[rllib] Remove nested import (#5204)

* remove nested import

* Update metrics.py

python/ray/rllib/evaluation/metrics.py

@@ -15,6 +15,11 @@ from ray.rllib.utils.memory import ray_get_and_free
 
 logger = logging.getLogger(__name__)
 
+RolloutMetrics = collections.namedtuple("RolloutMetrics", [
+    "episode_length", "episode_reward", "agent_rewards", "custom_metrics",
+    "perf_stats"
+])
+
 
 @DeveloperAPI
 def get_learner_stats(grad_info):
@@ -161,8 +166,6 @@ def summarize_episodes(episodes, new_episodes, num_dropped):
 def _partition(episodes):
     """Divides metrics data into true rollouts vs off-policy estimates."""
 
-    from ray.rllib.evaluation.sampler import RolloutMetrics
-
     rollouts, estimates = [], []
     for e in episodes:
         if isinstance(e, RolloutMetrics):

python/ray/rllib/evaluation/sampler.py

@@ -10,6 +10,7 @@ import threading
 import time
 
 from ray.rllib.evaluation.episode import MultiAgentEpisode, _flatten_action
+from ray.rllib.evaluation.metrics import RolloutMetrics
 from ray.rllib.evaluation.sample_batch_builder import \
     MultiAgentSampleBatchBuilder
 from ray.rllib.policy.tf_policy import TFPolicy
@@ -24,11 +25,6 @@ from ray.rllib.policy.policy import clip_action
 
 logger = logging.getLogger(__name__)
 
-RolloutMetrics = namedtuple("RolloutMetrics", [
-    "episode_length", "episode_reward", "agent_rewards", "custom_metrics",
-    "perf_stats"
-])
-
 PolicyEvalData = namedtuple("PolicyEvalData", [
     "env_id", "agent_id", "obs", "info", "rnn_state", "prev_action",
     "prev_reward"