Zheweiqiu opened a new issue #15892: retinaface model to onnx URL: https://github.com/apache/incubator-mxnet/issues/15892 Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential information to most of the technical issues and bug reports. For non-technical issues and feature requests, feel free to present the information in what you believe is the best form. For Q & A and discussion, please start a discussion thread at https://discuss.mxnet.io ## Description got error exporting retinaface model to onnx. But it worked when I tried insightface model. ## Environment info (Required) ----------Python Info---------- Version : 3.7.3 Compiler : GCC 7.3.0 Build : ('default', 'Mar 27 2019 22:11:17') Arch : ('64bit', '') ------------Pip Info----------- Version : 19.1.1 Directory : /home/qiuzhewei/anaconda3/lib/python3.7/site-packages/pip ----------MXNet Info----------- Version : 1.5.0 Directory : /home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet Commit Hash : 75a9e187d00a8b7ebc71412a02ed0e3ae489d91f Library : ['/home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet/libmxnet.so'] Build features: ✖ CUDA ✖ CUDNN ✖ NCCL ✖ CUDA_RTC ✖ TENSORRT ✔ CPU_SSE ✔ CPU_SSE2 ✔ CPU_SSE3 ✔ CPU_SSE4_1 ✔ CPU_SSE4_2 ✖ CPU_SSE4A ✔ CPU_AVX ✖ CPU_AVX2 ✖ OPENMP ✖ SSE ✔ F16C ✖ JEMALLOC ✖ BLAS_OPEN ✖ BLAS_ATLAS ✖ BLAS_MKL ✖ BLAS_APPLE ✔ LAPACK ✖ MKLDNN ✔ OPENCV ✖ CAFFE ✖ PROFILER ✔ DIST_KVSTORE ✖ CXX14 ✖ INT64_TENSOR_SIZE ✔ SIGNAL_HANDLER ✖ DEBUG ----------System Info---------- Platform : Linux-4.15.0-55-generic-x86_64-with-debian-stretch-sid system : Linux node : chaowei-SYS-7048GR-TR release : 4.15.0-55-generic version : #60~16.04.2-Ubuntu SMP Thu Jul 4 09:03:09 UTC 2019 ----------Hardware Info---------- machine : x86_64 processor : x86_64 Architecture: x86_64 CPU 运行模式： 32-bit, 64-bit Byte Order: Little Endian CPU(s): 12 On-line CPU(s) list: 0-11 每个核的线程数：1 每个座的核数： 6 Socket(s): 2 NUMA 节点： 2 厂商 ID： GenuineIntel CPU 系列： 6 型号： 79 Model name: Intel(R) Xeon(R) CPU E5-2603 v4 @ 1.70GHz 步进： 1 CPU MHz： 1316.511 CPU max MHz: 1700.0000 CPU min MHz: 1200.0000 BogoMIPS: 3403.17 虚拟化： VT-x L1d 缓存： 32K L1i 缓存： 32K L2 缓存： 256K L3 缓存： 15360K NUMA node0 CPU(s): 0-5 NUMA node1 CPU(s): 6-11 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a rdseed adx smap intel_pt xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm arat pln pts md_clear flush_l1d ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0016 sec, LOAD: 1.2854 sec. Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.3885 sec, LOAD: 1.5392 sec. Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.0077 sec, LOAD: 2.0701 sec. Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 9.3760 sec, LOAD: 0.8177 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0007 sec, LOAD: 0.9090 sec. Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.1989 sec, LOAD: 0.4561 sec. Package used (Python/R/Scala/Julia): I'm using Python 3.7 For Scala user, please provide: 1. Java version: (`java -version`) 2. Maven version: (`mvn -version`) 3. Scala runtime if applicable: (`scala -version`) For R user, please provide R `sessionInfo()`: ## Build info (Required if built from source) Compiler (gcc/clang/mingw/visual studio): MXNet commit hash: fatal: Not a git repository (or any of the parent directories): .git Build config: (Paste the content of config.mk, or the build command.) ## Error Message: [19:34:40] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.3.0. Attempting to upgrade... Traceback (most recent call last): File "mxnet2onnx.py", line 10, in <module> converted_model_path = onnx_mxnet.export_model(sym, params, [input_shape], np.float32, onnx_file) File "/home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet/contrib/onnx/mx2onnx/export_model.py", line 80, in export_model sym_obj, params_obj = load_module(sym, params) File "/home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet/contrib/onnx/mx2onnx/_export_helper.py", line 58, in load_module sym, arg_params, aux_params = mx.model.load_checkpoint(model_name, num_epochs) File "/home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet/model.py", line 450, in load_checkpoint symbol = sym.load('%s-symbol.json' % prefix) File "/home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet/symbol/symbol.py", line 2728, in load check_call(_LIB.MXSymbolCreateFromFile(c_str(fname), ctypes.byref(handle))) File "/home/qiuzhewei/anaconda3/lib/python3.7/site-packages/mxnet/base.py", line 253, in check_call raise MXNetError(py_str(_LIB.MXGetLastError())) mxnet.base.MXNetError: Cannot find argument 'mode', Possible Arguments: ---------------- axis : int, optional, default='-1' The axis along which to compute softmax. temperature : double or None, optional, default=None Temperature parameter in softmax dtype : {None, 'float16', 'float32', 'float64'},optional, default='None' DType of the output in case this can't be inferred. Defaults to the same as input's dtype if not defined (dtype=None). , in operator softmax(name="face_rpn_cls_prob_stride32", mode="channel") ## Minimum reproducible example (If you are using your own code, please provide a short script that reproduces the error. Otherwise, please provide link to the existing example.) I am using the code from http://mxnet.incubator.apache.org/versions/master/tutorials/onnx/export_mxnet_to_onnx.html ## Steps to reproduce (Paste the commands you ran that produced the error.) 1.Just run "python mxnet2onnx.py" where mxnet2onnx.py comes from the website above 2. ## What have you tried to solve it? 1. Tried to use another mxnet model(Resnet 50) to see if it works 2.
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