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less logging

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wassname
2019-01-29 15:17:24 +08:00
parent cb043a44dc
commit 5a395c8845
1 changed files with 13 additions and 11 deletions
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agent/DDPG_agent.py
+13 -11
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@@ -81,13 +81,14 @@ class DDPGAgent:
# tensorboard logging
suffix = 'test_' if deterministic else ''
config.logger.scalar_summary(suffix + 'reward', reward, self.total_steps)
if deterministic or ((steps % 10) == 0):
if ((steps % 50) == 0):
config.logger.scalar_summary(suffix + 'reward', reward, self.total_steps)
# it will log to much data if we log every step
if action.squeeze().ndim == 0:
config.logger.scalar_summary(suffix + 'action', action, self.total_steps)
else:
config.logger.histo_summary(suffix + 'action', action, self.total_steps)
#else:
# config.logger.histo_summary(suffix + 'action', action, self.total_steps)
config.logger.scalar_summary(suffix + 'noise', np.mean(noise), self.total_steps)
for key in info:
config.logger.scalar_summary('info_' + key, info[key], self.total_steps)
@@ -139,13 +140,14 @@ class DDPGAgent:
actor.zero_grad()
# tensorboard logging
config.logger.scalar_summary('loss_policy', -var_actions.grad.data.sum(), self.total_steps)
config.logger.scalar_summary('loss_critic', critic_loss, self.total_steps)
config.logger.scalar_summary('lr_actor', torch.FloatTensor([self.actor_opt.param_groups[0]['lr']]), self.total_steps)
config.logger.scalar_summary('lr_critic', torch.FloatTensor([self.critic_opt.param_groups[0]['lr']]), self.total_steps)
if config.gradient_clip:
config.logger.histo_summary('grad_norm_actor', actor_grad_norm, self.total_steps)
config.logger.histo_summary('grad_norm_critic', critic_grad_norm, self.total_steps)
if ((steps % 50) == 0):
config.logger.scalar_summary('loss_policy', -var_actions.grad.data.sum(), self.total_steps)
config.logger.scalar_summary('loss_critic', critic_loss, self.total_steps)
config.logger.scalar_summary('lr_actor', torch.FloatTensor([self.actor_opt.param_groups[0]['lr']]), self.total_steps)
config.logger.scalar_summary('lr_critic', torch.FloatTensor([self.critic_opt.param_groups[0]['lr']]), self.total_steps)
if config.gradient_clip:
config.logger.histo_summary('grad_norm_actor', actor_grad_norm, self.total_steps)
config.logger.histo_summary('grad_norm_critic', critic_grad_norm, self.total_steps)
self.soft_update(self.target_network, self.worker_network)