In python code, use some List[torch.Tensor] = [], then the mode convert from torch to onnx， show in graph using SequenceEmpty. And now, use code as follow in xmir/python/tvm/relay/frontend/onnx.py:
class SequenceEmpty(OnnxOpConverter): “”“Operator converter for sequence construction op.”"" @classmethod def _impl_v11(cls, inputs, attr, params):
Construct a tuple from input tensors.
const0 = _expr.const(0, dtype=“int64”)
return _expr.Tuple([])
However， error occur at"get_const_tuple", as follow:
def get_var(name, val, scan=False): checked_type = infer_type(val) if hasattr(checked_type, “type_annotation”): checked_type = checked_type.type_annotation if hasattr(checked_type, “checked_type”): checked_type = checked_type.checked_type shape = get_const_tuple(checked_type.shape)
I print the “val” and “checked_type” and all is show “()”. So，has anyone encountered a similar situation?