[Numpy] mxnet.np.dtype() falls back to official NumPy function numpy.vander()

[barry-jin]

Description

Calling mxnet.np.dtype() will fall back to official NumPy function numpy.vander() rather than numpy.dtype().

Error Message

>>> import numpy as _np
>>> from mxnet import np
>>> _np.dtype(np.float32)
dtype('float32')
>>> np.dtype(np.float32)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/ubuntu/.local/lib/python3.6/site-packages/mxnet/numpy/fallback.py", line 121, in fn
    return onp_obj(*args, **kwargs)
  File "<__array_function__ internals>", line 6, in vander
  File "/usr/local/lib/python3.6/dist-packages/numpy/lib/twodim_base.py", line 546, in vander
    x = asarray(x)
  File "/usr/local/lib/python3.6/dist-packages/numpy/core/_asarray.py", line 83, in asarray
    return array(a, dtype, copy=False, order=order)
ValueError: invalid __array_struct__

>>> from mxnet import np
>>> x = np.array([1, 2, 3, 5])
[17:27:08] ../src/storage/storage.cc:199: Using Pooled (Naive) StorageManager for CPU
>>> np.dtype(x, 3)
WARNING:root:np.vander is a fallback operator, which is actually using official numpy's implementation.
array([[ 1.,  1.,  1.],
       [ 4.,  2.,  1.],
       [ 9.,  3.,  1.],
       [25.,  5.,  1.]], dtype=float64)

To Reproduce

>>> from mxnet import np
>>> np.dtype(np.float32)

What have you tried to solve it?

Environment

We recommend using our script for collecting the diagnostic information with the following command
curl --retry 10 -s https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py | python3

Environment Information

cubator-mxnet/master/tools/diagnose.py | python3
----------Python Info----------
Version      : 3.6.9
Compiler     : GCC 8.4.0
Build        : ('default', 'Oct  8 2020 12:12:24')
Arch         : ('64bit', 'ELF')
------------Pip Info-----------
Version      : 20.2.3
Directory    : /usr/local/lib/python3.6/dist-packages/pip
----------MXNet Info-----------
Version      : 2.0.0
Directory    : /home/ubuntu/.local/lib/python3.6/site-packages/mxnet
Commit hash file "/home/ubuntu/.local/lib/python3.6/site-packages/mxnet/COMMIT_HASH" not found. Not installed from pre-built package or built from source.
Library      : ['/home/ubuntu/.local/lib/python3.6/site-packages/mxnet/libmxnet.so']
Build features:
✔ CUDA
✔ CUDNN
✖ NCCL
✖ TENSORRT
✖ CUTENSOR
✔ 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
✔ DIST_KVSTORE
✖ INT64_TENSOR_SIZE
✔ SIGNAL_HANDLER
✖ DEBUG
✖ TVM_OP
----------System Info----------
Platform     : Linux-5.4.0-1025-aws-x86_64-with-Ubuntu-18.04-bionic
system       : Linux
node         : ip-172-31-10-57
release      : 5.4.0-1025-aws
version      : #25~18.04.1-Ubuntu SMP Fri Sep 11 12:03:04 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):              8
On-line CPU(s) list: 0-7
Thread(s) per core:  2
Core(s) per socket:  4
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:             3177.532
BogoMIPS:            4999.99
Hypervisor vendor:   KVM
Virtualization type: full
L1d cache:           32K
L1i cache:           32K
L2 cache:            1024K
L3 cache:            36608K
NUMA node0 CPU(s):   0-7
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 aperfmperf 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 avx512_vnni
----------Network Test----------
Setting timeout: 10
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0020 sec, LOAD: 0.4750 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0520 sec, LOAD: 0.2822 sec.
Error open Gluon Tutorial(cn): https://zh.gluon.ai, <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)>, DNS finished in 0.11438822746276855 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0195 sec, LOAD: 0.1837 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0641 sec, LOAD: 0.2075 sec.
Error open Conda: https://repo.continuum.io/pkgs/free/, HTTP Error 403: Forbidden, DNS finished in 0.03410220146179199 sec.
----------Environment----------
KMP_DUPLICATE_LIB_OK="True"
KMP_INIT_AT_FORK="FALSE"

[barry-jin]

It looks like some other mxnet numpy operators in mxnet/numpy/fallback.py also fall back to official numpy.vander().

>>> from mxnet import np
>>> np.dtype([3.2, 2, 1])
array([[10.24,  3.2 ,  1.  ],
       [ 4.  ,  2.  ,  1.  ],
       [ 1.  ,  1.  ,  1.  ]])
>>> np.min_scalar_type([3.2, 2, 1])
array([[10.24,  3.2 ,  1.  ],
       [ 4.  ,  2.  ,  1.  ],
       [ 1.  ,  1.  ,  1.  ]])
>>> np.choose([3.2, 2, 1])
array([[10.24,  3.2 ,  1.  ],
       [ 4.  ,  2.  ,  1.  ],
       [ 1.  ,  1.  ,  1.  ]])
>>> np.roots([3.2, 2, 1])
array([[10.24,  3.2 ,  1.  ],
       [ 4.  ,  2.  ,  1.  ],
       [ 1.  ,  1.  ,  1.  ]])