Resnest50 to onnx. Different inference results

[Jack6680]

Description

I converted resnest50 model according to 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, 1, 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

Environment Information

----------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 : 64f737c
64f737c
64f737c
64f737c
64f737c
64f737c
64f737c
64f737c
64f737c
64f737c
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"

[github-actions]

Welcome to Apache MXNet (incubating)! We are on a mission to democratize AI, and we are glad that you are contributing to it by opening this issue.
Please make sure to include all the relevant context, and one of the @apache/mxnet-committers will be here shortly.
If you are interested in contributing to our project, let us know! Also, be sure to check out our guide on contributing to MXNet and our development guides wiki.