code: def test_incorrect_weight_dist(self):
      sm = StructureModel()
      nodes = list(str(x) for x in range(6))
      np.random.shuffle(nodes)
      sm.add_nodes_from(nodes)
  
      sm.add_weighted_edges_from([("0", "1", None), ("2", "4", None)])
  
      with pytest.raises(
          ValueError, match="Unknown weight distribution"
      ):
          _ = sem_generator(
              graph=sm,
              schema=None,
              default_type="continuous",
              distributions={"weight": "unknown"},
              noise_std=2.0,
              n_samples=1000,
              intercept=False,
              seed=10,
          )
  
imports: import operator
  from typing import Hashable, Tuple, Union
  import networkx
  import numpy
  import pandas
  import pytest
  from networkx.algorithms.dag import is_directed_acyclic_graph
  from sklearn.gaussian_process.kernels import RBF
  from causalnex.structure.data_generators.core import _sample_binary_from_latent, _sample_count_from_latent, _sample_poisson, generate_structure, nonlinear_sem_generator, sem_generator
  from causalnex.structure.structuremodel import StructureModel
label_desc: Use image node_id 6 for calling the TestMixedDataGen obj's underlying member method code with example usage: obj.test_incorrect_weight_dist() without return types