def get_data_distribution(dataset=[]):
  labels = []
  for data in dataset:
    for _,label in data:
      labels.extend(tf.argmax(label,axis=1).numpy())
  y, idx, count = tf.unique_with_counts(labels)
  return y, count

def visualize_data(class_data,count):
  plt.figure(figsize=(10,10))
  plt.bar(class_data,count,align="center")
  plt.tight_layout()
  plt.title("Class Distribution")
  plt.ylabel("Number of Data")
  plt.xlabel("Class in number")
  plt.show()

        __
        __