code: def test_quantile() -> None:
      r"""
      Tests if the quantiles of a single Gaussian and the quantiles of the mixture of two Gaussians
      identical to the first are equal. The quantiles of the single Gaussian are given by the
      Gaussian.quantile() method while the quantiles of the mixture from the Distribution.quantile() method.
      """
      mu = mx.nd.array(
          [[1, 10, 100, 1000, 10000], [-1, -10, -100, -1000, -10000]]
      )
      sigma = mx.nd.array([[1.0, 2.0, 3.0, 4.0, 5.0]] * 2)
  
      gau = Gaussian(mu, sigma)
  
      mixture_probs = mx.nd.broadcast_like(
          mx.nd.array([[0.5, 0.5]]).expand_dims(axis=0),
          mu,
          lhs_axes=(0, 1),
          rhs_axes=(0, 1),
      )
      mix = MixtureDistribution(
          mixture_probs=mixture_probs,
          components=[Gaussian(mu, sigma), Gaussian(mu, sigma)],
      )
  
      quantiles = mx.nd.array([0.1, 0.5, 0.9])
      gau_quantiles = gau.quantile(quantiles)
      mix_quantiles = mix.quantile(quantiles)
  
      relative_error = np.max(
          np.abs(gau_quantiles.asnumpy() / mix_quantiles.asnumpy() - 1)
      )
      assert relative_error < 1e-4
  
imports: import mxnet
  import numpy
  from gluonts.mx.distribution.gaussian import Gaussian
  from gluonts.mx.distribution.mixture import MixtureDistribution
  from gluonts.mx.distribution.uniform import Uniform
label_desc: Use image node_id 1 for calling a global function with example usage: test_quantile() without return types