Cannot convert TensorFlow model when contains `argwhere` and `strided_slice` op

strided_slice op not work when there is an argwhere input pipeline, because the output shape of argwhere is dynamic. Is there a better solution to fix that?

Error Information

Check failed: ObjectTypeChecker::Check(ptr) == false: Expect Array[IntImm] but get Array

Traceback (most recent call last):
  File "test_forward.py", line 4733, in <module>
    test_where_strided_slice((6), "int32")
  File "test_forward.py", line 1846, in test_where_strided_slice
    compare_tf_with_tvm(np_data, "in_data:0", "output:0", no_gpu=True, mode='vm')
  File "test_forward.py", line 253, in compare_tf_with_tvm
    cuda_layout=cuda_layout,
  File "test_forward.py", line 133, in run_tvm_graph
    graph_def, layout=layout, shape=shape_dict, outputs=out_names
  File "/root/code/fork_tvm/tvm/python/tvm/relay/frontend/tensorflow.py", line 3633, in from_tensorflow
    mod, params = g.from_tensorflow(graph, layout, shape, outputs)
  File "/root/code/fork_tvm/tvm/python/tvm/relay/frontend/tensorflow.py", line 3039, in from_tensorflow
    func = self._get_relay_func(graph, layout=layout, shape=shape, outputs=outputs)
  File "/root/code/fork_tvm/tvm/python/tvm/relay/frontend/tensorflow.py", line 3003, in _get_relay_func
    self._backtrack_construct(node.name)
  File "/root/code/fork_tvm/tvm/python/tvm/relay/frontend/tensorflow.py", line 3563, in _backtrack_construct
    op = self._convert_operator(node.op, node.name, inputs, attr)
  File "/root/code/fork_tvm/tvm/python/tvm/relay/frontend/tensorflow.py", line 3405, in _convert_operator
    sym = convert_map[op_name](inputs, attrs, self._params, self._mod)
  File "/root/code/fork_tvm/tvm/python/tvm/relay/frontend/tensorflow.py", line 1725, in _impl
    out = _op.strided_slice(inputs[0], begin=begin, end=end, strides=stride)
  File "/root/code/fork_tvm/tvm/python/tvm/relay/op/transform.py", line 898, in strided_slice
    return _make.strided_slice(data, begin, end, strides, slice_mode)
  File "/root/code/fork_tvm/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 237, in __call__
    raise get_last_ffi_error()
tvm._ffi.base.TVMError: Traceback (most recent call last):
  [bt] (4) /root/code/fork_tvm/tvm/build/libtvm.so(TVMFuncCall+0x61) [0x7ff37abac3d1]
  [bt] (3) /root/code/fork_tvm/tvm/build/libtvm.so(void tvm::runtime::TypedPackedFunc<tvm::RelayExpr (tvm::RelayExpr, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::String)>::AssignTypedLambda<tvm::RelayExpr (*)(tvm::RelayExpr, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::String)>(tvm::RelayExpr (*)(tvm::RelayExpr, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::Array<tvm::Integer, void>, tvm::runtime::String))::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*) const+0x22a) [0x7ff37a75833a]
  [bt] (2) /root/code/fork_tvm/tvm/build/libtvm.so(tvm::runtime::TVMMovableArgValue_::operator tvm::runtime::Array<tvm::Integer, void><tvm::runtime::Array<tvm::Integer, void>, void>() const+0x6a) [0x7ff379f926ba]
  [bt] (1) /root/code/fork_tvm/tvm/build/libtvm.so(tvm::runtime::Array<tvm::Integer, void> tvm::runtime::TVMPODValue_::AsObjectRef<tvm::runtime::Array<tvm::Integer, void> >() const+0x4ab) [0x7ff379f9259b]
  [bt] (0) /root/code/fork_tvm/tvm/build/libtvm.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x61) [0x7ff379e1d9a1]
  File "/root/code/fork_tvm/tvm/include/tvm/runtime/packed_func.h", line 1405
TVMError: 
---------------------------------------------------------------
An internal invariant was violated during the execution of TVM.
Please read TVM's error reporting guidelines.
More details can be found here: https://discuss.tvm.ai/t/error-reporting/7793.
---------------------------------------------------------------
  Check failed: ObjectTypeChecker<TObjectRef>::Check(ptr) == false: Expect Array[IntImm] but get Array

Minimal code to reproduce

I added a test in test_forward.py

# tvm/tests/python/frontend/tensorflow/test_forward.py
#######################################################################
# StridedSlice
# ------------
def test_where_strided_slice(
        ip_shape,
        dtype):
    """ One iteration of a Stridedslice """

    tf.reset_default_graph()
    with tf.Graph().as_default():
        in_data = tf.placeholder(dtype, ip_shape, name="in_data")
        weight = tf.ones((10, 20))
        mask = tf.squeeze(tf.where(in_data), axis=1)
        data = tf.gather(weight, mask)
        data = tf.reshape(data, shape=(-1, 2, 10))
        tf.strided_slice(
            data,
            begin=(1, 0, 0),
            end=(0, 1, 0),
            strides=(1, 1, 1),
            begin_mask=4,
            end_mask=5,
            new_axis_mask=0,
            shrink_axis_mask=2,
            ellipsis_mask=0,
            name="output",
        )

        np_data = (np.random.uniform(size=ip_shape) * 10).astype(dtype)
        np_data[0:3] = 0
        print(np_data)

        compare_tf_with_tvm(np_data, "in_data:0", "output:0", no_gpu=True, mode='vm')