code: def test_inference_mixture_different_families(
      mixture_distribution: MixtureDistribution,
      mixture_distribution_output: MixtureDistributionOutput,
      epochs: int,
      serialize_fn,
  ) -> None:
      # First sample from mixture distribution and then confirm the MLE are close to true parameters
      num_samples = 10_000
      samples = mixture_distribution.sample(num_samples=num_samples)
      variate_dimensionality = (
          mixture_distribution.components[0].args[0].shape[0]
      )
      fitted_dist = fit_mixture_distribution(
          samples,
          mixture_distribution_output,
          variate_dimensionality,
          epochs=epochs,
      )
  
      assert np.allclose(
          fitted_dist.mixture_probs.asnumpy(),
          mixture_distribution.mixture_probs.asnumpy(),
          atol=1e-1,
      ), f"Mixing probability estimates {fitted_dist.mixture_probs.asnumpy()} too far from {mixture_distribution.mixture_probs.asnumpy()}"
      for ci, c in enumerate(mixture_distribution.components):
          for ai, a in enumerate(c.args):
              assert np.allclose(
                  fitted_dist.components[ci].args[ai].asnumpy(),
                  a.asnumpy(),
                  atol=1e-1,
              ), f"Parameter {ai} estimate {fitted_dist.components[ci].args[ai].asnumpy()} too far from {c}"
  
file_path: gluonts/test/mx/distribution/test_mixture.py
imports: import mxnet
  import numpy
  import pytest
  from gluonts.core.serde import dump_json, load_json
  from gluonts.gluonts_tqdm import tqdm
  from gluonts.mx import Tensor
  from gluonts.mx.distribution import Gamma, GammaOutput, Gaussian, GaussianOutput, GenPareto, GenParetoOutput, LaplaceOutput, MixtureDistribution, MixtureDistributionOutput, MultivariateGaussianOutput, StudentT, StudentTOutput
  from gluonts.mx.distribution.distribution import Distribution
  from gluonts.mx.distribution.distribution_output import DistributionOutput
  from gluonts.testutil import empirical_cdf
label_desc: Use image node_id 8 for calling a global function with example usage: test_inference_mixture_different_families(mixture_distribution, mixture_distribution_output, epochs, serialize_fn) without return types