Jack6680 opened a new issue #20313:
URL: https://github.com/apache/incubator-mxnet/issues/20313


   ## Description
   I converted resnest50 model according to 
[19808](https://github.com/apache/incubator-mxnet/issues/19808). Now I try to 
compare results given by onnx model with onnxruntime. The difference between 
them is quite large. The output of numpy.testing.assert_allclose is
   ```
   Mismatched elements: 1000 / 1000 (100%)
   Max absolute difference: 0.32469702
   Max relative difference: 27.369648
   ```
   ### Error Message
   -
   ## To Reproduce
   
   
   ### Steps to reproduce
   
   model conversion
   
   ```
   from gluoncv import model_zoo
   import numpy as np
   import mxnet as mx
   model_name = 'resnest50'
   resnet50 = model_zoo.get_model(model_name, pretrained=True)
   print(model_name+' downloaded')
   resnet50.hybridize()
   print(model_name+' hybridized')
   input_shape=(1,3,224,224)
   data_array = np.random.uniform(0, 255, size=input_shape).astype("float32")
   mx_data = mx.nd.array(data_array)
   resnet50(mx_data)
   resnet50.export(model_name)
   print(model_name+' exported')
   from mxnet.contrib import onnx as onnx_mxnet
   onnx_file='./tp.onnx'
   params = './'+model_name+'-0000.params'
   sym='./'+model_name+'-symbol.json'
   onnx_mxnet.export_model(sym, params, [input_shape], np.float32, onnx_file)
   print('onnx export done')
   ```
   Model testing
   
   
   import onnxruntime as rt
   import numpy
   from onnxruntime.datasets import get_example
   
   sess = rt.InferenceSession('tp.onnx')
   input_name = sess.get_inputs()[0].name
   data_array = np.random.uniform(0, 1, size=input_shape).astype("float32")
   mx_data = mx.nd.array(data_array)
   onnx_data = mx_data.asnumpy()
   a = sess.run(None, {input_name: onnx_data})[0][0]
   b = resnet50(mx_data)[0].asnumpy()
   print(numpy.testing.assert_allclose(b,a))
   
   
   
   ## Environment
   
   
   <details>
   <summary>Environment Information</summary>
   
   ----------Python Info----------
   Version      : 3.7.10
   Compiler     : GCC 9.3.0
   Build        : ('default', 'Feb 20 2021 21:15:28')
   Arch         : ('64bit', '')
   ------------Pip Info-----------
   Version      : 20.0.2
   Directory    : /usr/lib/python3/dist-packages/pip
   ----------MXNet Info-----------
   Version      : 1.7.0
   Directory    : /home/local/.local/lib/python3.7/site-packages/mxnet
   Commit Hash   : 64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   64f737cdd59fe88d2c5b479f25d011c5156b6a8a
   Library      : 
['/home/local/.local/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
   ✖ TVM_OP
   ----------System Info----------
   Platform     : Linux-5.8.0-53-generic-x86_64-with-Ubuntu-20.04-focal
   system       : Linux
   node         : tva-pc-03
   release      : 5.8.0-53-generic
   version      : #60~20.04.1-Ubuntu SMP Thu May 6 09:52:46 UTC 2021
   ----------Hardware Info----------
   machine      : x86_64
   processor    : x86_64
   Architecture:                    x86_64
   CPU op-mode(s):                  32-bit, 64-bit
   Byte Order:                      Little Endian
   Address sizes:                   39 bits physical, 48 bits virtual
   CPU(s):                          12
   On-line CPU(s) list:             0-11
   Thread(s) per core:              2
   Core(s) per socket:              6
   Socket(s):                       1
   NUMA node(s):                    1
   Vendor ID:                       GenuineIntel
   CPU family:                      6
   Model:                           165
   Model name:                      Intel(R) Core(TM) i5-10600K CPU @ 4.10GHz
   Stepping:                        5
   CPU MHz:                         4399.823
   CPU max MHz:                     4800,0000
   CPU min MHz:                     800,0000
   BogoMIPS:                        8199.79
   Virtualization:                  VT-x
   L1d cache:                       192 KiB
   L1i cache:                       192 KiB
   L2 cache:                        1,5 MiB
   L3 cache:                        12 MiB
   NUMA node0 CPU(s):               0-11
   Vulnerability Itlb multihit:     KVM: Mitigation: VMX disabled
   Vulnerability L1tf:              Not affected
   Vulnerability Mds:               Not affected
   Vulnerability Meltdown:          Not affected
   Vulnerability Spec store bypass: Vulnerable
   Vulnerability Spectre v1:        Vulnerable: __user pointer sanitization and 
usercopy barriers only; no swapgs barriers
   Vulnerability Spectre v2:        Vulnerable, IBPB: disabled, STIBP: disabled
   Vulnerability Srbds:             Not affected
   Vulnerability Tsx async abort:   Not affected
   Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep 
mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse s
                                    se2 ss ht tm pbe syscall nx pdpe1gb rdtscp 
lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtop
                                    ology nonstop_tsc cpuid aperfmperf pni 
pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma c
                                    x16 xtpr pdcm pcid sse4_1 sse4_2 x2apic 
movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_
                                    lm abm 3dnowprefetch cpuid_fault epb 
invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi 
                                    flexpriority ept vpid ept_ad fsgsbase 
tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap c
                                    lflushopt intel_pt xsaveopt xsavec xgetbv1 
xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window
                                     hwp_epp pku ospke md_clear flush_l1d 
arch_capabilities
   ----------Network Test----------
   Setting timeout: 10
   Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0006 
sec, LOAD: 0.4579 sec.
   Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0247 sec, LOAD: 
0.1638 sec.
   Error open Gluon Tutorial(cn): https://zh.gluon.ai, <urlopen error [SSL: 
CERTIFICATE_VERIFY_FAILED] certificate verify failed: certificate has expired 
(_ssl.c:1091)>, DNS finished in 0.036272525787353516 sec.
   Timing for FashionMNIST: 
https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz,
 DNS: 0.1557 sec, LOAD: 1.3185 sec.
   Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.1053 sec, LOAD: 
0.6913 sec.
   Error open Conda: https://repo.continuum.io/pkgs/free/, HTTP Error 403: 
Forbidden, DNS finished in 0.00019788742065429688 sec.
   ----------Environment----------
   KMP_DUPLICATE_LIB_OK="True"
   KMP_INIT_AT_FORK="FALSE"
   
   
   </details>
   


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