add operator HardSwishJitAutoFn export to onnx

timm/models/layers/activations_me.py

@@ -152,6 +152,13 @@ class HardSwishJitAutoFn(torch.autograd.Function):
         x = ctx.saved_tensors[0]
         return hard_swish_jit_bwd(x, grad_output)
 
+    @staticmethod
+    def symbolic(g, self):
+        input = g.op("Add", self, g.op('Constant', value_t=torch.tensor(3, dtype=torch.float)))
+        hardtanh_ = g.op("Clip", input, g.op('Constant', value_t=torch.tensor(0, dtype=torch.float)), g.op('Constant', value_t=torch.tensor(6, dtype=torch.float)))
+        hardtanh_ = g.op("Div", hardtanh_, g.op('Constant', value_t=torch.tensor(6, dtype=torch.float)))
+        return g.op("Mul", self, hardtanh_)
+
 
 def hard_swish_me(x, inplace=False):
     return HardSwishJitAutoFn.apply(x)