[Bug] ConstantOfShape as shape input failed when using "freeze_params=False" option

[MoebiusMeow]

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I simply used relay.frontend.from_onnx to import an ONNX model from PyTorch. The code works fine when freeze_params is set to True (default).

When I was trying to separate weights from other constants, the same issue as #11783 occurred.

Here is the traceback:

    mod, params = relay.frontend.from_onnx(graph_def, freeze_params=False)
  File "python/tvm/relay/frontend/onnx.py", line 5816, in from_onnx
    mod, params = g.from_onnx(graph, opset)
  File "python/tvm/relay/frontend/onnx.py", line 5486, in from_onnx
    self._construct_nodes(graph)
  File "python/tvm/relay/frontend/onnx.py", line 5598, in _construct_nodes
    op = self._convert_operator(op_name, inputs, attr, self.opset)
  File "python/tvm/relay/frontend/onnx.py", line 5709, in _convert_operator
    sym = convert_map[op_name](inputs, attrs, self._params)
  File "python/tvm/relay/frontend/onnx.py", line 2732, in _impl_v8
    shape = fold_constant(expand_shape(in_shape, shape))
  File "python/tvm/relay/frontend/onnx.py", line 2701, in expand_shape
    if in_dims < new_dims:
  File "python/tvm/tir/expr.py", line 185, in __bool__
    return self.__nonzero__()
  File "python/tvm/tir/expr.py", line 180, in __nonzero__
    "Cannot use and / or / not operator to Expr, hint: "
ValueError: Cannot use and / or / not operator to Expr, hint: use tvm.tir.all / tvm.tir.any instea

onnx.py:2701:

def expand_shape(in_shape, shape):
    """A function expands the shape when the rank is lower than that of the given
    intput. Also it replaces the extent of the shape with the corresponding extent
    of the intput when it is 1.
    """
    in_dims = infer_shape(in_shape)[0] 
    new_dims = infer_shape(shape)[0] 

The value "shape" in infer_shape is

free_var %onnx::ConstantOfShape_139: Tensor[(1), int64];
dyn.full(1, %onnx::ConstantOfShape_139, shape=None, dtype="int64")

And I got in_dims = 3 and new_dims = ?

It seems that the "freeze_params=False" prevented the input of "ConstantOfShape" op to be used in inferring shape. Well, it is actually reasonable considering that when I directly used ONNX infer_shapes, I also got float32[20,12,unk__0]

Environment

Both on TVM 0.9.0 branch and main branch. PyTorch 1.12.0. ONNX 1.12.0. A "ConstantOfShape" op following by an Expand op is needed to reproduce the error.