code: def _nannumel_sparse(x, **kwargs):
      """
      A reduction to count the number of elements in a sparse array, excluding nans.
      This will in general result in a dense matrix with an unpredictable fill value.
      So make it official and convert it to dense.
  
      https://github.com/dask/dask/issues/7169
      """
      n = _nannumel(x, **kwargs)
      # If all dimensions are contracted, this will just be a number, otherwise we
      # want to densify it.
      return n.todense() if hasattr(n, "todense") else n
  
imports: from __future__ import annotations
  import math
  import numpy
  from dask.array import chunk
  from dask.array.core import Array
  from dask.array.dispatch import concatenate_lookup, divide_lookup, einsum_lookup, empty_lookup, nannumel_lookup, numel_lookup, percentile_lookup, tensordot_lookup, to_cupy_dispatch, to_numpy_dispatch
  from dask.array.numpy_compat import divide
  from dask.array.numpy_compat import ma_divide
  from dask.array.percentile import _percentile
  from dask.backends import CreationDispatch, DaskBackendEntrypoint
label_desc: Use image node_id 14 for calling a global function with example usage: _nannumel_sparse(x) and returns: unknown