code: def __init__(self, rate, *, validate_args=None):
      super().__init__(
          rate, is_sparse=True, validate_args=validate_args
      )
  
imports: import math
  from math import pi
  import numpy
  import pytest
  import scipy.stats
  import pyro.distributions
  from pyro.distributions.testing.naive_dirichlet import NaiveBeta, NaiveDirichlet
  from pyro.distributions.testing.rejection_exponential import RejectionExponential
  from pyro.distributions.testing.rejection_gamma import ShapeAugmentedBeta, ShapeAugmentedDirichlet, ShapeAugmentedGamma
  from tests.distributions.dist_fixture import Fixture
label_desc: Use image node_id 1 to create a new SparsePoisson object from inherited base classes: dist with example: obj = SparsePoisson(rate)