Hello Derek, Is this issue still open..? If open can I work on it?
On Mon, Oct 28, 2019 at 5:30 PM armnn-dev-request@lists.linaro.org wrote:
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Today's Topics:
- Re: ArmNN | ONXX model load issue (Derek Lamberti)
Message: 1 Date: Mon, 28 Oct 2019 10:31:11 +0000 From: Derek Lamberti derek.lamberti@linaro.org To: Rahul Chowdhury rahul.c@pathpartnertech.com Cc: Manjunath Kulkarni manjunath.kulkarni@pathpartnertech.com, armnn-dev@lists.linaro.org Subject: Re: [Armnn-dev] ArmNN | ONXX model load issue Message-ID: <CAPeFqV89WNV-sw20X0NB= tznsiMmNpw0bzj23HcgNSEmoFFmWg@mail.gmail.com> Content-Type: text/plain; charset="UTF-8"
Hi Rahul,
ArmNN doesn't support zero dimension tensors implicitly. Often this can be resolved by converting the tensor to a 1D tensor with 1 element. We have done this conversion automatically within the TfLite parser and this has worked for a particular use case we ran into. A similar solution might work for your use case too. This could be done within the ToTensorInfo() function in OnnxParser.cpp. If this resolves the issue for you I'd recommend issuing a pull request so that we can integrate it into master.
Hope that helps, ~Derek
On Thu, 22 Aug 2019 at 15:32, Rahul Chowdhury rahul.c@pathpartnertech.com wrote:
Hi,
We are using ArmNN to cross-compile a standalone C++ application on Linux that loads a standard onnx model. During the model loading, we see a
crash
with the below error output -
terminate called after throwing an instance of 'armnn::InvalidArgumentException' what(): Tensor numDimensions must be greater than 0
Initially we were on armnn master, and later we switched to tag v19.05,
but
the error was same for both.
Below is the code snippet to load the model - armnnOnnxParser::IOnnxParserPtr parser = armnnOnnxParser::IOnnxParser::Create(); std::cout << "\nmodel load start"; armnn::INetworkPtr network = parser->CreateNetworkFromBinaryFile("onnx_3DDFA.onnx"); std::cout << "\nmodel load end";
It crashes after printing "model load start" with the error message
printed
above.
A gdb backtrace is also provided below - (gdb) r Starting program: /home/root/Rahul/armnn_onnx/3DDFA_ArmNN_onnx/3ddfa_armnn_onnx [Thread debugging using libthread_db enabled] Using host libthread_db library "/lib/libthread_db.so.1".
terminate called after throwing an instance of 'armnn::InvalidArgumentException' what(): Tensor numDimensions must be greater than 0 model load start Program received signal SIGABRT, Aborted. __GI_raise (sig=sig@entry=6) at /usr/src/debug/glibc/2.26-r0/git/sysdeps/unix/sysv/linux/raise.c:51 51 } (gdb) bt #0 __GI_raise (sig=sig@entry=6) at /usr/src/debug/glibc/2.26-r0/git/sysdeps/unix/sysv/linux/raise.c:51 #1 0x0000ffffbe41df00 in __GI_abort () at /usr/src/debug/glibc/2.26-r0/git/stdlib/abort.c:90 #2 0x0000ffffbe6aa0f8 in __gnu_cxx::__verbose_terminate_handler() ()
from
/usr/lib/libstdc++.so.6 #3 0x0000ffffbe6a7afc in ?? () from /usr/lib/libstdc++.so.6 #4 0x0000ffffbe6a7b50 in std::terminate() () from
/usr/lib/libstdc++.so.6
#5 0x0000ffffbe6a7e20 in __cxa_throw () from /usr/lib/libstdc++.so.6 #6 0x0000ffffbefdad84 in armnn::TensorShape::TensorShape(unsigned int, unsigned int const*) () from
/home/root/Rahul/armnn_onnx/build/libarmnn.so
#7 0x0000ffffbe7e34d8 in armnnOnnxParser::(anonymous namespace)::ToTensorInfo(onnx::ValueInfoProto const&) [clone .constprop.493] () from /home/root/Rahul/armnn_onnx/build/libarmnnOnnxParser.so #8 0x0000ffffbe7e4080 in
armnnOnnxParser::OnnxParser::SetupInfo(google::protobuf::RepeatedPtrFieldonnx::ValueInfoProto
const*) () from /home/root/Rahul/armnn_onnx/build/libarmnnOnnxParser.so #9 0x0000ffffbe7e41ac in armnnOnnxParser::OnnxParser::LoadGraph() ()
from
/home/root/Rahul/armnn_onnx/build/libarmnnOnnxParser.so #10 0x0000ffffbe7e4760 in armnnOnnxParser::OnnxParser::CreateNetworkFromModel(onnx::ModelProto&) () from /home/root/Rahul/armnn_onnx/build/libarmnnOnnxParser.so #11 0x0000ffffbe7e49b0 in armnnOnnxParser::OnnxParser::CreateNetworkFromBinaryFile(char const*) () from /home/root/Rahul/armnn_onnx/build/libarmnnOnnxParser.so #12 0x0000000000402290 in main () (gdb)
Can someone point out if we are missing something out or doing something wrong? Any help or input is highly appreciated.
Regards, Rahul
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