code: def _get_mask(X, value_to_mask):
      """Compute the boolean mask X == missing_values."""
      if value_to_mask == "NaN" or cp.isnan(value_to_mask):
          return cp.isnan(X)
      else:
          return X == value_to_mask
  
file_path: cuml/python/cuml/thirdparty_adapters/adapters.py
imports: from cupyx.scipy import sparse
  from scipy import sparse
  from scipy.sparse import csc_matrix
  from scipy.sparse import csc_matrix
  from cuml.internals.safe_imports import cpu_only_import_from
  from cupyx.scipy.sparse import csc_matrix
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals.global_settings import GlobalSettings
  from cuml.internals.input_utils import input_to_cupy_array, input_to_host_array
  from cuml.internals.safe_imports import gpu_only_import
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 5 for calling a global function with example usage: _get_mask(X, value_to_mask) and returns: cp, unknown