access2rohit opened a new issue #18258: URL: https://github.com/apache/incubator-mxnet/issues/18258
## Description I ran the following command to obtain individual operator performance w/ and w/o Large Tensor Support on both CPU and GPU ``` #CPU python incubator-mxnet/benchmark/opperf/opperf.py --output-format json --output-file mxnet_operator_benchmark_results.json #GPU python incubator-mxnet/benchmark/opperf/opperf.py --ctx gpu --output-format json --output-file mxnet_operator_benchmark_results.json ``` ### Error Message In both contexts(CPU and GPU) I get the following error log: ``` INFO:root:Begin Benchmark - BatchNorm INFO:root:Complete Benchmark - BatchNorm INFO:root:Begin Benchmark - Correlation INFO:root:Complete Benchmark - Correlation INFO:root:Begin Benchmark - Dropout INFO:root:Complete Benchmark - Dropout INFO:root:Begin Benchmark - Embedding INFO:root:Complete Benchmark - Embedding INFO:root:Begin Benchmark - FullyConnected INFO:root:Complete Benchmark - FullyConnected Traceback (most recent call last): File "benchmark/opperf/opperf.py", line 227, in <module> sys.exit(main()) File "benchmark/opperf/opperf.py", line 207, in main benchmark_results = run_all_mxnet_operator_benchmarks(ctx=ctx, dtype=dtype, profiler=profiler, int64_tensor=int64_tensor, warmup=warmup, runs=runs) File "benchmark/opperf/opperf.py", line 113, in run_all_mxnet_operator_benchmarks mxnet_operator_benchmark_results.append(run_nn_basic_operators_benchmarks(ctx=ctx, dtype=dtype, profiler=profiler, int64_tensor=int64_tensor, warmup=warmup, runs=runs)) File "/home/ubuntu/workspace/incubator-mxnet/benchmark/opperf/nd_operations/nn_basic_operators.py", line 143, in run_nn_basic_operators_benchmarks mx_nn_basic_op_results = run_op_benchmarks(mx_nn_basic_ops, dtype, ctx, profiler, int64_tensor, warmup, runs) File "/home/ubuntu/workspace/incubator-mxnet/benchmark/opperf/utils/benchmark_utils.py", line 210, in run_op_benchmarks warmup=warmup, runs=runs) File "/home/ubuntu/workspace/incubator-mxnet/benchmark/opperf/utils/benchmark_utils.py", line 177, in run_performance_test benchmark_result = _run_nd_operator_performance_test(op, inputs, run_backward, warmup, runs, kwargs_list, profiler) File "/home/ubuntu/workspace/incubator-mxnet/benchmark/opperf/utils/benchmark_utils.py", line 114, in _run_nd_operator_performance_test _, _ = benchmark_helper_func(op, warmup, **kwargs_list[0]) File "/home/ubuntu/workspace/incubator-mxnet/benchmark/opperf/utils/profiler_utils.py", line 200, in cpp_profile_it res = func(*args, **kwargs) File "/home/ubuntu/workspace/incubator-mxnet/benchmark/opperf/utils/ndarray_utils.py", line 60, in nd_forward_backward_and_profile nd.waitall() File "/home/ubuntu/workspace/incubator-mxnet/python/mxnet/ndarray/ndarray.py", line 211, in waitall check_call(_LIB.MXNDArrayWaitAll()) File "/home/ubuntu/workspace/incubator-mxnet/python/mxnet/base.py", line 246, in check_call raise get_last_ffi_error() mxnet.base.MXNetError: Traceback (most recent call last): File "../include/mxnet/././tensor_blob.h", line 198 ``` ## Environment We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below: ``` curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python # paste outputs here ``` ``` ubuntu@ip-172-31-0-156 ~/workspace/incubator-mxnet (master) $ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python ----------Python Info---------- Version : 3.6.6 Compiler : GCC 7.3.0 Build : ('default', 'Oct 9 2018 12:34:16') Arch : ('64bit', '') ------------Pip Info----------- Version : 19.3.1 Directory : /home/ubuntu/anaconda3/lib/python3.6/site-packages/pip ----------MXNet Info----------- Version : 2.0.0 Directory : /home/ubuntu/workspace/incubator-mxnet/python/mxnet Num GPUs : 8 Hashtag not found. Not installed from pre-built package. ----------System Info---------- Platform : Linux-5.3.0-1017-aws-x86_64-with-debian-buster-sid system : Linux node : ip-172-31-0-156 release : 5.3.0-1017-aws version : #18~18.04.1-Ubuntu SMP Wed Apr 8 15:12:16 UTC 2020 ----------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): 64 On-line CPU(s) list: 0-63 Thread(s) per core: 2 Core(s) per socket: 16 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz Stepping: 1 CPU MHz: 2714.244 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4600.17 Hypervisor vendor: Xen Virtualization type: full L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 46080K NUMA node0 CPU(s): 0-15,32-47 NUMA node1 CPU(s): 16-31,48-63 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq monitor est ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single pti fsgsbase bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx xsaveopt ida ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0024 sec, LOAD: 0.5204 sec. Timing for GluonNLP GitHub: https://github.com/dmlc/gluon-nlp, DNS: 0.0009 sec, LOAD: 0.4424 sec. Timing for GluonNLP: http://gluon-nlp.mxnet.io, DNS: 0.0858 sec, LOAD: 0.0844 sec. Timing for D2L: http://d2l.ai, DNS: 0.0102 sec, LOAD: 0.1282 sec. Timing for D2L (zh-cn): http://zh.d2l.ai, DNS: 0.0307 sec, LOAD: 0.1754 sec. Timing for FashionMNIST: https://repo.mxnet.io/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0756 sec, LOAD: 0.3423 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0031 sec, LOAD: 0.1128 sec. Error open Conda: https://repo.continuum.io/pkgs/free/, HTTP Error 403: Forbidden, DNS finished in 0.0049092769622802734 sec. ``` ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org