[Relay][Frontend][ONNX] Add Sign and Equal operators to ONNX frontend (#3760)

* [Relay][Frontend][ONNX] Add Sign and Equal operators to ONNX frontend

* Dummy change to retrigger integration test

python/tvm/relay/frontend/onnx.py

@@ -850,6 +850,18 @@ class ConstantFill(OnnxOpConverter):
             shape = shape + attr.pop('extra_shape')
         return _op.full(inputs[0], shape)
 
+class Sign(OnnxOpConverter):
+    """ Operator converter for Sign.
+    """
+    @classmethod
+    def _impl_v1(cls, inputs, attr, params):
+        return _op.sign(inputs[0])
+
+class Equal(Elemwise):
+    """ Operator converter for Equal.
+    """
+    name = 'equal'
+
 # compatible operators that do NOT require any conversion.
 _identity_list = []
 
@@ -964,6 +976,8 @@ def _get_convert_map(opset):
         'Unsqueeze': Unsqueeze.get_converter(opset),
         'Pad': Pad.get_converter(opset),
         'Shape': Shape.get_converter(opset),
+        'Sign': Sign.get_converter(opset),
+        'Equal': Equal.get_converter(opset)
     }
 
 

tests/python/frontend/onnx/test_forward.py

@@ -962,6 +962,7 @@ def test_binary_ops():
     verify_binary_ops("Sum", x, y, x + y, broadcast=None)
     verify_binary_ops("Greater", x, y, x > y, broadcast=True)
     verify_binary_ops("Less", x, y, x < y, broadcast=True)
+    verify_binary_ops("Equal", x, y, x == y, broadcast=True)
 
 def test_single_ops():
     in_shape = (1, 2, 3, 3)
@@ -1116,6 +1117,15 @@ def test_inception():
 # def test_shufflenetv2():
 #     check_torch_conversion(torchvision.models.shufflenetv2, (1,3,224,224))
 
+def test_sign():
+    def Sign_x(x):
+        return np.sign(x)
+    _test_onnx_op_elementwise((3, 4, 5, 6),
+                              Sign_x,
+                              {},
+                              'float32',
+                              'Sign',
+                              {})
 
 if __name__ == '__main__':
     test_flatten()
@@ -1159,3 +1169,4 @@ if __name__ == '__main__':
     test_resnet()
     test_inception()
     test_densenet()
+    test_sign()