class_docstr: A dataset of random colored graphs.
  The task is to classify each graph with the color which occurs the most in
  its nodes.
  The graphs have `n_colors` colors, of at least `n_min` and at most `n_max`
  nodes connected with probability `p`.
class_docstr_tok: ["A","dataset","of","random","colored","graphs",".","The","task","is","to","classify","each","graph","with","the","color","which","occurs","the","most","in","its","nodes",".","The","graphs","have","`","n_colors","`","colors",",","of","at","least","`","n_min","`","and","at","most","`","n_max","`","nodes","connected","with","probability","`","p","`","."]
code: def __init__(
      self, n_samples, n_colors=3, n_min=10, n_max=100, p=0.1, **kwargs
  ):
      self.n_samples = n_samples
      self.n_colors = n_colors
      self.n_min = n_min
      self.n_max = n_max
      self.p = p
      super().__init__(**kwargs)
  
imports: import numpy
  import scipy.sparse
  import tensorflow
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.losses import CategoricalCrossentropy
  from tensorflow.keras.metrics import categorical_accuracy
  from tensorflow.keras.models import Model
  from tensorflow.keras.optimizers import Adam
  from spektral.data import Dataset, DisjointLoader, Graph
  from spektral.layers import GCSConv, GlobalAvgPool
  from spektral.transforms.normalize_adj import NormalizeAdj
label_desc: Use image node_id 1 to create a new MyDataset object from inherited base classes: Dataset with example: obj = MyDataset(n_samples, n_colors, n_min, n_max, p)