code: def dense_shape_from_sparse(sparse, validate=True):
      if validate:
          _validate_sparse(sparse)
  
      return tuple(
          [
              np.max(sparse[axis]) + 2
              if axis in list(sparse.dtype.fields.keys())
              else 1
              for axis in SPARSE_AXES_FIELDS
          ]
      )
  
imports: from enum import Enum
  import numpy
  from numpy.random.mtrand import RandomState
  import scipy.sparse
  import centrosome.index
label_desc: Use image node_id 7 for calling a global function with example usage: dense_shape_from_sparse(sparse, validate) and returns: tuple