[RLlib] Clean up deprecated concat_samples calls

rllib/evaluation/sampler.py

@@ -35,7 +35,7 @@
 from ray.rllib.offline import InputReader
 from ray.rllib.policy.policy import Policy
 from ray.rllib.policy.policy_map import PolicyMap
-from ray.rllib.policy.sample_batch import SampleBatch
+from ray.rllib.policy.sample_batch import SampleBatch, concat_samples
 from ray.rllib.utils.annotations import DeveloperAPI, override
 from ray.rllib.utils.debug import summarize
 from ray.rllib.utils.deprecation import deprecation_warning, DEPRECATED_VALUE
@@ -91,10 +91,9 @@ class SamplerInput(InputReader, metaclass=ABCMeta):
     def next(self) -> SampleBatchType:
         batches = [self.get_data()]
         batches.extend(self.get_extra_batches())
-        if len(batches) > 1:
-            return batches[0].concat_samples(batches)
-        else:
-            return batches[0]
+        if len(batches) == 0:
+            raise RuntimeError("No data available from sampler.")
+        return concat_samples(batches)
 
     @abstractmethod
     @DeveloperAPI

rllib/execution/buffers/mixin_replay_buffer.py

@@ -5,7 +5,7 @@
 
 from ray.util.timer import _Timer
 from ray.rllib.execution.replay_ops import SimpleReplayBuffer
-from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID, SampleBatch
+from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID, concat_samples
 from ray.rllib.utils.deprecation import Deprecated
 from ray.rllib.utils.replay_buffers.multi_agent_replay_buffer import ReplayMode
 from ray.rllib.utils.replay_buffers.replay_buffer import _ALL_POLICIES
@@ -155,7 +155,7 @@ def replay(
 
             # No replay desired -> Return here.
             if self.replay_ratio == 0.0:
-                return SampleBatch.concat_samples(output_batches)
+                return concat_samples(output_batches)
             # Only replay desired -> Return a (replayed) sample from the
             # buffer.
             elif self.replay_ratio == 1.0:
@@ -168,7 +168,7 @@ def replay(
             while random.random() < num_new * replay_proportion:
                 replay_proportion -= 1
                 output_batches.append(buffer.replay())
-            return SampleBatch.concat_samples(output_batches)
+            return concat_samples(output_batches)
 
     def get_host(self) -> str:
         """Returns the computer's network name.

rllib/policy/sample_batch.py

@@ -348,7 +348,7 @@ def concat(self, other: "SampleBatch") -> "SampleBatch":
             >>> print(b1.concat(b2)) # doctest: +SKIP
             {"a": np.array([1, 2, 3, 4, 5])}
         """
-        return self.concat_samples([self, other])
+        return concat_samples([self, other])
 
     @PublicAPI
     def copy(self, shallow: bool = False) -> "SampleBatch":
@@ -1376,7 +1376,7 @@ def wrap_as_needed(
 
     @staticmethod
     @PublicAPI
-    @Deprecated(new="concat_samples() from rllib.policy.sample_batch", error=False)
+    @Deprecated(new="concat_samples() from rllib.policy.sample_batch", error=True)
     def concat_samples(samples: List["MultiAgentBatch"]) -> "MultiAgentBatch":
         return concat_samples_into_ma_batch(samples)
 

rllib/policy/tests/test_sample_batch.py

@@ -9,7 +9,11 @@
 
 import ray
 from ray.rllib.models.repeated_values import RepeatedValues
-from ray.rllib.policy.sample_batch import SampleBatch, attempt_count_timesteps
+from ray.rllib.policy.sample_batch import (
+    SampleBatch,
+    attempt_count_timesteps,
+    concat_samples,
+)
 from ray.rllib.utils.compression import is_compressed
 from ray.rllib.utils.framework import try_import_torch
 from ray.rllib.utils.test_utils import check
@@ -84,7 +88,7 @@ def test_right_zero_padding(self):
         )
 
     def test_concat(self):
-        """Tests, SampleBatches.concat() and ...concat_samples()."""
+        """Tests, SampleBatches.concat() and concat_samples()."""
         s1 = SampleBatch(
             {
                 "a": np.array([1, 2, 3]),
@@ -97,7 +101,7 @@ def test_concat(self):
                 "b": {"c": np.array([5, 6, 7])},
             }
         )
-        concatd = SampleBatch.concat_samples([s1, s2])
+        concatd = concat_samples([s1, s2])
         check(concatd["a"], [1, 2, 3, 2, 3, 4])
         check(concatd["b"]["c"], [4, 5, 6, 5, 6, 7])
         check(next(concatd.rows()), {"a": 1, "b": {"c": 4}})
@@ -129,11 +133,11 @@ def test_concat_max_seq_len(self):
             }
         )
 
-        concatd = SampleBatch.concat_samples([s1, s2])
+        concatd = concat_samples([s1, s2])
         check(concatd.max_seq_len, s2.max_seq_len)
 
         with self.assertRaises(ValueError):
-            SampleBatch.concat_samples([s1, s2, s3])
+            concat_samples([s1, s2, s3])
 
     def test_rows(self):
         s1 = SampleBatch(

rllib/utils/replay_buffers/multi_agent_mixin_replay_buffer.py

@@ -8,9 +8,8 @@
 from ray.rllib.policy.rnn_sequencing import timeslice_along_seq_lens_with_overlap
 from ray.rllib.policy.sample_batch import (
     DEFAULT_POLICY_ID,
-    MultiAgentBatch,
     SampleBatch,
-    concat_samples,
+    concat_samples_into_ma_batch,
 )
 from ray.rllib.utils.annotations import override
 from ray.rllib.utils.replay_buffers.multi_agent_prioritized_replay_buffer import (
@@ -291,7 +290,7 @@ def round_up_or_down(value, ratio):
 
             # No replay desired
             if self.replay_ratio == 0.0:
-                return concat_samples(output_batches)
+                return concat_samples_into_ma_batch(output_batches)
             # Only replay desired
             elif self.replay_ratio == 1.0:
                 return _buffer.sample(num_items, **kwargs)
@@ -315,7 +314,7 @@ def round_up_or_down(value, ratio):
             # Depending on the implementation of underlying buffers, samples
             # might be SampleBatches
             output_batches = [batch.as_multi_agent() for batch in output_batches]
-            return MultiAgentBatch.concat_samples(output_batches)
+            return concat_samples_into_ma_batch(output_batches)
 
         def check_buffer_is_ready(_policy_id):
             if (
@@ -344,7 +343,7 @@ def check_buffer_is_ready(_policy_id):
                     if check_buffer_is_ready(policy_id):
                         samples.append(mix_batches(policy_id).as_multi_agent())
 
-            return MultiAgentBatch.concat_samples(samples)
+            return concat_samples_into_ma_batch(samples)
 
     @DeveloperAPI
     @override(MultiAgentPrioritizedReplayBuffer)

rllib/utils/replay_buffers/replay_buffer.py

@@ -9,7 +9,7 @@
 import ray  # noqa F401
 import psutil
 
-from ray.rllib.policy.sample_batch import SampleBatch
+from ray.rllib.policy.sample_batch import SampleBatch, concat_samples
 from ray.rllib.utils.actor_manager import FaultAwareApply
 from ray.rllib.utils.deprecation import Deprecated
 from ray.rllib.utils.metrics.window_stat import WindowStat
@@ -376,8 +376,7 @@ def _encode_sample(self, idxes: List[int]) -> SampleBatchType:
 
         if samples:
             # We assume all samples are of same type
-            sample_type = type(samples[0])
-            out = sample_type.concat_samples(samples)
+            out = concat_samples(samples)
         else:
             out = SampleBatch()
         out.decompress_if_needed()