 = None
         new_output_1 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_1[(Ellipsis, slice(None, 7, None))] = output_3
         setitem_1 = new_output_1
@@ -204,10 +204,10 @@ def forward(
         bool_3 = None
         invert_2 = ~getitem_9
         getitem_9 = None
-        output_5 = output_4.masked_fill(invert_2, -inf)
+        output_5 = output_4.masked_fill(invert_2, -1e6)
         output_4 = invert_2 = None
         new_output_2 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_2[(Ellipsis, slice(None, 7, None))] = output_5
         setitem_2 = new_output_2
@@ -253,10 +253,10 @@ def forward(
         bool_4 = None
         invert_3 = ~getitem_13
         getitem_13 = None
-        output_7 = output_6.masked_fill(invert_3, -inf)
+        output_7 = output_6.masked_fill(invert_3, -1e6)
         output_6 = invert_3 = None
         new_output_3 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_3[(Ellipsis, slice(None, 7, None))] = output_7
         setitem_3 = new_output_3
@@ -302,10 +302,10 @@ def forward(
         bool_5 = None
         invert_4 = ~getitem_17
         getitem_17 = None
-        output_9 = output_8.masked_fill(invert_4, -inf)
+        output_9 = output_8.masked_fill(invert_4, -1e6)
         output_8 = invert_4 = None
         new_output_4 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_4[(Ellipsis, slice(None, 7, None))] = output_9
         setitem_4 = new_output_4
@@ -354,10 +354,10 @@ def forward(
         bool_6 = None
         invert_5 = ~getitem_21
         getitem_21 = None
-        output_11 = output_10.masked_fill(invert_5, -inf)
+        output_11 = output_10.masked_fill(invert_5, -1e6)
         output_10 = invert_5 = None
         new_output_5 = torch.full(
-            (1, 900, 256), -inf, device=device(type="cuda", index=0)
+            (1, 900, 256), -1e6, device=device(type="cuda", index=0)
         )
         new_output_5[(Ellipsis, slice(None, 7, None))] = output_11
         setitem_5 = new_output_5