Hi Ciyong, thanks for trying to reproduce: I used this one: https://github.com/awslabs/deeplearning-benchmark/blob/master/dawnbench/cifar10.py
Could you provide hardware and OS details? I will rerun and repost numbers in a few minutes. Pedro. On Wed, Jun 26, 2019 at 4:18 AM Chen, Ciyong <ciyong.c...@intel.com> wrote: > > Hi Pedro, > > I'm looking at this case, and using the script of > "incubator-mxnet/example/image-classification/train_cifar10.py" to get > the timing data, but seems there's not much difference between mxnet > 1.4.1.rc0 and 1.5.0.rc1 on C5.18xlarge. > > Not sure if there's any difference in the python script, can you point me the > link to get your script (cifar10.py)? > Or you can also have a try with MXNet's script (train_cifar10.py) and see the > performance. > > Here's the command I used to collect the time: > python train_cifar10.py --num-epoch=5 > > 1) 1.5.0.rc1 (4d9667121ae6fb643f2a02ab15e25231ed756cde) > real 9m4.880s > user 333m13.340s > sys 14m36.100s > > 2) 1.4.1.rc0 (1a7199691f5cbc6012bb53eecbf884bed5ae6590) > real 9m2.155s > user 329m37.092s > sys 16m8.668s > > -Ciyong > > > -----Original Message----- > From: Pedro Larroy [mailto:pedro.larroy.li...@gmail.com] > Sent: Wednesday, June 26, 2019 6:28 AM > To: dev@mxnet.incubator.apache.org > Cc: d...@mxnet.apache.org > Subject: Re: [VOTE] Release Apache MXNet (incubating) version 1.5.0.rc1 > > Hi these were my build flags and system info: > > > --- # CMake configuration > USE_CUDA: "OFF" # Build with CUDA support > USE_OLDCMAKECUDA: "OFF" # Build with old cmake cuda > USE_NCCL: "OFF" # Use NVidia NCCL with CUDA > USE_OPENCV: "ON" # Build with OpenCV support > USE_OPENMP: "ON" # Build with Openmp support > USE_CUDNN: "ON" # Build with cudnn support) # one could set CUDNN_ROOT for > search path > USE_SSE: "ON" # Build with x86 SSE instruction support IF NOT ARM > USE_F16C: "ON" # Build with x86 F16C instruction support) # autodetects > support if "ON" > USE_LAPACK: "ON" # Build with lapack support > USE_MKL_IF_AVAILABLE: "ON" # Use MKL if found > USE_MKLML_MKL: "ON" # Use MKLDNN variant of MKL (if MKL found) IF > USE_MKL_IF_AVAILABLE AND (NOT APPLE) > USE_MKLDNN: "ON" # Use MKLDNN variant of MKL (if MKL found) IF > USE_MKL_IF_AVAILABLE AND (NOT APPLE) > USE_OPERATOR_TUNING: "ON" # Enable auto-tuning of operators IF NOT MSVC > USE_GPERFTOOLS: "ON" # Build with GPerfTools support (if found) > USE_JEMALLOC: "ON" # Build with Jemalloc support > USE_PROFILER: "ON" # Build with Profiler support > USE_DIST_KVSTORE: "OFF" # Build with DIST_KVSTORE support > USE_PLUGINS_WARPCTC: "OFF" # Use WARPCTC Plugins > USE_PLUGIN_CAFFE: "OFF" # Use Caffe Plugin > USE_CPP_PACKAGE: "OFF" # Build C++ Package > USE_MXNET_LIB_NAMING: "ON" # Use MXNet library naming conventions. > USE_GPROF: "OFF" # Compile with gprof (profiling) flag > USE_CXX14_IF_AVAILABLE: "OFF" # Build with C++14 if the compiler supports it > USE_VTUNE: "OFF" # Enable use of Intel Amplifier XE (VTune)) # one could set > VTUNE_ROOT for search path > ENABLE_CUDA_RTC: "ON" # Build with CUDA runtime compilation support > BUILD_CPP_EXAMPLES: "ON" # Build cpp examples > INSTALL_EXAMPLES: "OFF" # Install the example source files. > USE_SIGNAL_HANDLER: "ON" # Print stack traces on segfaults. > USE_TENSORRT: "OFF" # Enable infeference optimization with TensorRT. > USE_ASAN: "OFF" # Enable Clang/GCC ASAN sanitizers. > ENABLE_TESTCOVERAGE: "OFF" # Enable compilation with test coverage metric > output > CMAKE_BUILD_TYPE: "Release" > CMAKE_CUDA_COMPILER_LAUNCHER: "ccache" > CMAKE_C_COMPILER_LAUNCHER: "ccache" > CMAKE_CXX_COMPILER_LAUNCHER: "ccache" > > commit 4d9667121ae6fb643f2a02ab15e25231ed756cde (HEAD, tag: 1.5.0.rc1, > upstream/v1.5.x) > commit 1a7199691f5cbc6012bb53eecbf884bed5ae6590 (HEAD, tag: 1.4.1.rc0, > upstream/v1.4.x) > > curl http://169.254.169.254/latest/meta-data/instance-type > c5d.18xlarge > > > Version : 3.6.7 > Compiler : GCC 8.2.0 > Build : ('default', 'Oct 22 2018 11:32:17') > Arch : ('64bit', 'ELF') > ------------Pip Info----------- > Version : 19.1.1 > Directory : /home/piotr/mxnet_1.5/py3_venv/lib/python3.6/site-packages/pip > ----------MXNet Info----------- > Version : 1.5.0 > Directory : /home/piotr/mxnet_1.5/python/mxnet > Hashtag not found. Not installed from pre-built package. > ----------System Info---------- > Platform : Linux-4.15.0-1035-aws-x86_64-with-Ubuntu-18.04-bionic > system : Linux > node : ip-172-31-63-171 > release : 4.15.0-1035-aws > version : #37-Ubuntu SMP Mon Mar 18 16:15:14 UTC 2019 > ----------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): 72 > On-line CPU(s) list: 0-71 > Thread(s) per core: 2 > Core(s) per socket: 18 > Socket(s): 2 > NUMA node(s): 2 > Vendor ID: GenuineIntel > CPU family: 6 > Model: 85 > Model name: Intel(R) Xeon(R) Platinum 8124M CPU @ 3.00GHz > Stepping: 4 > CPU MHz: 1326.446 > BogoMIPS: 6000.00 > Hypervisor vendor: KVM > Virtualization type: full > L1d cache: 32K > L1i cache: 32K > L2 cache: 1024K > L3 cache: 25344K > NUMA node0 CPU(s): 0-17,36-53 > NUMA node1 CPU(s): 18-35,54-71 > Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr > pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb > rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc cpuid > aperfmperf pni pclmulqdq monitor ssse3 fma cx16 pcid > sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c > rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase > tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq > rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec > xgetbv1 xsaves ida arat pku ospke ----------Network Test---------- > > ----------Python Info---------- > Version : 3.6.7 > Compiler : GCC 8.2.0 > Build : ('default', 'Oct 22 2018 11:32:17') > Arch : ('64bit', 'ELF') > ------------Pip Info----------- > Version : 19.1.1 > Directory : /home/piotr/mxnet_1.4/py3_venv/lib/python3.6/site-packages/pip > ----------MXNet Info----------- > Version : 1.4.1 > Directory : /home/piotr/mxnet_1.4/python/mxnet > Hashtag not found. Not installed from pre-built package. > ----------System Info---------- > Platform : Linux-4.15.0-1035-aws-x86_64-with-Ubuntu-18.04-bionic > system : Linux > node : ip-172-31-63-171 > release : 4.15.0-1035-aws > version : #37-Ubuntu SMP Mon Mar 18 16:15:14 UTC 2019 > ----------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): 72 > On-line CPU(s) list: 0-71 > Thread(s) per core: 2 > Core(s) per socket: 18 > Socket(s): 2 > NUMA node(s): 2 > Vendor ID: GenuineIntel > CPU family: 6 > Model: 85 > Model name: Intel(R) Xeon(R) Platinum 8124M CPU @ 3.00GHz > Stepping: 4 > CPU MHz: 1223.344 > BogoMIPS: 6000.00 > Hypervisor vendor: KVM > Virtualization type: full > L1d cache: 32K > L1i cache: 32K > L2 cache: 1024K > L3 cache: 25344K > NUMA node0 CPU(s): 0-17,36-53 > NUMA node1 CPU(s): 18-35,54-71 > Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr > pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb > rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc cpuid > aperfmperf pni pclmulqdq monitor ssse3 fma cx16 pcid > sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c > rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase > tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq > rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec > xgetbv1 xsaves ida arat pku ospke ----------Network Test---------- > > On Tue, Jun 25, 2019 at 2:35 PM Pedro Larroy <pedro.larroy.li...@gmail.com> > wrote: > > > > I did a training of cifar10 in CPU and seems there's some regressions > > in the range of 7% increase of training time against 1.4.1: > > > > (py3_venv) piotr@ip-172-31-63-171:0:~/deeplearning-benchmark/dawnbench > > (master)+$ time python cifar10.py --epochs 5 > > real 11m30.388s > > user 417m7.766s > > sys 16m57.315s > > > > VS 1.4.1: > > real 10m41.994s > > user 392m40.646s > > sys 12m30.601s > > > > > > On Thu, Jun 20, 2019 at 10:15 PM Lai Wei <roywei...@gmail.com> wrote: > > > > > > Hi Anirudh, > > > > > > Thanks for jumping into this quickly, I followed up on the issue. > > > > > > I was meant for sockeye developer/maintainers to help setup nightly > > > tests and raise issues early. > > > > > > Thanks! > > > > > > On Fri, Jun 21, 2019 at 10:10 AM Haibin Lin > > > <haibin.lin....@gmail.com> > > > wrote: > > > > > > > In GluonNLP we are testing with MXNET nightly build for each PR, > > > > and we did find some MXNet related issue caught by the CI. > > > > I recommend other toolkits also add integration tests with MXNet > > > > nightly. > > > > It helps identify issues early. > > > > > > > > Best, > > > > Haibin > > > > > > > > On Thu, Jun 20, 2019 at 18:52 Zhao, Patric <patric.z...@intel.com> > > > > wrote: > > > > > > > > > Thanks to raise the issue and we will take a look ASAP. > > > > > > > > > > The downstream cases is not in the MXNet CI so it's hard to > > > > > catch the potential bugs or performance degradation for MXNet > > > > > developers. > > > > > > > > > > In the future, I suggest adding the major downstream test cases, > > > > > like > > > > from > > > > > sockeye, GluonNLP, GLuonCV, DGL, Gluon-TS, into the nightly test. > > > > > If it's still too heavy, maybe testing it weekly or monthly :) > > > > > > > > > > Thanks, > > > > > > > > > > --Patric > > > > > > > > > > > -----Original Message----- > > > > > > From: Anirudh Subramanian [mailto:anirudh2...@gmail.com] > > > > > > Sent: Friday, June 21, 2019 9:31 AM > > > > > > To: dev@mxnet.incubator.apache.org > > > > > > Cc: d...@mxnet.apache.org > > > > > > Subject: Re: [VOTE] Release Apache MXNet (incubating) version > > > > > > 1.5.0.rc1 > > > > > > > > > > > > Hi Lai, > > > > > > > > > > > > I have opened an issue: > > > > > > https://github.com/apache/incubator-mxnet/issues/15297 > > > > > > I came to know about this issue only today and I have not been > > > > monitoring > > > > > > sockeye. > > > > > > I jumped onto this issue to make sure it wasn't caused by the > > > > > > dlpack > > > > > changes. > > > > > > Also, I don't think sockeye CI checks against master, it is > > > > > > using > > > > 1.4.1. > > > > > > > > > > > > Anirudh > > > > > > > > > > > > > > > > > > On Thu, Jun 20, 2019 at 6:17 PM Lai Wei <roywei...@gmail.com> wrote: > > > > > > > > > > > > > Hi, > > > > > > > > > > > > > > Could you share which test failed and what’s the crash? How > > > > > > > to reproduce it? > > > > > > > > > > > > > > I was able to install sockeye and run all tests passed. > > > > > > > Using python setup.py test > > > > > > > > > > > > > > I have tested both nightly pip package and 1.5.0.rc1 > > > > > > > > > > > > > > It would be great to create an issue with reproducible steps > > > > > > > and move the discussion there. > > > > > > > > > > > > > > Also I see sockeye nightly build[1] has been failing for > > > > > > > some time, > > > > if > > > > > > > it’s due to MXNet change, please raise this early so we can > > > > > > > track and solve it in time rather than block the release during > > > > > > > vote time. > > > > > > > > > > > > > > [1] https://travis-ci.org/awslabs/sockeye > > > > > > > > > > > > > > > > > > > > > On Fri, Jun 21, 2019 at 7:01 AM Anirudh Subramanian > > > > > > > <anirudh2...@gmail.com > > > > > > > > > > > > > > > wrote: > > > > > > > > > > > > > > > I was able to reproduce a crash with the commit > > > > > > > > 09202f7f261954383aa387144524d38f83f18d06 but not with the > > > > > > > > commit a862270beb2d796c1ba311183f7f4a766a18ad6c. > > > > > > > > > > > > > > > > Anirudh > > > > > > > > > > > > > > > > On Thu, Jun 20, 2019 at 3:53 PM Lai Wei > > > > > > > > <roywei...@gmail.com> > > > > wrote: > > > > > > > > > > > > > > > > > Hi Przemyslaw, > > > > > > > > > > > > > > > > > > Is there an issue with more details to track the problem? > > > > > > > > > > > > > > > > > > > > > > > > > > > On Fri, Jun 21, 2019 at 6:04 AM Przemysław Trędak > > > > > > > > > <ptre...@apache.org> > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > -1 > > > > > > > > > > > > > > > > > > > > There is a crash in sockeye unit test (python setup.py > > > > > > > > > > test) observed starting with nightly 1.5 build from > > > > > > > > > > 6/13 and still occuring in > > > > > > > > 1.5rc1. I > > > > > > > > > > don't yet have the exact commit that is responsible > > > > > > > > > > for it, but it is either > > > > > > > > > > a862270beb2d796c1ba311183f7f4a766a18ad6c (dlpack > > > > > > > > > > related) or > > > > > > > > > > 09202f7f261954383aa387144524d38f83f18d06 (cached op > > > > > > optimization). > > > > > > > > > > > > > > > > > > > > On 2019/06/20 06:36:22, Lai Wei <roywei...@gmail.com> wrote: > > > > > > > > > > > Dear MXNet community, > > > > > > > > > > > > > > > > > > > > > > This is the 3-day vote to release Apache MXNet > > > > > > > > > > > (incubating) version > > > > > > > > > > 1.5.0. > > > > > > > > > > > Voting on dev@ will start June 19, 23:59:59(PST) > > > > > > > > > > > and close > > > > on > > > > > > > June > > > > > > > > > 22, > > > > > > > > > > > 23:59:59. > > > > > > > > > > > > > > > > > > > > > > 1) Link to release notes: > > > > > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/MXNET/1.5.0+Release+No > > > > te > > > > > > > > s > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > 2) Link to release candidate: > > > > > > > > > > > > > > > > > > > > > > > > > > https://github.com/apache/incubator-mxnet/releases/tag/1.5.0.r > > > > > > > > > > > c1 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > 3) Link to source and signatures on apache dist server: > > > > > > > > > > > > > > > > > > > > > > > > > > https://dist.apache.org/repos/dist/dev/incubator/mxnet/1.5.0.r > > > > > > > > > > > c1/ > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Please remember to TEST first before voting accordingly: > > > > > > > > > > > > > > > > > > > > > > +1 = approve > > > > > > > > > > > +0 = no opinion > > > > > > > > > > > -1 = disapprove (provide reason) > > > > > > > > > > > -- > > > > > > > > > > > Best Regards > > > > > > > > > > > > > > > > > > > > > > Lai > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > Best Regards > > > > > > > > > > > > > > > > > > Lai > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > Best Regards > > > > > > > > > > > > > > Lai > > > > > > > > > > > > > > > > > > > -- > > > Best Regards > > > > > > Lai