Python tensorboard_log_gradients примеры использования

Пример #1

Файл: inverse_policy_mdn.py Проект: HumanCompatibleAI/deep-rlsp

 def _define_tensorboard_metrics(self):
     tf.summary.scalar("loss/loss", self.loss)
     tf.summary.scalar("loss/mixture_entropy", self.mixture_entropy)
     tf.summary.scalar("learning_rate", self.learning_rate)
     for i, lp in enumerate(self.logprobs):
         tf.summary.scalar("loss/logprob_{}".format(i + 1), lp)
     tensorboard_log_gradients(self.gradients)

Пример #2

    def _define_tensorboard_metrics(self):
        tensorboard_log_gradients(self.gradients)

        tf.summary.scalar("loss/loss", self.loss)
        tf.summary.scalar("learning_rate", self.learning_rate)

        tf.summary.scalar("loss/likelihood", tf.reduce_mean(self.likelihood))
        tf.summary.scalar("loss/divergence", tf.reduce_mean(self.divergence))
        tf.summary.scalar("loss/elbo", self.elbo)

Пример #3

Файл: policy_discriminator.py Проект: HumanCompatibleAI/deep-rlsp

 def _define_tensorboard_metrics(self):
     tf.summary.scalar("loss/loss", self.loss)
     tf.summary.scalar("learning_rate", self.learning_rate)
     tensorboard_log_gradients(self.gradients)