access2rohit opened a new issue #17411: topk() takes more memory URL: https://github.com/apache/incubator-mxnet/issues/17411 ## Description topk() takes more memory than the supplied input. ### Error Message ``` Memory Error ``` ## To Reproduce ``` b = create_2d_tensor(rows=LARGE_X, columns=SMALL_Y) k = nd.topk(b, k=10, axis=0, dtype=np.int64) assert np.sum(k.asnumpy() == (LARGE_X - 1)) == SMALL_Y ind, val = mx.nd.topk(b, k=3, axis=0, dtype=np.int64, ret_typ="both", is_ascend=False) ``` ### Steps to reproduce Run the above script on MXNet built from master ## 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 ----------Python Info---------- Version : 3.6.4 Compiler : GCC 7.2.0 Build : ('default', 'Jan 16 2018 18:10:19') Arch : ('64bit', '') ------------Pip Info----------- Version : 18.0 Directory : /home/ubuntu/anaconda3/lib/python3.6/site-packages/pip ----------MXNet Info----------- /home/ubuntu/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters Version : 1.6.0 Directory : /home/ubuntu/incubator-mxnet/python/mxnet Num GPUs : 0 Hashtag not found. Not installed from pre-built package. ----------System Info---------- Platform : Linux-4.4.0-1098-aws-x86_64-with-debian-stretch-sid system : Linux node : ip-172-31-82-110 release : 4.4.0-1098-aws version : #109-Ubuntu SMP Fri Nov 8 09:30:18 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): 32 On-line CPU(s) list: 0-31 Thread(s) per core: 2 Core(s) per socket: 16 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz Stepping: 1 CPU MHz: 2699.984 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4600.06 Hypervisor vendor: Xen Virtualization type: full L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 46080K NUMA node0 CPU(s): 0-31 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 rep_good nopl xtopology nonstop_tsc aperfmperf pni pclmulqdq 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 kaiser fsgsbase bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx xsaveopt ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0022 sec, LOAD: 0.5111 sec. Timing for GluonNLP GitHub: https://github.com/dmlc/gluon-nlp, DNS: 0.0007 sec, LOAD: 0.3350 sec. Timing for GluonNLP: http://gluon-nlp.mxnet.io, DNS: 0.0973 sec, LOAD: 0.2595 sec. Timing for D2L: http://d2l.ai, DNS: 0.0936 sec, LOAD: 0.0044 sec. Timing for D2L (zh-cn): http://zh.d2l.ai, DNS: 0.0249 sec, LOAD: 0.1220 sec. Timing for FashionMNIST: https://repo.mxnet.io/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.1407 sec, LOAD: 0.3436 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0027 sec, LOAD: 0.0983 sec. Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0037 sec, LOAD: 0.0303 sec. ```
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