Is it possible to include callbacks (tensorboard) to GANs? about keras-gan HOT 5 CLOSED

def write_log(callback, names, logs, batch_no):
    for name, value in zip(names, logs):
        summary = tf.Summary()
        summary_value = summary.value.add()
        summary_value.simple_value = value
        summary_value.tag = name
        callback.writer.add_summary(summary, batch_no)
        callback.writer.flush()

log_path = './logs'
callback = TensorBoard(log_path)
callback.set_model(model)

d_loss = discriminator.train_on_batch...
g_loss = combined.train_on_batch...

write_log(callback, ['g_loss'], [g_loss], batch_no)
write_log(callback, ['d_loss'], [d_loss], batch_no)

            d_loss_real = self.discriminator.train_on_batch(imgs, np.ones((half_batch, 1)))
            d_loss_fake = self.discriminator.train_on_batch(gen_imgs, np.zeros((half_batch, 1)))
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)

TypeError: only size-1 arrays can be converted to Python scalars

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "D:/Research/Generative_adversarial_networks/dcgan/keras_degan.py", line 196, in <module>
    dcgan.train(callback, epochs=4000, batch_size=32, save_interval=200)
  File "D:/Research/Generative_adversarial_networks/dcgan/keras_degan.py", line 163, in train
    write_log(callback, ['d_loss'], [d_loss], epoch)
  File "D:/Research/Generative_adversarial_networks/dcgan/keras_degan.py", line 22, in write_log
    summary_value.simple_value = value
  File "C:\Users\bikas\Anaconda3\lib\site-packages\numpy\core\arrayprint.py", line 1379, in array_repr
    if type(arr) is not ndarray:
SystemError: <class 'type'> returned a result with an error set