n_jobs>1 returns an error for sparse input about pynndescent HOT 5 CLOSED

nn = NNDescent(X, metric='cosine')
nn = NNDescent(X, metric='cosine', n_jobs=-1)

~/anaconda3/envs/sonic/lib/python3.7/site-packages/pynndescent/sparse_threaded.py in sparse_init_random(current_graph, inds, indptr, data, dist, n_neighbors, chunk_size, rng_state, parallel, seed_per_row)
     95 
     96     # run map functions
---> 97     for index, status in parallel(parallel_calls(current_graph_map, n_tasks)):
     98         if status is False:
     99             raise ValueError("Failed in random initialization")

~/anaconda3/envs/sonic/lib/python3.7/site-packages/joblib/parallel.py in __call__(self, iterable)
   1015 
   1016             with self._backend.retrieval_context():
-> 1017                 self.retrieve()
   1018             # Make sure that we get a last message telling us we are done
   1019             elapsed_time = time.time() - self._start_time

~/anaconda3/envs/sonic/lib/python3.7/site-packages/joblib/parallel.py in retrieve(self)
    907             try:
    908                 if getattr(self._backend, 'supports_timeout', False):
--> 909                     self._output.extend(job.get(timeout=self.timeout))
    910                 else:
    911                     self._output.extend(job.get())

~/anaconda3/envs/sonic/lib/python3.7/multiprocessing/pool.py in get(self, timeout)
    655             return self._value
    656         else:
--> 657             raise self._value
    658 
    659     def _set(self, i, obj):

~/anaconda3/envs/sonic/lib/python3.7/multiprocessing/pool.py in worker(inqueue, outqueue, initializer, initargs, maxtasks, wrap_exception)
    119         job, i, func, args, kwds = task
    120         try:
--> 121             result = (True, func(*args, **kwds))
    122         except Exception as e:
    123             if wrap_exception and func is not _helper_reraises_exception:

~/anaconda3/envs/sonic/lib/python3.7/site-packages/joblib/_parallel_backends.py in __call__(self, *args, **kwargs)
    606     def __call__(self, *args, **kwargs):
    607         try:
--> 608             return self.func(*args, **kwargs)
    609         except KeyboardInterrupt:
    610             # We capture the KeyboardInterrupt and reraise it as

~/anaconda3/envs/sonic/lib/python3.7/site-packages/joblib/parallel.py in __call__(self)
    254         with parallel_backend(self._backend, n_jobs=self._n_jobs):
    255             return [func(*args, **kwargs)
--> 256                     for func, args, kwargs in self.items]
    257 
    258     def __len__(self):

~/anaconda3/envs/sonic/lib/python3.7/site-packages/joblib/parallel.py in <listcomp>(.0)
    254         with parallel_backend(self._backend, n_jobs=self._n_jobs):
    255             return [func(*args, **kwargs)
--> 256                     for func, args, kwargs in self.items]
    257 
    258     def __len__(self):

~/anaconda3/envs/sonic/lib/python3.7/site-packages/pynndescent/sparse_threaded.py in current_graph_map(index)
     90                 rng_state_threads[index],
     91                 seed_per_row=seed_per_row,
---> 92                 sparse_dist=dist,
     93             ),
     94         )

~/anaconda3/envs/sonic/lib/python3.7/site-packages/numba/dispatcher.py in _compile_for_args(self, *args, **kws)
    399                 e.patch_message(msg)
    400 
--> 401             error_rewrite(e, 'typing')
    402         except errors.UnsupportedError as e:
    403             # Something unsupported is present in the user code, add help info

~/anaconda3/envs/sonic/lib/python3.7/site-packages/numba/dispatcher.py in error_rewrite(e, issue_type)
    342                 raise e
    343             else:
--> 344                 reraise(type(e), e, None)
    345 
    346         argtypes = []

~/anaconda3/envs/sonic/lib/python3.7/site-packages/numba/six.py in reraise(tp, value, tb)
    666             value = tp()
    667         if value.__traceback__ is not tb:
--> 668             raise value.with_traceback(tb)
    669         raise value
    670 

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function getitem>) with argument(s) of type(s): (Heap(array(int32, 2d, C), array(float32, 2d, C), array(uint8, 2d, C)), (Literal[int](0), int64, Literal[int](0)))
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    All templates rejected with literals.
In definition 7:
    All templates rejected without literals.
In definition 8:
    All templates rejected with literals.
In definition 9:
    All templates rejected without literals.
In definition 10:
    All templates rejected with literals.
In definition 11:
    All templates rejected without literals.
In definition 12:
    All templates rejected with literals.
In definition 13:
    All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of intrinsic-call at /home/dkobak/anaconda3/envs/sonic/lib/python3.7/site-packages/pynndescent/sparse_threaded.py (40)

File "../../../anaconda3/envs/sonic/lib/python3.7/site-packages/pynndescent/sparse_threaded.py", line 40:
def sparse_current_graph_map_jit(
    <source elided>
            seed(rng_state_local, i)
        if heap[0, i, 0] < 0.0:
        ^

This is not usually a problem with Numba itself but instead often caused by
the use of unsupported features or an issue in resolving types.

(sonic) dkobak@lisboa:~$ python
Python 3.7.7 (default, Mar 26 2020, 15:48:22) 
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import scipy
>>> from pynndescent import NNDescent
>>> import numpy as np
>>> X = scipy.sparse.csr_matrix(np.random.randn(1000,100)>1)
>>> X
<1000x100 sparse matrix of type '<class 'numpy.bool_'>'
	with 15906 stored elements in Compressed Sparse Row format>
>>> nn = NNDescent(X, metric='cosine')
/home/dkobak/anaconda3/envs/sonic/lib/python3.7/site-packages/pynndescent/sparse_nndescent.py:502: NumbaTypeSafetyWarning: unsafe cast from uint32 to int32. Precision may be lost.
  init_rp_tree(inds, indptr, data, dist, current_graph, leaf_array)
>>> nn = NNDescent(X, metric='cosine')
>>> nn = NNDescent(X, metric='cosine', n_jobs=-1)
corrupted size vs. prev_size
Aborted (core dumped)
(sonic) dkobak@lisboa:~$