pnnx add missing Tensor.to pattern (#4908)

tools/pnnx/src/pass_level2/Tensor_to.cpp

@@ -55,12 +55,15 @@ pnnx.Output             output      1 0 out
 
         op->params["copy"] = captured_params.at("copy");
 
-        if (captured_params.at("memory_format").i == 0)
-            op->params["memory_format"] = "torch.contiguous_format";
-        if (captured_params.at("memory_format").i == 1)
-            op->params["memory_format"] = "torch.preserve_format";
-        if (captured_params.at("memory_format").i == 2)
-            op->params["memory_format"] = "torch.channels_last";
+        if (captured_params.at("memory_format").type == 2)
+        {
+            if (captured_params.at("memory_format").i == 0)
+                op->params["memory_format"] = "torch.contiguous_format";
+            if (captured_params.at("memory_format").i == 1)
+                op->params["memory_format"] = "torch.preserve_format";
+            if (captured_params.at("memory_format").i == 2)
+                op->params["memory_format"] = "torch.channels_last";
+        }
     }
 };
 
@@ -83,7 +86,29 @@ pnnx.Output             output      1 0 out
     }
 };
 
+class Tensor_to_2 : public Tensor_to
+{
+public:
+    const char* match_pattern_graph() const
+    {
+        return R"PNNXIR(7767517
+10 9
+pnnx.Input              input_0     0 1 input
+prim::Constant          op_0        0 1 dtype value=%dtype
+prim::Constant          op_1        0 1 layout value=*
+prim::Constant          op_2        0 1 device value=*
+prim::Constant          op_3        0 1 pin_memory value=*
+prim::Constant          op_4        0 1 non_blocking value=*
+prim::Constant          op_5        0 1 copy value=%copy
+prim::Constant          op_6        0 1 memory_format value=%memory_format
+aten::to                op_7        8 1 input dtype layout device pin_memory non_blocking copy memory_format out
+pnnx.Output             output      1 0 out
+)PNNXIR";
+    }
+};
+
 REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(Tensor_to, 20)
 REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(Tensor_to_1, 20)
+REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(Tensor_to_2, 20)
 
 } // namespace pnnx

tools/pnnx/tests/test_Tensor_to.py

@@ -27,7 +27,8 @@ class Model(nn.Module):
         x = x.to(device='cpu', dtype=torch.int, copy=True)
         x = x + 1
         y = y - 2
-        return x, y
+        z = x.to(y.device)
+        return x, y, z
 
 def test():
     net = Model()