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[rllib] fix clip by value issue as TF upgraded (#4697)
* fix clip_by_value issue * fix typo
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1622fc21fc
commit
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2 changed files with 11 additions and 5 deletions
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@ -166,8 +166,9 @@ class DDPGPolicyGraph(DDPGPostprocessing, TFPolicyGraph):
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stddev=self.config["target_noise"]),
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stddev=self.config["target_noise"]),
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-target_noise_clip, target_noise_clip)
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-target_noise_clip, target_noise_clip)
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policy_tp1_smoothed = tf.clip_by_value(
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policy_tp1_smoothed = tf.clip_by_value(
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policy_tp1 + clipped_normal_sample, action_space.low,
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policy_tp1 + clipped_normal_sample,
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action_space.high)
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action_space.low * tf.ones_like(policy_tp1),
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action_space.high * tf.ones_like(policy_tp1))
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else:
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else:
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# no smoothing, just use deterministic actions
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# no smoothing, just use deterministic actions
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policy_tp1_smoothed = policy_tp1
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policy_tp1_smoothed = policy_tp1
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@ -473,8 +474,9 @@ class DDPGPolicyGraph(DDPGPostprocessing, TFPolicyGraph):
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tf.shape(deterministic_actions),
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tf.shape(deterministic_actions),
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stddev=self.config["exploration_gaussian_sigma"])
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stddev=self.config["exploration_gaussian_sigma"])
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stochastic_actions = tf.clip_by_value(
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stochastic_actions = tf.clip_by_value(
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deterministic_actions + normal_sample, action_low,
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deterministic_actions + normal_sample,
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action_high)
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action_low * tf.ones_like(deterministic_actions),
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action_high * tf.ones_like(deterministic_actions))
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elif noise_type == "ou":
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elif noise_type == "ou":
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# add OU noise for exploration, DDPG-style
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# add OU noise for exploration, DDPG-style
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zero_acts = action_low.size * [.0]
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zero_acts = action_low.size * [.0]
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@ -494,7 +496,9 @@ class DDPGPolicyGraph(DDPGPostprocessing, TFPolicyGraph):
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noise = noise_scale * base_scale \
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noise = noise_scale * base_scale \
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* exploration_value * action_range
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* exploration_value * action_range
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stochastic_actions = tf.clip_by_value(
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stochastic_actions = tf.clip_by_value(
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deterministic_actions + noise, action_low, action_high)
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deterministic_actions + noise,
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action_low * tf.ones_like(deterministic_actions),
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action_high * tf.ones_like(deterministic_actions))
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else:
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else:
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raise ValueError(
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raise ValueError(
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"Unknown noise type '%s' (try 'ou' or 'gaussian')" %
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"Unknown noise type '%s' (try 'ou' or 'gaussian')" %
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@ -47,6 +47,8 @@ class TFRunBuilder(object):
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self.session, self.fetches, self.debug_name,
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self.session, self.fetches, self.debug_name,
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self.feed_dict, os.environ.get("TF_TIMELINE_DIR"))
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self.feed_dict, os.environ.get("TF_TIMELINE_DIR"))
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except Exception:
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except Exception:
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logger.exception("Error fetching: {}, feed_dict={}".format(
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self.fetches, self.feed_dict))
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raise ValueError("Error fetching: {}, feed_dict={}".format(
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raise ValueError("Error fetching: {}, feed_dict={}".format(
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self.fetches, self.feed_dict))
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self.fetches, self.feed_dict))
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if isinstance(to_fetch, int):
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if isinstance(to_fetch, int):
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