OliverColeman opened a new issue #17218: mxnet.ndarray.from_numpy() throws error for float16 dtype URL: https://github.com/apache/incubator-mxnet/issues/17218 ## Description When trying to convert a numpy array with dtype `float16` I get the error below. I looked through the code and it looks like it should be supported, but I've tried the latest production release (mxnet-cu101==1.5.1.post0) and the latest pre-release (mxnet-cu101==1.6.0b20191029) with no success. ### Error Message ``` ValueError Traceback (most recent call last) <ipython-input-3-699ed656d29b> in <module> 3 4 a = np.zeros((1, 1), dtype=np.float16) ----> 5 b = mx.ndarray.from_numpy(a) /opt/conda/lib/python3.7/site-packages/mxnet/ndarray/ndarray.py in from_numpy(ndarray, zero_copy) 4268 raise ValueError("Only c-contiguous arrays are supported for zero-copy") 4269 ndarray.flags['WRITEABLE'] = False -> 4270 c_obj = _make_dl_managed_tensor(ndarray) 4271 handle = NDArrayHandle() 4272 check_call(_LIB.MXNDArrayFromDLPackEx(ctypes.byref(c_obj), True, ctypes.byref(handle))) /opt/conda/lib/python3.7/site-packages/mxnet/ndarray/ndarray.py in _make_dl_managed_tensor(array) 4257 def _make_dl_managed_tensor(array): 4258 c_obj = DLManagedTensor() -> 4259 c_obj.dl_tensor = _make_dl_tensor(array) 4260 c_obj.manager_ctx = _make_manager_ctx(array) 4261 c_obj.deleter = dl_managed_tensor_deleter /opt/conda/lib/python3.7/site-packages/mxnet/ndarray/ndarray.py in _make_dl_tensor(array) 4244 def _make_dl_tensor(array): 4245 if str(array.dtype) not in DLDataType.TYPE_MAP: -> 4246 raise ValueError(str(array.dtype) + " is not supported.") 4247 dl_tensor = DLTensor() 4248 dl_tensor.data = array.ctypes.data_as(ctypes.c_void_p) ValueError: float16 is not supported. ``` ## To Reproduce ``` import numpy as np import mxnet as mx a = np.zeros((1, 1), dtype=np.float16) b = mx.ndarray.from_numpy(a) ``` ## Environment ``` ----------Python Info---------- Version : 3.7.4 Compiler : GCC 7.3.0 Build : ('default', 'Aug 13 2019 20:35:49') Arch : ('64bit', '') ------------Pip Info----------- Version : 19.2.3 Directory : /opt/conda/lib/python3.7/site-packages/pip ----------MXNet Info----------- Version : 1.5.1 Directory : /opt/conda/lib/python3.7/site-packages/mxnet Num GPUs : 2 Commit Hash : c9818480680f84daa6e281a974ab263691302ba8 ----------System Info---------- Platform : Linux-4.15.0-55-generic-x86_64-with-debian-buster-sid system : Linux node : axl1 release : 4.15.0-55-generic version : #60-Ubuntu SMP Tue Jul 2 18:22:20 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): 4 On-line CPU(s) list: 0-3 Thread(s) per core: 1 Core(s) per socket: 4 Socket(s): 1 NUMA node(s): 1 Vendor ID: AuthenticAMD CPU family: 23 Model: 17 Model name: AMD Ryzen 3 2200G with Radeon Vega Graphics Stepping: 0 CPU MHz: 1439.174 CPU max MHz: 3500.0000 CPU min MHz: 1600.0000 BogoMIPS: 6986.88 Virtualization: AMD-V L1d cache: 32K L1i cache: 64K L2 cache: 512K L3 cache: 4096K NUMA node0 CPU(s): 0-3 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 mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx hw_pstate sme ssbd ibpb vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt sha_ni xsaveopt xsavec xgetbv1 xsaves clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif overflow_recov succor smca ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0203 sec, LOAD: 0.6295 sec. Timing for GluonNLP GitHub: https://github.com/dmlc/gluon-nlp, DNS: 0.0064 sec, LOAD: 0.5858 sec. Timing for GluonNLP: http://gluon-nlp.mxnet.io, DNS: 0.2835 sec, LOAD: 1.0021 sec. Timing for D2L: http://d2l.ai, DNS: 0.3187 sec, LOAD: 0.2566 sec. Timing for D2L (zh-cn): http://zh.d2l.ai, DNS: 0.0743 sec, LOAD: 0.3067 sec. Timing for FashionMNIST: https://repo.mxnet.io/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.2324 sec, LOAD: 0.7845 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.1998 sec, LOAD: 1.2013 sec. Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0397 sec, LOAD: 0.3711 sec. ```
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