code: def accuracy(y_true, logits):
      # y_true: shape=(batch_size) or (batch_size,1), type=integer
      # logits: shape=(batch_size, num_of_classes), type=float
      # returns float
      batch_size = y_true.shape[0]
      y_true = tf.squeeze(y_true)
      y_pred = tf.math.argmax(logits, axis=1)
      y_pred = tf.cast(y_pred, y_true.dtype)
      equal = tf.cast(y_pred == y_true, tf.int32)
      return tf.math.reduce_sum(equal).numpy() / batch_size
  
label_desc: Use image node_id 2 for calling a global function with example usage: accuracy(y_true, logits) and returns: unknown