MingkangW opened a new pull request, #15529:
URL: https://github.com/apache/tvm/pull/15529
The type of add op`s output is activation, it should annotate by
QAnnotateKind.ACTIVATION. If not, the graph will cast int32 into int8 directly
without quantized, when quantize resnet. It will product overflow error, and it
won`t prompt when infer the model. The resnet18_v1 test case is below.
before fixed
%703 = add(%701, %702) /* ty=Tensor[(1, 512, 7, 7), int32] */;
%704 = nn.relu(%703) /* ty=Tensor[(1, 512, 7, 7), int32] */;
%705 = cast(%704, dtype="int8") /* ty=Tensor[(1, 512, 7, 7), int8] */;
%706 = annotation.stop_fusion(%705) /* ty=Tensor[(1, 512, 7, 7), int8] */;
after fixed
%443 = add(%441, %442) /* ty=Tensor[(1, 512, 7, 7), int32] */;
%444 = nn.relu(%443) /* ty=Tensor[(1, 512, 7, 7), int32] */;
%445 = cast(%444, dtype="int64") /* ty=Tensor[(1, 512, 7, 7), int64] */;
%446 = fixed_point_multiply(%445, multiplier=1439683968, shift=-2) /*
ty=Tensor[(1, 512, 7, 7), int64] */;
%447 = clip(%446, a_min=-127f, a_max=127f) /* ty=Tensor[(1, 512, 7, 7),
int64] */;
%448 = cast(%447, dtype="int32") /* ty=Tensor[(1, 512, 7, 7), int32] */;
%449 = cast(%448, dtype="int8") /* ty=Tensor[(1, 512, 7, 7), int8] */;
%450 = annotation.stop_fusion(%449) /* ty=Tensor[(1, 512, 7, 7), int8] */;
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