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My model is onnx format generated by pytorch and I try to convert it to bin and xml, but it show the error "output array is read-only".
I see that other people on the Internet having this problem is about numpy's version, however, it seems not work for me.
I degrade the version numpy from 1.16.2 to 1.15.0, still doesn't work.
Any suggestion?
'''
File "C:\Intel\computer_vision_sdk_2018.5.456\deployment_tools\model_optimizer\mo\main.py", line 325, in main
return driver(argv)
File "C:\Intel\computer_vision_sdk_2018.5.456\deployment_tools\model_optimizer\mo\main.py", line 302, in driver
mean_scale_values=mean_scale)
File "C:\Intel\computer_vision_sdk_2018.5.456\deployment_tools\model_optimizer\mo\pipeline\onnx.py", line 165, in driver
fuse_linear_ops(graph)
File "C:\Intel\computer_vision_sdk_2018.5.456\deployment_tools\model_optimizer\mo\middle\passes\fusing\fuse_linear_ops.py", line 258, in fuse_linear_ops
is_fused = _fuse_add(graph, node, fuse_nodes)
File "C:\Intel\computer_vision_sdk_2018.5.456\deployment_tools\model_optimizer\mo\middle\passes\fusing\fuse_linear_ops.py", line 212, in _fuse_add
fuse_node.in_node(2).value += value
ValueError: output array is read-only
'''
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Dear Anthony,
This is indeed strange.
I have messaged you so that you can send me your onnx model privately.
Thanks for using OpenVino !
Shubha
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Hi, Shubha R.:
Thank you for your help.
I have already emailed you to "idz.admin@intel.com" or this is just a Forums Notification, because I receive any message in my Intel account.
Do I miss something?
Sorry for my late reply!
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Dear Anthony I did not receive anything from you. I have once again sent you a PM message. Just kindly reply to it and attach your model as a zip file.
Thanks for using OpenVino !
Shubha
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Dearest Anthony,
Thank you for sending me your zipped up model over PM.
I've got good news and bad news. The bad news is that I reproduced your problem on OpenVino version computer_vision_sdk_2018.5.456 (commonly known as R5.1), so you really did see a bug ! The good news is that it's been fixed in the latest OpenVino Release which dropped today (2019 R1).
Thanks for using OpenVino !
Shubha
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Hi Shubha R.,
Could you explain in more detail about this bug? I am just curious.
Because I comment out Line 224 to 260 in use_linear_ops.py and it work.
Thank you!
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Dear Anthony,
So I performed a "diff" between the 5.1 version of fuse_linear_ops.py and the latest 2019 R1 version. What I noticed is that there is a slight redesign of the _fuse_mul, _fuse_add and fuse_linear_ops methods:
Version 2019 R1 method signature:
def _fuse_mul(graph: Graph, node: Node, fuse_nodes: list, backward: bool = True):
Version 5.1 method signature:
def _fuse_mul(graph: nx.MultiDiGraph, node: Node, fuse_nodes: list, backward: bool = True):
The main difference is the first argument. So in all three methods 2019 R1 uses Graph rather than networkx.MultiDiGraph.
Looking through this file there are other minor changes also. I encourage you to do a "diff" yourself and see what the changes in this file are, after all OpenVino is open source !
Thanks for using OpenVino !
Shubha

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