fixing call_module on subscripting into generator (#81258)

named_modules() return a generator, which is not subscriptable and causes node support query to fail
Pull Request resolved: #81258
Approved by: https://github.com/SherlockNoMad

Author: jjsjann123

test/test_fx_backends.py

@@ -130,6 +130,38 @@ def _generate_random_inputs(self, device, inputs_meta: List[Tuple[torch.Size, to
         return inputs
 
 
+    @skipCUDAIfRocm
+    @dtypes(torch.float32)
+    def test_nvfuser_call_module_backend(self, device, dtype):
+
+        class Model(torch.nn.Module):
+
+            def __init__(self):
+                super(Model, self).__init__()
+                self.bn = torch.nn.BatchNorm2d(3)
+                self.relu = torch.nn.ReLU()
+
+            def forward(self, inp):
+                o = self.bn(inp)
+                o = self.relu(o)
+                return o
+
+        inp = torch.randn(2, 3, 4, 5).to(dtype=dtype, device=device)
+        m = Model().to(dtype=dtype, device=device)
+
+        # note that the traced module here contains only `call_module` node,
+        # which isn't fused by nvfuser backend. But `nvfuser.compile` should run without error
+        traced = symbolic_trace(m)
+
+        nvfuser = NvFuserBackend()
+        compiled_module = nvfuser.compile(traced)
+
+        eager_result = m(inp)
+        nvfuser_result = compiled_module(inp)
+
+        torch.testing.assert_close(eager_result, nvfuser_result, rtol=1e-5, atol=1e-5)
+
+
     @skipCUDAIfRocm
     @dtypes(torch.float32)
     def test_nvfuser_backend(self, device, dtype):

torch/fx/passes/infra/partitioner.py

@@ -90,7 +90,7 @@ def __get_supported_nodes(self) -> NodeList:
         logging.debug("Collecting supported nodes...")
         supported_nodes = []
         for node in self.graph_module.graph.nodes:
-            if self.operator_support.is_node_supported(self.graph_module.named_modules(), node):
+            if self.operator_support.is_node_supported(dict(self.graph_module.named_modules()), node):
                 supported_nodes.append(node)
         return supported_nodes