ylfdq1118 opened a new issue #13760: nd.slice does not return empty tensor when begin=end URL: https://github.com/apache/incubator-mxnet/issues/13760 ## Description For `mxnet.ndarray.slice(data, begin, end)`, if `begin=end`, it does not return an empty tensor. Instead, it returns a tensor with the same shape as `data`. ## Environment info (Required) ----------Python Info---------- Version : 3.5.2 Compiler : GCC 5.4.0 20160609 Build : ('default', 'Nov 23 2017 16:37:01') Arch : ('64bit', 'ELF') ------------Pip Info----------- Version : 18.1 Directory : /home/lingfan/.local/pythonenv/dgl/lib/python3.5/site-packages/pip ----------MXNet Info----------- Version : 1.5.0 Directory : /home/lingfan/.local/pythonenv/dgl/lib/python3.5/site-packages/mxnet Commit Hash : 812b06a4f29e84a068767b56afdbfd0e1408fcaf ----------System Info---------- Platform : Linux-4.4.0-1070-aws-x86_64-with-Ubuntu-16.04-xenial system : Linux node : ip-172-31-86-85 release : 4.4.0-1070-aws version : #80-Ubuntu SMP Thu Oct 4 13:56:07 UTC 2018 ----------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: 79 Model name: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz Stepping: 1 CPU MHz: 2701.332 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4600.18 Hypervisor vendor: Xen Virtualization type: full L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 46080K 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 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 Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0039 sec, LOAD: 0.0274 sec. Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.2937 sec, LOAD: 0.5235 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0060 sec, LOAD: 0.0966 sec. Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0047 sec, LOAD: 0.1268 sec. Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0015 sec, LOAD: 0.4607 sec. Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0451 sec, LOAD: 0.3926 sec. ## Minimum reproducible example ``` >>> import mxnet.ndarray as nd >>> a = nd.normal(shape=(4, 3)) >>> a [[ 2.2122064 0.7740038 1.0434405 ] [ 1.1839255 1.8917114 -1.2347414 ] [-1.771029 -0.45138445 0.57938355] [-1.856082 -1.9768796 -0.20801921]] <NDArray 4x3 @cpu(0)> >>> nd.slice(a, begin=0, end=0) [[ 2.2122064 0.7740038 1.0434405 ] [ 1.1839255 1.8917114 -1.2347414 ] [-1.771029 -0.45138445 0.57938355] [-1.856082 -1.9768796 -0.20801921]] <NDArray 4x3 @cpu(0)> >>> nd.slice(a, begin=2, end=2) [[-1.7710290e+00 -4.5138445e-01 5.7938355e-01] [-1.8560820e+00 -1.9768796e+00 -2.0801921e-01] [ 0.0000000e+00 0.0000000e+00 1.8637270e-43] [ 0.0000000e+00 3.8537848e-34 4.5786026e-41]] <NDArray 4x3 @cpu(0)> ``` @zheng-da @jermainewang
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