resolve merge conflicts

Author: G2uge

graph_net/torch/backend/unstable_to_stable_backend.py

@@ -126,50 +126,70 @@ def _impl_unstable_to_stable_fftn(self, gm):
 
         return gm
 
-    def _impl_unstable_to_stable_one_hot(self, gm):
+    def _impl_unstable_to_stable_special_logit(self, gm):
         """
-        Convert torch._C._nn.one_hot to torch.nn.functional.one_hot
+        Convert torch._C._special.special_logit to torch.special.logit
         """
-        import torch.nn.functional as F
-
         issue_nodes = (
             node
             for node in gm.graph.nodes
             if node.op == "call_function"
             if hasattr(node.target, "__module__")
-            if node.target.__module__ == "torch._C._nn"
+            if node.target.__module__ == "torch._C._special"
             if hasattr(node.target, "__name__")
-            if node.target.__name__ == "one_hot"
+            if node.target.__name__ == "special_logit"
         )
         for node in issue_nodes:
-            node.target = F.one_hot
+            node.target = torch.special.logit
 
         # Recompile the graph
         gm.recompile()
 
         return gm
 
-    def _impl_unstable_to_stable_special_logit(self, gm):
+    # replace this line with modification code for task 116 (torch._C._linalg.linalg_vector_norm)
+
+    # replace this line with modification code for task 117 (torch._C._linalg.linalg_norm)
+
+    # replace this line with modification code for task 118 (torch._C._nn.softplus)
+
+    # replace this line with modification code for task 119 (torch._C._nn.one_hot)
+
+    def _impl_unstable_to_stable_one_hot(self, gm):
         """
-        Convert torch._C._special.special_logit to torch.special.logit
+        Convert torch._C._nn.one_hot to torch.nn.functional.one_hot
         """
+        import torch.nn.functional as F
+
         issue_nodes = (
             node
             for node in gm.graph.nodes
             if node.op == "call_function"
             if hasattr(node.target, "__module__")
-            if node.target.__module__ == "torch._C._special"
+            if node.target.__module__ == "torch._C._nn"
             if hasattr(node.target, "__name__")
-            if node.target.__name__ == "special_logit"
+            if node.target.__name__ == "one_hot"
         )
         for node in issue_nodes:
-            node.target = torch.special.logit
+            node.target = F.one_hot
 
         # Recompile the graph
         gm.recompile()
 
         return gm
 
+    # replace this line with modification code for task 121 (torch._C._set_grad_enabled)
+
+    # replace this line with modification code for task 122 (torch._C._log_api_usage_once)
+
+    # replace this line with modification code for task 123 (torch._C._nn.pad)
+
+    # replace this line with modification code for task 125 (torch._C._nn.gelu)
+
+    # replace this line with modification code for task 126 (torch._C._nn.scaled_dot_product_attention)
+
+    # replace this line with modification code for task 127 (torch._C._nn.linear)
+
     def unstable_to_stable(self, gm):
         methods = (
             name

graph_net/torch/fx_graph_serialize_util.py

@@ -24,9 +24,17 @@ def serialize_graph_module_to_str(gm: torch.fx.GraphModule) -> str:
         (r"torch\._C\._fft\.fft_irfft\(", "torch.fft.irfft("),
         (r"torch\._C\._fft\.fft_rfft\(", "torch.fft.rfft("),
         (r"torch\._C\._fft\.fft_fftn\(", "torch.fft.fftn("),
-        (r"torch\._C\._nn\.one_hot\(", "torch.nn.functional.one_hot("),
         (r"torch\._C\._special\.special_logit\(", "torch.special.logit("),
-        # Add new rules to this list as needed
+        # replace this line with modification code for task 116 (torch._C._linalg.linalg_vector_norm)
+        # replace this line with modification code for task 117 (torch._C._linalg.linalg_norm)
+        # replace this line with modification code for task 118 (torch._C._nn.softplus)
+        (r"torch\._C\._nn\.one_hot\(", "torch.nn.functional.one_hot("),
+        # replace this line with modification code for task 121 (torch._C._set_grad_enabled)
+        # replace this line with modification code for task 122 (torch._C._log_api_usage_once)
+        # replace this line with modification code for task 123 (torch._C._nn.pad)
+        # replace this line with modification code for task 125 (torch._C._nn.gelu)
+        # replace this line with modification code for task 126 (torch._C._nn.scaled_dot_product_attention)
+        # replace this line with modification code for task 127 (torch._C._nn.linear)
     ]
     for pattern, repl in replacements:
         code = re.sub(pattern, repl, code)