chi-hung opened a new issue #12971: DeformableConvolution throws an "not 
implemented" error
URL: https://github.com/apache/incubator-mxnet/issues/12971
 
 
   ## Description
   
   ```mxnet.symbol.contrib.DeformableConvolution``` throws this error: 
   
   MXNetError: [01:30:30] 
src/operator/contrib/./deformable_convolution-inl.h:352: not implemented
   
   ## Environment info (Required)
   
   A [docker 
container](https://github.com/chi-hung/DockerKeras/blob/master/Dockerfiles/MXNet/mxnet-cu9.2-dnn7.2-18.10.dockerfile)
 that contains:
   * Python 3.6.3 
   * Ubuntu 18.04
   * MXNet (for GPU) built from commit *d1234a4*
   * More details:
        ```
        ----------Python Info----------
        Version      : 3.6.3
        Compiler     : GCC 4.8.2 20140120 (Red Hat 4.8.2-15)
        Build        : ('default', 'May  4 2018 04:22:28')
        Arch         : ('64bit', '')
        ------------Pip Info-----------
        Version      : 9.0.3
        Directory    : 
/opt/intel/intelpython3/lib/python3.6/site-packages/pip-9.0.3-py3.6.egg/pip
        ----------MXNet Info-----------
        Version      : 1.3.1
        Directory    : 
/opt/intel/intelpython3/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet
        Hashtag not found. Not installed from pre-built package.
        ----------System Info----------
        Platform     : Linux-4.4.0-133-generic-x86_64-with-debian-buster-sid
        system       : Linux
        node         : 911f134d8cfd
        release      : 4.4.0-133-generic
        version      : #159-Ubuntu SMP Fri Aug 10 07:31:43 UTC 2018
        ----------Hardware Info----------
        machine      : x86_64
        processor    : x86_64
        Architecture:        x86_64
        CPU op-mode(s):      32-bit, 64-bit
        Byte Order:          Little Endian
        CPU(s):              32
        On-line CPU(s) list: 0-31
        Thread(s) per core:  2
        Core(s) per socket:  8
        Socket(s):           2
        NUMA node(s):        2
        Vendor ID:           GenuineIntel
        CPU family:          6
        Model:               79
        Model name:          Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz
        Stepping:            1
        CPU MHz:             3159.250
        CPU max MHz:         3600.0000
        CPU min MHz:         1200.0000
        BogoMIPS:            6400.54
        Virtualization:      VT-x
        L1d cache:           32K
        L1i cache:           32K
        L2 cache:            256K
        L3 cache:            25600K
        NUMA node0 CPU(s):   0-7,16-23
        NUMA node1 CPU(s):   8-15,24-31
        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 aperfmperf eagerfpu 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 epb 
invpcid_single intel_pt ibrs ibpb stibp kaiser tpr_shadow vnmi flexpriority ept 
vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdseed 
adx smap xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida 
arat pln pts
        ----------Network Test----------
        Setting timeout: 10
        Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 
0.0615 sec, LOAD: 1.1407 sec.
        Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.1471 sec, 
LOAD: 0.9320 sec.
        Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.0473 sec, 
LOAD: 0.7047 sec.
        Timing for FashionMNIST: 
https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz,
 DNS: 0.1199 sec, LOAD: 0.9396 sec.
        Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0229 sec, 
LOAD: 1.0230 sec.
        Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0132 
sec, LOAD: 0.9278 sec.
        ```
   ## Minimum reproducible example
   ```
   import mxnet
   mxnet.symbol.contrib.DeformableConvolution(num_filter=5,kernel=3,pad=1)  # 
throws error
   mxnet.ndarray.contrib.DeformableConvolution(num_filter=5,kernel=3,pad=1)  # 
throws error, too.
   ```
   

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