vitobellini opened a new issue, #21053:
URL: https://github.com/apache/incubator-mxnet/issues/21053
Hello,
I noticed that MXNet comes with a fixed state for Random Number Generator.
Performing random sampling I obtain the same sequences of numbers every time
I restart the kernel.
```
from mxnet import nd
for _ in range(3):
print(nd.random.uniform(0, 1).asscalar())
```
How to reproduce:
- Run the code
- Restart the kernel
- Repeat
I get every time the same sequence:
- 0.5488135
- 0.5928446
- 0.71518934
Note: I have not fixed the random seed.
Note: Even on different platform I get the same sequence of numbers.
Other libraries like numpy behave differently, I get different random
numbers every time I restart the kernel.
Is this an expected behaviour? If yes, what is the reason behind this?
Why this is a problem? Because as a user of MXNet if someone does not know
about this behaviour, then the risk is to end up in deterministic scenarios for
algorithms or evaluations, where this behaviour is not expected.
```
# curl --retry 10 -s
https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py |
python
----------Python Info----------
Version : 3.7.10
Compiler : GCC 5.4.0 20160609
Build : ('default', 'Dec 1 2021 23:14:01')
Arch : ('64bit', '')
------------Pip Info-----------
Version : 21.3.1
Directory : /usr/local/lib/python3.7/site-packages/pip
----------MXNet Info-----------
Version : 1.8.0
Directory : /usr/local/lib/python3.7/site-packages/mxnet
Num GPUs : 0
Commit Hash : e34390235c5b95fd37db1ffb0e211be93b72857a
----------System Info----------
Platform :
Linux-4.14.276-211.499.amzn2.x86_64-x86_64-with-debian-stretch-sid
system : Linux
node :
mxnet-1-8-cpu-py37-ub-ml-t3-medium-e1a0ef98c4048b78b93bd886cfb4
release : 4.14.276-211.499.amzn2.x86_64
version : #1 SMP Wed Apr 27 21:08:48 UTC 2022
----------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): 2
On-line CPU(s) list: 0,1
Thread(s) per core: 2
Core(s) per socket: 1
Socket(s): 1
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz
Stepping: 7
CPU MHz: 2500.004
BogoMIPS: 5000.00
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 32K
L1i cache: 32K
L2 cache: 1024K
L3 cache: 36608K
NUMA node0 CPU(s): 0,1
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 rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq 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 pti fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms
invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw
avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke
----------Network Test----------
Setting timeout: 10
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0017
sec, LOAD: 0.5205 sec.
Timing for GluonNLP GitHub: https://github.com/dmlc/gluon-nlp, DNS: 0.0016
sec, LOAD: 0.5493 sec.
Timing for GluonNLP: http://gluon-nlp.mxnet.io, DNS: 0.0414 sec, LOAD:
0.1936 sec.
Timing for D2L: http://d2l.ai, DNS: 0.0116 sec, LOAD: 0.0047 sec.
Timing for D2L (zh-cn): http://zh.d2l.ai, DNS: 0.0151 sec, LOAD: 0.2168 sec.
Timing for FashionMNIST:
https://repo.mxnet.io/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz,
DNS: 0.0361 sec, LOAD: 0.0466 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0022 sec, LOAD:
0.3712 sec.
Error open Conda: https://repo.continuum.io/pkgs/free/, HTTP Error 403:
Forbidden, DNS finished in 0.0018382072448730469 sec.
```
```
# python -c "from mxnet.runtime import Features; print(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]
```
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