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12 changes: 11 additions & 1 deletion python/tvm/relay/frontend/onnx.py
Original file line number Diff line number Diff line change
Expand Up @@ -868,6 +868,15 @@ class Equal(Elemwise):
"""
name = 'equal'


class Not(Elemwise):
""" Operator converter for Not.
"""
@classmethod
def _impl_v1(cls, inputs, attr, params):
return _op.logical_not(inputs[0])


# compatible operators that do NOT require any conversion.
_identity_list = []

Expand Down Expand Up @@ -983,7 +992,8 @@ def _get_convert_map(opset):
'Pad': Pad.get_converter(opset),
'Shape': Shape.get_converter(opset),
'Sign': Sign.get_converter(opset),
'Equal': Equal.get_converter(opset)
'Equal': Equal.get_converter(opset),
'Not': Not.get_converter(opset)
}


Expand Down
29 changes: 29 additions & 0 deletions tests/python/frontend/onnx/test_forward.py
Original file line number Diff line number Diff line change
Expand Up @@ -1130,6 +1130,34 @@ def Sign_x(x):
'Sign',
{})


def verify_not(indata, dtype):
x = indata.astype(dtype)
outdata = np.logical_not(x)

node = helper.make_node('Not', inputs=['in'], outputs=['out'],)

graph = helper.make_graph([node],
'not_test',
inputs=[helper.make_tensor_value_info("in", TensorProto.BOOL, list(x.shape))],
outputs=[helper.make_tensor_value_info("out", TensorProto.BOOL, list(outdata.shape))])

model = helper.make_model(graph, producer_name='not_test')

for target, ctx in ctx_list():
tvm_out = get_tvm_output(model, [x], target, ctx, outdata.shape)
tvm.testing.assert_allclose(outdata, tvm_out)


def test_not():
# 2d
verify_not(indata=(np.random.randn(3, 4) > 0), dtype=bool)
# 3d
verify_not(indata=(np.random.randn(3, 4, 5) > 0), dtype=bool)
# 4d
verify_not(indata=(np.random.randn(3, 4, 5, 6) > 0), dtype=bool)


if __name__ == '__main__':
test_flatten()
test_reshape()
Expand Down Expand Up @@ -1173,3 +1201,4 @@ def Sign_x(x):
test_inception()
test_densenet()
test_sign()
test_not()