code: def generate_dummy_graph(
      num_nodes: int,
      num_edges: int,
      node_feature_dim: int = 9,
      edge_feature_dim: int = 3,
      labels_dim: int = 128,
  ) -> ArrayDict:
      """Generates a dummy graph with random edges, features and label."""
      nodes = np.arange(num_nodes)
      node_features = np.random.standard_normal(
          (num_nodes, node_feature_dim)
      )
  
      possible_edge_indices = list(itertools.permutations(nodes, 2))
      edge_indices = np.array(
          random.choices(possible_edge_indices, k=num_edges)
      )
      edge_features = np.random.standard_normal(
          (num_edges, edge_feature_dim)
      )
  
      labels = np.random.randint(low=0, high=3, size=(1, labels_dim))
      labels = labels.astype(np.float64)
      labels[labels == 2] = np.nan
  
      return {
          "labels": labels,
          "num_nodes": np.array([num_nodes]),
          "node_feat": node_features,
          "num_edges": np.array([num_edges]),
          "edge_feat": edge_features,
          "edge_index": edge_indices,
      }
  
file_path: datasets/tensorflow_datasets/datasets/ogbg_molpcba/dummy_data_generation.py
imports: import collections
  import itertools
  import random
  from typing import Dict, Iterable, List, Text
  from absl import app
  from absl import flags
  from etils import epath
  import numpy
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.utils import resource_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import pandas
label_desc: Use image node_id 4 for calling a global function with example usage: generate_dummy_graph(num_nodes, num_edges, node_feature_dim, edge_feature_dim, labels_dim) and returns: dict