baselines/a2c/a2c.py [214:225]:
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        nseconds = time.time()-tstart

        # Calculate the fps (frame per second)
        fps = int((update*nbatch)/nseconds)
        if update % log_interval == 0 or update == 1:
            # Calculates if value function is a good predicator of the returns (ev > 1)
            # or if it's just worse than predicting nothing (ev =< 0)
            ev = explained_variance(values, rewards)
            logger.record_tabular("nupdates", update)
            logger.record_tabular("total_timesteps", update*nbatch)
            logger.record_tabular("fps", fps)
            logger.record_tabular("policy_entropy", float(policy_entropy))
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baselines/acktr/acktr.py [137:144]:
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        nseconds = time.time()-tstart
        fps = int((update*nbatch)/nseconds)
        if update % log_interval == 0 or update == 1:
            ev = explained_variance(values, rewards)
            logger.record_tabular("nupdates", update)
            logger.record_tabular("total_timesteps", update*nbatch)
            logger.record_tabular("fps", fps)
            logger.record_tabular("policy_entropy", float(policy_entropy))
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