Any suggestion on run RingNet with Python 3.6.8 and Windows 10?

[drrobincroft]

I have downloaded the source code and models of RingNet and tried days to make it work on Python 3.6.8 and Windows 10.
But it is constantly throwing bugs like follows
tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for operation Flamenetnormal/strided_slice_5: node Flamenetnormal/strided_slice_5 (defined at Python\Python36\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) was explicitly assigned to /device:GPU:* but available devices are [ /job:localhost/replica:0/task:0/device:CPU:0 ]. Make sure the device specification refers to a valid device.
and
tensorflow.python.framework.errors_impl.InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint.
Do you have any idea about it?

I already know it stuck here in demo.py.
...
def main(config, template_mesh):
sess = tf.Session()
model = RingNet_inference(config, sess=sess)
input_img, proc_param, img = preprocess_image(config.img_path)
vertices, flame_parameters = model.predict(np.expand_dims(input_img, axis=0), get_parameters=True)
cams = flame_parameters[0][:3]
...

[Fsajjad99]

I was running on python 2.7 but from my experience, this error was thrown because of version mismatch in tensorflow, cuda and cudnn libraries. Perhaps looking into those would be helpful

[XRarach]

Also tried porting this to python3 and failed, I would be very interested in the results of this article in comparison to Flame itself in terms of speed.