docstr: Tests that generated graph is dag for different numbers of nodes and degrees
docstr_tok: ["Tests","that","generated","graph","is","dag","for","different","numbers","of","nodes","and","degrees"]
code: def test_is_dag_nodes_degrees(self, num_nodes, degree):
      """Tests that generated graph is dag for different numbers of nodes and degrees"""
      sm = generate_structure(num_nodes, degree)
      assert nx.is_directed_acyclic_graph(sm)
  
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 2 for calling the TestGenerateStructure obj's underlying member method code with example usage: obj.test_is_dag_nodes_degrees(num_nodes, degree) without return types