[ONNXRuntimeError] Arcface model fails during ONNX runtime session run

Symptom

Arcface model from onnx model zoo doesn't run properly in ONNX runtime session run (tested in 1.0.0).

The following error message gets printed out:

2019-11-20 17:24:29.510729 [E:onnxruntime:, sequential_executor.cc:165 Execute] Non-zero status code returned while running BatchNormalization node. Name:'stage1_unit1_bn1' Status Message: Invalid input scale: NumDimensions() != 3
Traceback (most recent call last):
  File "test.py", line 21, in <module>
    ort_sess.run(None, ort_data)
  File "/Users/moreau/.pyenv/versions/3.7.0/lib/python3.7/site-packages/onnxruntime/capi/session.py", line 136, in run
    return self._sess.run(output_names, input_feed, run_options)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Non-zero status code returned while running BatchNormalization node. Name:'stage1_unit1_bn1' Status Message: Invalid input scale: NumDimensions() != 3

Reproducing the error

Environment:

• ubuntu: 18.04
• python: 3.7.0
• onnx: 1.6.0
• onnxruntime: 1.0.0
• numpy: 1.17.4

Dockerfile to reproduce error:

FROM ubuntu:18.04
RUN apt-get update
RUN apt-get install -y python3-dev python3-pip git vim
RUN pip3 install --upgrade pip

RUN pip3 install numpy==1.17.4
RUN pip3 install onnx==1.6.0
RUN pip3 install onnxruntime==1.0.0

Model:

• URL: https://s3.amazonaws.com/onnx-model-zoo/arcface/resnet100/resnet100.onnx
• SHA: 66074b860f905295aab5a842be57f37d

Minimal python script:

import numpy as np
import urllib.request
import onnxruntime
import os

MODEL_FILE = "resnet100.onnx"
URL = "https://s3.amazonaws.com/onnx-model-zoo/arcface/resnet100/resnet100.onnx"

# Download model file
if not os.path.exists(MODEL_FILE):
    urllib.request.urlretrieve(URL, MODEL_FILE)

# Create ONNX runtime session
ort_sess = onnxruntime.InferenceSession(MODEL_FILE)
# Print information on model input
for idx, inp in enumerate(ort_sess.get_inputs()):
    print("Input info: {}".format(inp))
# Init data
ort_data = {"data": np.random.rand(1,3,112,112).astype("float32")}
# Run
ort_sess.run(None, ort_data)

Start with the test.py reproduction and Dockerfile, then inspect the Arcface resnet100.onnx model at the onnxruntime.InferenceSession and run entry points. Compare the stage1_unit1_bn1 BatchNormalization node with the reported runtime error and verify the result by rerunning the minimal script; done means the model session runs without that error.