Failed converting tensorflow ssd-resnet34 model to relay

Failed converting tensorflow ssd model to relay

Error log:

at /home/antoinette/tvm/src/relay/op/nn/pad.cc:129
  File "/home/antoinette/tvm/src/relay/analysis/type_solver.cc", line 624
TVMError: 
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
  Check failed: (false) is false: [23:11:05] /home/antoinette/tvm/src/relay/op/nn/pad.cc:129: 
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
  Check failed: (data->shape.size() == param->pad_width.size()) is false: There should be as many pad width pairs as shape dimensions but the shape has 0 dimensions and there are 4 pad width pairs.

The model can be found here:
https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/ssd-resnet34-fp32-inference.tar.gz
/ssd-resnet34-fp32-inference/pretrained_model/ssd_resnet34_fp32_bs1_pretrained_model.pb

The script to reproduce:

import tvm
from tvm import te
from tvm import relay

import numpy as np
import os.path

import tensorflow as tf

try:
    tf_compat_v1 = tf.compat.v1
except ImportError:
    tf_compat_v1 = tf

import tvm.relay.testing.tf as tf_testing

layout = "NCHW"

with tf_compat_v1.gfile.GFile("/home/antoinette/TLCBench/models/ssd-resnet34-fp32-inference/pretrained_model/ssd_resnet34_fp32_bs1_pretrained_model.pb", "rb") as f:
    graph_def = tf_compat_v1.GraphDef()
    graph_def.ParseFromString(f.read())
    graph = tf.import_graph_def(graph_def, name="")
    graph_def = tf_testing.ProcessGraphDefParam(graph_def)
    with tf_compat_v1.Session() as sess:
        graph_def = tf_testing.AddShapesToGraphDef(sess, out_node = ["v/Softmax", "v/stack"])

mod, params = relay.frontend.from_tensorflow(graph_def, layout=layout)

Can anyone help, please?