[BUG] HDBSCAN: metric='precomputed' results in AttributeError

[RichieHakim]

Describe the bug
Attempting to use the 'precomputed' option for cuml.cluster.HDBSCAN results in an empty AttributeError.

Steps/Code to reproduce bug

hdbscan = cuml.cluster.HDBSCAN(metric="precomputed").fit(distances.toarray())

Error received:

/media/rich/OS/Users/Richard/Linux_stuff_on_OS/conda_envs/envs/rapids-21.12/lib/python3.8/site-packages/cuml/internals/api_decorators.py in inner_with_setters(*args, **kwargs)
    407                                 target_val=target_val)
    408 
--> 409                 return func(*args, **kwargs)
    410 
    411         @wraps(func)

cuml/cluster/hdbscan.pyx in cuml.cluster.hdbscan.HDBSCAN.fit()

cuml/common/base.pyx in cuml.common.base.Base.__getattr__()

AttributeError: 

Expected behavior
The function should take in a distance matrix (square shaped. I'm using the output of a KNN run)

Environment details (please complete the following information):

• Environment location: [Bare-metal, Docker, Cloud(specify cloud provider)]
• Linux Distro/Architecture: [Ubuntu 20.04 amd64]
• GPU Model/Driver: [NVIDIA RTX 3090]
• CUDA: [11.0]
• Method of cuDF & cuML install: [Conda]

# packages in environment at /media/rich/OS/Users/Richard/Linux_stuff_on_OS/conda_envs/envs/rapids-21.12:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       1_gnu    conda-forge
abseil-cpp                20210324.2           h9c3ff4c_0    conda-forge
anytree                   2.8.0                    pypi_0    pypi
argon2-cffi               21.3.0                   pypi_0    pypi
argon2-cffi-bindings      21.2.0                   pypi_0    pypi
arrow-cpp                 5.0.0           py38h579a05f_22_cuda    conda-forge
arrow-cpp-proc            3.0.0                      cuda    conda-forge
asttokens                 2.0.5                    pypi_0    pypi
attrs                     21.4.0                   pypi_0    pypi
aws-c-cal                 0.5.11               h95a6274_0    conda-forge
aws-c-common              0.6.2                h7f98852_0    conda-forge
aws-c-event-stream        0.2.7               h3541f99_13    conda-forge
aws-c-io                  0.10.5               hfb6a706_0    conda-forge
aws-checksums             0.1.11               ha31a3da_7    conda-forge
aws-sdk-cpp               1.8.186              hb4091e7_3    conda-forge
backcall                  0.2.0                    pypi_0    pypi
bleach                    4.1.0                    pypi_0    pypi
bokeh                     2.4.2            py38h578d9bd_0    conda-forge
bzip2                     1.0.8                h7f98852_4    conda-forge
c-ares                    1.18.1               h7f98852_0    conda-forge
ca-certificates           2021.10.26           h06a4308_2  
cachetools                5.0.0              pyhd8ed1ab_0    conda-forge
cffi                      1.15.0                   pypi_0    pypi
click                     8.0.3            py38h578d9bd_1    conda-forge
cloudpickle               2.0.0              pyhd8ed1ab_0    conda-forge
colorama                  0.4.4                    pypi_0    pypi
cudatoolkit               11.0.221             h6bb024c_0    nvidia
cudf                      21.12.02        cuda_11_py38_g06540b9b37_0    rapidsai
cuml                      21.12.00        cuda11_py38_g04c4927f3_0    rapidsai
cupy                      9.6.0            py38h57017e2_0    conda-forge
cycler                    0.11.0                   pypi_0    pypi
cython                    0.29.26                  pypi_0    pypi
cytoolz                   0.11.2           py38h497a2fe_1    conda-forge
dask                      2021.11.2          pyhd8ed1ab_0    conda-forge
dask-core                 2021.11.2          pyhd8ed1ab_0    conda-forge
dask-cudf                 21.12.02        cuda_11_py38_g06540b9b37_0    rapidsai
debugpy                   1.5.1                    pypi_0    pypi
decorator                 5.1.1                    pypi_0    pypi
defusedxml                0.7.1                    pypi_0    pypi
distlib                   0.3.4                    pypi_0    pypi
distributed               2021.11.2        py38h578d9bd_0    conda-forge
dlpack                    0.5                  h9c3ff4c_0    conda-forge
entrypoints               0.3                      pypi_0    pypi
executing                 0.8.2                    pypi_0    pypi
faiss-proc                1.0.0                      cuda    rapidsai
fastavro                  1.4.9            py38h497a2fe_0    conda-forge
fastrlock                 0.8              py38h709712a_1    conda-forge
fonttools                 4.28.5                   pypi_0    pypi
freetype                  2.10.4               h0708190_1    conda-forge
fsspec                    2021.11.1          pyhd8ed1ab_0    conda-forge
future                    0.18.2                   pypi_0    pypi
gflags                    2.2.2             he1b5a44_1004    conda-forge
glog                      0.5.0                h48cff8f_0    conda-forge
grpc-cpp                  1.42.0               ha1441d3_1    conda-forge
h5py                      3.6.0                    pypi_0    pypi
h5py-wrapper              1.1.0                    pypi_0    pypi
hdfdict                   0.3.1                    pypi_0    pypi
heapdict                  1.0.1                      py_0    conda-forge
icu                       69.1                 h9c3ff4c_0    conda-forge
imageio                   2.13.5                   pypi_0    pypi
importlib-resources       5.4.0                    pypi_0    pypi
ipykernel                 6.6.1                    pypi_0    pypi
ipython                   7.31.0                   pypi_0    pypi
ipython-genutils          0.2.0                    pypi_0    pypi
ipywidgets                7.6.5                    pypi_0    pypi
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jinja2                    3.0.3              pyhd8ed1ab_0    conda-forge
joblib                    1.1.0              pyhd8ed1ab_0    conda-forge
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jpeg                      9d                   h36c2ea0_0    conda-forge
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jupyter                   1.0.0                    pypi_0    pypi
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jupyter-core              4.9.1                    pypi_0    pypi
jupyterlab-pygments       0.1.2                    pypi_0    pypi
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kiwisolver                1.3.2                    pypi_0    pypi
krb5                      1.19.2               hcc1bbae_3    conda-forge
lcms2                     2.12                 hddcbb42_0    conda-forge
ld_impl_linux-64          2.36.1               hea4e1c9_2    conda-forge
lerc                      3.0                  h9c3ff4c_0    conda-forge
libblas                   3.9.0           12_linux64_openblas    conda-forge
libbrotlicommon           1.0.9                h7f98852_6    conda-forge
libbrotlidec              1.0.9                h7f98852_6    conda-forge
libbrotlienc              1.0.9                h7f98852_6    conda-forge
libcblas                  3.9.0           12_linux64_openblas    conda-forge
libcudf                   21.12.02        cuda11_g06540b9b37_0    rapidsai
libcuml                   21.12.00        cuda11_g04c4927f3_0    rapidsai
libcumlprims              21.12.00        cuda11_g0a7f19f_0    nvidia
libcurl                   7.81.0               h2574ce0_0    conda-forge
libcusolver               11.3.2.107           hc875929_0    nvidia
libdeflate                1.8                  h7f98852_0    conda-forge
libedit                   3.1.20191231         he28a2e2_2    conda-forge
libev                     4.33                 h516909a_1    conda-forge
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libhwloc                  2.3.0                h5e5b7d1_1    conda-forge
libiconv                  1.16                 h516909a_0    conda-forge
liblapack                 3.9.0           12_linux64_openblas    conda-forge
libllvm11                 11.1.0               hf817b99_2    conda-forge
libnghttp2                1.43.0               h812cca2_1    conda-forge
libnsl                    2.0.0                h7f98852_0    conda-forge
libopenblas               0.3.18          pthreads_h8fe5266_0    conda-forge
libpng                    1.6.37               h21135ba_2    conda-forge
libprotobuf               3.19.2               h780b84a_0    conda-forge
librmm                    21.12.00        cuda11_g957ad04_0    rapidsai
libssh2                   1.10.0               ha56f1ee_2    conda-forge
libstdcxx-ng              11.2.0              he4da1e4_11    conda-forge
libthrift                 0.15.0               he6d91bd_1    conda-forge
libtiff                   4.3.0                h6f004c6_2    conda-forge
libutf8proc               2.7.0                h7f98852_0    conda-forge
libwebp-base              1.2.1                h7f98852_0    conda-forge
libxml2                   2.9.12               h885dcf4_1    conda-forge
libzlib                   1.2.11            h36c2ea0_1013    conda-forge
llvmlite                  0.37.0           py38h4630a5e_1    conda-forge
locket                    0.2.0                      py_2    conda-forge
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markupsafe                2.0.1            py38h497a2fe_1    conda-forge
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s2n                       1.0.10               h9b69904_0    conda-forge
scanimage-tiff-reader     1.4.1                    pypi_0    pypi
scikit-image              0.19.1                   pypi_0    pypi
scikit-learn              1.0.2                    pypi_0    pypi
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torch                     1.9.0+cu111              pypi_0    pypi
torchaudio                0.9.0                    pypi_0    pypi
torchvision               0.10.0+cu111             pypi_0    pypi
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Additional context

1. I don't it's relevant, but there also seems to be versioning incompatibilities with the hdbscan library. This is despite the fact that some of the methods in cuML's HDBSCAN require hdbscan. The incompatibility is between the combination of numba, numpy, and scikit-learn
2. Using metric = 'manhattan' seems to kill my kernel also

[cjnolet]

Thanks for opening an issue about this @RichieHakim. You are correct to notice that the bug is in the documentation- it should not state precomputed is an option for the metric argument because that feature is not yet supported. The only distance currently supported is 'euclidean' and we do plan to support other distances in the future. Since it's a duplicate of #4460, I'm going to close this issue and add a note to #4460 to also include only the euclidean metric is supported in the documentation for now. We have a pending item in #3879 to add support more distances.