Fitting a sparse matrix with at least 4,096 rows fails when using correlation as the distance metric

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Hi,

I'm encountering an error when attempting to run UMAP using correlation as the distance metric. I've reduced my code to a minimal reproducible example below.

```
import numpy as np
from scipy import sparse
import umap

np.random.seed(149)

X = sparse.rand(5000, 1000)
embed = umap.UMAP(metric='correlation').fit_transform(X)
```

This results in the following error:
```
TypingError Traceback (most recent call last)
in
1 X = sparse.rand(5000, 5000)
----> 2 embed = umap.UMAP(metric='correlation').fit_transform(X)

~/.conda/envs/py37/lib/python3.7/site-packages/umap/umap_.py in fit_transform(self, X, y)
2012 Embedding of the training data in low-dimensional space.
2013 """
-> 2014 self.fit(X, y)
2015 return self.embedding_
2016

~/.conda/envs/py37/lib/python3.7/site-packages/umap/umap_.py in fit(self, X, y)
1799 self.low_memory,
1800 use_pynndescent=True,
-> 1801 verbose=self.verbose,
1802 )
1803

~/.conda/envs/py37/lib/python3.7/site-packages/umap/umap_.py in nearest_neighbors(X, n_neighbors, metric, metric_kwds, angular, random_state, low_memory, use_pynndescent, verbose)
362 leaf_array=leaf_array,
363 n_iters=n_iters,
--> 364 verbose=verbose,
365 )
366 else:

~/.conda/envs/py37/lib/python3.7/site-packages/numba/core/dispatcher.py in _compile_for_args(self, *args, **kws)
413 e.patch_message(msg)
414
--> 415 error_rewrite(e, 'typing')
416 except errors.UnsupportedError as e:
417 # Something unsupported is present in the user code, add help info

~/.conda/envs/py37/lib/python3.7/site-packages/numba/core/dispatcher.py in error_rewrite(e, issue_type)
356 raise e
357 else:
--> 358 reraise(type(e), e, None)
359
360 argtypes = []

~/.conda/envs/py37/lib/python3.7/site-packages/numba/core/utils.py in reraise(tp, value, tb)
78 value = tp()
79 if value.__traceback__ is not tb:
---> 80 raise value.with_traceback(tb)
81 raise value
82

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Internal error at .
missing a required argument: 'n_features'
During: resolving callee type: type(CPUDispatcher())
During: typing of call at /home/mstone/.conda/envs/py37/lib/python3.7/site-packages/umap/sparse_nndescent.py (235)

Enable logging at debug level for details.

File ".conda/envs/py37/lib/python3.7/site-packages/umap/sparse_nndescent.py", line 235:
def sparse_nn_descent(

d = sparse_dist(from_inds, from_data, to_inds, to_data)
^
```

The error does not appear when using the default Euclidean metric, nor when providing a dense numpy matrix.

```
# Both work OK
embed = umap.UMAP().fit_transform(X)
embed = umap.UMAP(metric='correlation').fit_transform(X.toarray())
```

The error appears to start occurring when the matrix has at least 4,096 rows, and is unaffected by the number of features.

```
# Works OK
X = sparse.rand(4095, 1000)
embed = umap.UMAP(metric='correlation').fit_transform(X)

# Error
X = sparse.rand(4096, 1000)
embed = umap.UMAP(metric='correlation').fit_transform(X)
```

Is there anything special about exceeding 2^12 rows that might be causing this?

Thanks!

Start with sparse_nndescent.py around line 235, where sparse_nn_descent calls the sparse correlation distance, and reproduce the failure with the provided 4095-row and 4096-row examples. Confirm that correlation distance works for sparse inputs at 4096 or more rows while Euclidean sparse inputs and dense correlation inputs continue to work.

Written by the indexing model from the issue text.