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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/01/06 02:35:24 UTC
[GitHub] [incubator-mxnet] OliverColeman opened a new issue #17218:
mxnet.ndarray.from_numpy() throws error for float16 dtype
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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[GitHub] [incubator-mxnet] yajiedesign commented on issue #17218:
mxnet.ndarray.from_numpy() throws error for float16 dtype
Posted by GitBox <gi...@apache.org>.
yajiedesign commented on issue #17218: mxnet.ndarray.from_numpy() throws error for float16 dtype
URL: https://github.com/apache/incubator-mxnet/issues/17218#issuecomment-571454004
@wkcn hi.now the old windows build system has been borken.We will move the night release to S3, which is currently in progress and will take some time.
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[GitHub] [incubator-mxnet] OliverColeman commented on issue #17218:
mxnet.ndarray.from_numpy() throws error for float16 dtype
Posted by GitBox <gi...@apache.org>.
OliverColeman commented on issue #17218: mxnet.ndarray.from_numpy() throws error for float16 dtype
URL: https://github.com/apache/incubator-mxnet/issues/17218#issuecomment-571365444
That got it, thanks :)
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[GitHub] [incubator-mxnet] wkcn commented on issue #17218:
mxnet.ndarray.from_numpy() throws error for float16 dtype
Posted by GitBox <gi...@apache.org>.
wkcn commented on issue #17218: mxnet.ndarray.from_numpy() throws error for float16 dtype
URL: https://github.com/apache/incubator-mxnet/issues/17218#issuecomment-571051410
The bug has been fixed in the PR https://github.com/apache/incubator-mxnet/pull/16234 on Nov. 22, 2019.
However, the version of the nightly-build mxnet-cu101mkl is 20191006, and the version of the nightly-build mxnet-cu101 is 20191122.
MXNet installed by `pip install mxnet-cu101 --pre` works.
Hi @yajiedesign , could you please help update these nightly-build packages? Thanks a lot : )
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[GitHub] [incubator-mxnet] wkcn commented on issue #17218:
mxnet.ndarray.from_numpy() throws error for float16 dtype
Posted by GitBox <gi...@apache.org>.
wkcn commented on issue #17218: mxnet.ndarray.from_numpy() throws error for float16 dtype
URL: https://github.com/apache/incubator-mxnet/issues/17218#issuecomment-571619498
@yajiedesign Thank you! It seems that the build system for Linux CUDA10.1 has been broken too.
The version of nightly-built MXNet CUDA10.1 Linux is built on 20191122.
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[GitHub] [incubator-mxnet] wkcn commented on issue #17218:
mxnet.ndarray.from_numpy() throws error for float16 dtype
Posted by GitBox <gi...@apache.org>.
wkcn commented on issue #17218: mxnet.ndarray.from_numpy() throws error for float16 dtype
URL: https://github.com/apache/incubator-mxnet/issues/17218#issuecomment-571011395
Thank you for the report: ) I will check it.
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