[ONNX] Add hardsigmoid symbolic in opset 9 pytorch#49649 (pytorch#54193)

Summary:
Fixes pytorch#49649
Adds support for torch.nn.Hardsigmoid operator in torch.onnx.export

Pull Request resolved: pytorch#54193

Reviewed By: anjali411

Differential Revision: D27522969

Pulled By: SplitInfinity

fbshipit-source-id: 33abcec578f4bc3cf5c3ee1c1bed7d94816bee96

Author: whiteking64

docs/source/onnx.rst

@@ -617,6 +617,7 @@ The following operators are supported:
 * glu
 * group_norm
 * gt
+* hardsigmoid
 * hardswish
 * hardtanh
 * im2col

test/onnx/test_pytorch_onnx_onnxruntime.py

@@ -972,6 +972,18 @@ def forward(self, x):
         x = torch.rand(3, 3).to(dtype=torch.float32)
         self.run_test(MyModel(), x)
 
+    def test_hardsigmoid(self):
+        model = torch.nn.Hardsigmoid()
+
+        x = torch.rand(3, 3).to(dtype=torch.float32)
+        self.run_test(model, x)
+
+        # corner cases
+        x = torch.tensor(3).to(dtype=torch.float32)
+        self.run_test(model, x)
+        x = torch.tensor(-3).to(dtype=torch.float32)
+        self.run_test(model, x)
+
     def test_clamp(self):
         class ClampModel(torch.nn.Module):
             def forward(self, x):

torch/onnx/symbolic_opset9.py

@@ -1866,6 +1866,12 @@ def hardswish(g, self):
     hardtanh_ = g.op("Div", hardtanh_, g.op('Constant', value_t=torch.tensor(6, dtype=torch.float)))
     return g.op("Mul", self, hardtanh_)
 
+
+@parse_args('v')
+def hardsigmoid(g, self):
+    return g.op('HardSigmoid', self, alpha_f=1 / 6)
+
+
 def alias(g, self):
     return self