[GitHub] [incubator-mxnet] kaivu1999 opened a new issue #15017: Issue in using nd.ones((3, 4), ctx=gpu()) , CUDA 10.1

[GitBox <gi...@apache.org>]

kaivu1999 opened a new issue #15017: Issue in using nd.ones((3, 4), ctx=gpu()) , CUDA 10.1
URL: https://github.com/apache/incubator-mxnet/issues/15017
 
 
   ## Description
   Not able to use ctx=gpu() in nd.ones()
   
   ## Environment info (Required)
   
   ```
   nvcc -V
   nvcc: NVIDIA (R) Cuda compiler driver
   Copyright (c) 2005-2019 NVIDIA Corporation
   Built on Wed_Apr_24_19:10:27_PDT_2019
   Cuda compilation tools, release 10.1, V10.1.168
   
   ```
   ```
   x = nd.ones((3,4), ctx=gpu())
   ```
   This leads to the following error
   ```
   [14:03:41] src/imperative/./imperative_utils.h:90: GPU support is disabled. Compile MXNet with USE_CUDA=1 to enable GPU support.
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File "/home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/ndarray/ndarray.py", line 2421, in ones
       return _internal._ones(shape=shape, ctx=ctx, dtype=dtype, **kwargs)
     File "<string>", line 34, in _ones
     File "/home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/_ctypes/ndarray.py", line 92, in _imperative_invoke
       ctypes.byref(out_stypes)))
     File "/home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/base.py", line 252, in check_call
       raise MXNetError(py_str(_LIB.MXGetLastError()))
   mxnet.base.MXNetError: [14:03:41] src/imperative/imperative.cc:79: Operator _ones is not implemented for GPU.
   
   Stack trace returned 10 entries:
   [bt] (0) /home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x23d55a) [0x7f85c9fb755a]
   [bt] (1) /home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x23dbc1) [0x7f85c9fb7bc1]
   [bt] (2) /home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/libmxnet.so(mxnet::Imperative::InvokeOp(mxnet::Context const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, mxnet::DispatchMode, mxnet::OpStatePtr)+0x9fb) [0x7f85cc9a8abb]
   [bt] (3) /home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/libmxnet.so(mxnet::Imperative::Invoke(mxnet::Context const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&)+0x38c) [0x7f85cc9a917c]
   [bt] (4) /home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x2b34989) [0x7f85cc8ae989]
   [bt] (5) /home/kaivalya/ntu/first/lib/python3.5/site-packages/mxnet/libmxnet.so(MXImperativeInvokeEx+0x6f) [0x7f85cc8aef7f]
   [bt] (6) /home/kaivalya/ntu/first/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(ffi_call_unix64+0x4c) [0x7f85e5a6fe20]
   [bt] (7) /home/kaivalya/ntu/first/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(ffi_call+0x2eb) [0x7f85e5a6f88b]
   [bt] (8) /home/kaivalya/ntu/first/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(_ctypes_callproc+0x49a) [0x7f85e5a6a01a]
   [bt] (9) /home/kaivalya/ntu/first/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(+0x9fcb) [0x7f85e5a5dfcb]
   ```
   
   Package used (Python/R/Scala/Julia):
   (I'm using ...)
   autopep8==1.4.4
   backcall==0.1.0
   certifi==2019.3.9
   chardet==3.0.4
   cycler==0.10.0
   decorator==4.4.0
   graphviz==0.8.4
   idna==2.8
   ipykernel==5.1.1
   ipython==7.5.0
   ipython-genutils==0.2.0
   jedi==0.13.3
   jupyter-client==5.2.4
   jupyter-core==4.4.0
   kiwisolver==1.1.0
   matplotlib==3.0.3
   mxnet==1.4.1
   mxnet-cu101==1.5.0b20190516
   numpy==1.14.6
   parso==0.4.0
   pexpect==4.7.0
   pickleshare==0.7.5
   prompt-toolkit==2.0.9
   ptyprocess==0.6.0
   pycodestyle==2.5.0
   Pygments==2.4.0
   pyparsing==2.4.0
   python-dateutil==2.8.0
   pyzmq==18.0.1
   requests==2.22.0
   six==1.12.0
   tornado==6.0.2
   traitlets==4.3.2
   urllib3==1.25.2
   wcwidth==0.1.7
   
   
   I am new to MXNet and CUDA can someone help me, please?

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