[RLlib] Rename rllib.utils.types into typing to match built-in python module's name. (#10114)

rllib/agents/callbacks.py

@@ -6,7 +6,7 @@ from ray.rllib.policy.sample_batch import SampleBatch
 from ray.rllib.evaluation import MultiAgentEpisode, RolloutWorker
 from ray.rllib.utils.annotations import PublicAPI
 from ray.rllib.utils.deprecation import deprecation_warning
-from ray.rllib.utils.types import AgentID, PolicyID
+from ray.rllib.utils.typing import AgentID, PolicyID
 
 
 @PublicAPI

rllib/agents/dqn/apex.py

@@ -16,7 +16,7 @@ from ray.rllib.execution.metric_ops import StandardMetricsReporting
 from ray.rllib.execution.replay_buffer import ReplayActor
 from ray.rllib.utils import merge_dicts
 from ray.rllib.utils.actors import create_colocated
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 # yapf: disable
 # __sphinx_doc_begin__

rllib/agents/mbmpo/model_ensemble.py

@@ -6,7 +6,7 @@ from ray.rllib.utils.framework import try_import_torch
 from ray.rllib.evaluation.rollout_worker import get_global_worker
 from ray.rllib.policy.sample_batch import SampleBatch
 from ray.rllib.execution.common import STEPS_SAMPLED_COUNTER
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 from ray.rllib.utils.torch_ops import convert_to_torch_tensor
 
 torch, nn = try_import_torch()

rllib/agents/trainer.py

@@ -25,7 +25,7 @@ from ray.rllib.utils.framework import try_import_tf, TensorStructType
 from ray.rllib.utils.annotations import override, PublicAPI, DeveloperAPI
 from ray.rllib.utils.deprecation import DEPRECATED_VALUE, deprecation_warning
 from ray.rllib.utils.from_config import from_config
-from ray.rllib.utils.types import TrainerConfigDict, \
+from ray.rllib.utils.typing import TrainerConfigDict, \
     PartialTrainerConfigDict, EnvInfoDict, ResultDict, EnvType, PolicyID
 from ray.tune.registry import ENV_CREATOR, register_env, _global_registry
 from ray.tune.trainable import Trainable

rllib/agents/trainer_template.py

@@ -9,7 +9,7 @@ from ray.rllib.execution.metric_ops import StandardMetricsReporting
 from ray.rllib.policy import Policy
 from ray.rllib.utils import add_mixins
 from ray.rllib.utils.annotations import override, DeveloperAPI
-from ray.rllib.utils.types import TrainerConfigDict, ResultDict
+from ray.rllib.utils.typing import TrainerConfigDict, ResultDict
 
 logger = logging.getLogger(__name__)
 

rllib/env/base_env.py

@@ -5,7 +5,7 @@ from ray.rllib.env.external_multi_agent_env import ExternalMultiAgentEnv
 from ray.rllib.env.multi_agent_env import MultiAgentEnv
 from ray.rllib.env.vector_env import VectorEnv
 from ray.rllib.utils.annotations import override, PublicAPI
-from ray.rllib.utils.types import EnvType, MultiEnvDict, EnvID, \
+from ray.rllib.utils.typing import EnvType, MultiEnvDict, EnvID, \
     AgentID, MultiAgentDict
 
 if TYPE_CHECKING:

rllib/env/env_context.py

@@ -1,5 +1,5 @@
 from ray.rllib.utils.annotations import PublicAPI
-from ray.rllib.utils.types import EnvConfigDict
+from ray.rllib.utils.typing import EnvConfigDict
 
 
 @PublicAPI

rllib/env/external_env.py

@@ -5,7 +5,7 @@ import uuid
 from typing import Optional
 
 from ray.rllib.utils.annotations import PublicAPI
-from ray.rllib.utils.types import EnvActionType, EnvObsType, EnvInfoDict
+from ray.rllib.utils.typing import EnvActionType, EnvObsType, EnvInfoDict
 
 
 @PublicAPI

rllib/env/external_multi_agent_env.py

@@ -4,7 +4,7 @@ from typing import Optional
 
 from ray.rllib.utils.annotations import override, PublicAPI
 from ray.rllib.env.external_env import ExternalEnv, _ExternalEnvEpisode
-from ray.rllib.utils.types import MultiAgentDict
+from ray.rllib.utils.typing import MultiAgentDict
 
 
 @PublicAPI

rllib/env/multi_agent_env.py

@@ -2,7 +2,7 @@ from typing import Tuple, Dict, List
 import gym
 
 from ray.rllib.utils.annotations import PublicAPI
-from ray.rllib.utils.types import MultiAgentDict, AgentID
+from ray.rllib.utils.typing import MultiAgentDict, AgentID
 
 # If the obs space is Dict type, look for the global state under this key.
 ENV_STATE = "state"

rllib/env/policy_client.py

@@ -14,7 +14,7 @@ from ray.rllib.evaluation.rollout_worker import RolloutWorker
 from ray.rllib.env import ExternalEnv, MultiAgentEnv, ExternalMultiAgentEnv
 from ray.rllib.policy.sample_batch import MultiAgentBatch
 from ray.rllib.utils.annotations import PublicAPI
-from ray.rllib.utils.types import MultiAgentDict, EnvInfoDict, EnvObsType, \
+from ray.rllib.utils.typing import MultiAgentDict, EnvInfoDict, EnvObsType, \
     EnvActionType
 
 logger = logging.getLogger(__name__)

rllib/env/remote_vector_env.py

@@ -4,7 +4,7 @@ from typing import Tuple, Callable, Optional
 import ray
 from ray.rllib.env.base_env import BaseEnv, _DUMMY_AGENT_ID, ASYNC_RESET_RETURN
 from ray.rllib.utils.annotations import override, PublicAPI
-from ray.rllib.utils.types import MultiEnvDict, EnvType, EnvID, MultiAgentDict
+from ray.rllib.utils.typing import MultiEnvDict, EnvType, EnvID, MultiAgentDict
 
 logger = logging.getLogger(__name__)
 

rllib/env/unity3d_env.py

@@ -5,7 +5,7 @@ from typing import Callable, Tuple
 
 from ray.rllib.env.multi_agent_env import MultiAgentEnv
 from ray.rllib.utils.annotations import override
-from ray.rllib.utils.types import MultiAgentDict, PolicyID, AgentID
+from ray.rllib.utils.typing import MultiAgentDict, PolicyID, AgentID
 
 logger = logging.getLogger(__name__)
 

rllib/env/vector_env.py

@@ -4,7 +4,7 @@ import numpy as np
 from typing import Callable, List, Tuple
 
 from ray.rllib.utils.annotations import override, PublicAPI
-from ray.rllib.utils.types import EnvType, EnvConfigDict, EnvObsType, \
+from ray.rllib.utils.typing import EnvType, EnvConfigDict, EnvObsType, \
     EnvInfoDict, EnvActionType
 
 logger = logging.getLogger(__name__)

rllib/evaluation/episode.py

@@ -7,7 +7,7 @@ from ray.rllib.env.base_env import _DUMMY_AGENT_ID
 from ray.rllib.policy.policy import Policy
 from ray.rllib.utils.annotations import DeveloperAPI
 from ray.rllib.utils.spaces.space_utils import flatten_to_single_ndarray
-from ray.rllib.utils.types import SampleBatchType, AgentID, PolicyID, \
+from ray.rllib.utils.typing import SampleBatchType, AgentID, PolicyID, \
     EnvObsType, EnvInfoDict, EnvActionType
 
 if TYPE_CHECKING:

rllib/evaluation/metrics.py

@@ -9,7 +9,7 @@ from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID
 from ray.rllib.offline.off_policy_estimator import OffPolicyEstimate
 from ray.rllib.policy.policy import LEARNER_STATS_KEY
 from ray.rllib.utils.annotations import DeveloperAPI
-from ray.rllib.utils.types import GradInfoDict, LearnerStatsDict, ResultDict
+from ray.rllib.utils.typing import GradInfoDict, LearnerStatsDict, ResultDict
 
 logger = logging.getLogger(__name__)
 

rllib/evaluation/observation_function.py

@@ -4,7 +4,7 @@ from ray.rllib.env import BaseEnv
 from ray.rllib.policy import Policy
 from ray.rllib.evaluation import MultiAgentEpisode, RolloutWorker
 from ray.rllib.utils.framework import TensorType
-from ray.rllib.utils.types import AgentID, PolicyID
+from ray.rllib.utils.typing import AgentID, PolicyID
 
 
 class ObservationFunction:

rllib/evaluation/rollout_worker.py

@@ -36,7 +36,7 @@ from ray.rllib.utils.filter import get_filter, Filter
 from ray.rllib.utils.framework import try_import_tf, try_import_torch
 from ray.rllib.utils.sgd import do_minibatch_sgd
 from ray.rllib.utils.tf_run_builder import TFRunBuilder
-from ray.rllib.utils.types import EnvType, AgentID, PolicyID, EnvConfigDict, \
+from ray.rllib.utils.typing import EnvType, AgentID, PolicyID, EnvConfigDict, \
     ModelConfigDict, TrainerConfigDict, SampleBatchType, ModelWeights, \
     ModelGradients, MultiAgentPolicyConfigDict
 from ray.util.debug import log_once, disable_log_once_globally, \

rllib/evaluation/sample_batch_builder.py

@@ -8,7 +8,7 @@ from ray.rllib.policy.policy import Policy
 from ray.rllib.policy.sample_batch import SampleBatch, MultiAgentBatch
 from ray.rllib.utils.annotations import PublicAPI, DeveloperAPI
 from ray.rllib.utils.debug import summarize
-from ray.rllib.utils.types import PolicyID, AgentID
+from ray.rllib.utils.typing import PolicyID, AgentID
 from ray.rllib.env.base_env import _DUMMY_AGENT_ID
 from ray.util.debug import log_once
 

rllib/evaluation/sample_collector.py

@@ -4,7 +4,7 @@ from typing import Dict, Optional
 
 from ray.rllib.evaluation.episode import MultiAgentEpisode
 from ray.rllib.models.modelv2 import ModelV2
-from ray.rllib.utils.types import AgentID, EpisodeID, PolicyID, \
+from ray.rllib.utils.typing import AgentID, EpisodeID, PolicyID, \
     TensorType
 
 logger = logging.getLogger(__name__)

rllib/evaluation/sampler.py

@@ -25,7 +25,7 @@ from ray.rllib.utils.debug import summarize
 from ray.rllib.utils.spaces.space_utils import flatten_to_single_ndarray, \
     unbatch
 from ray.rllib.utils.tf_run_builder import TFRunBuilder
-from ray.rllib.utils.types import SampleBatchType, AgentID, PolicyID, \
+from ray.rllib.utils.typing import SampleBatchType, AgentID, PolicyID, \
     EnvObsType, EnvInfoDict, EnvID, MultiEnvDict, EnvActionType, \
     TensorStructType
 

rllib/evaluation/worker_set.py

@@ -12,7 +12,7 @@ from ray.rllib.env.env_context import EnvContext
 from ray.rllib.policy import Policy
 from ray.rllib.utils import merge_dicts
 from ray.rllib.utils.framework import try_import_tf
-from ray.rllib.utils.types import PolicyID, TrainerConfigDict, EnvType
+from ray.rllib.utils.typing import PolicyID, TrainerConfigDict, EnvType
 
 tf1, tf, tfv = try_import_tf()
 

rllib/execution/replay_buffer.py

@@ -13,7 +13,7 @@ from ray.rllib.utils.annotations import DeveloperAPI
 from ray.util.iter import ParallelIteratorWorker
 from ray.rllib.utils.timer import TimerStat
 from ray.rllib.utils.window_stat import WindowStat
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 # Constant that represents all policies in lockstep replay mode.
 _ALL_POLICIES = "__all__"

rllib/execution/replay_ops.py

@@ -6,7 +6,7 @@ from ray.util.iter_metrics import SharedMetrics
 from ray.rllib.execution.replay_buffer import LocalReplayBuffer
 from ray.rllib.execution.common import \
     STEPS_SAMPLED_COUNTER, _get_shared_metrics
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 
 class StoreToReplayBuffer:

rllib/execution/rollout_ops.py

@@ -13,7 +13,7 @@ from ray.rllib.execution.common import STEPS_SAMPLED_COUNTER, LEARNER_INFO, \
 from ray.rllib.policy.sample_batch import SampleBatch, DEFAULT_POLICY_ID, \
     MultiAgentBatch
 from ray.rllib.utils.sgd import standardized
-from ray.rllib.utils.types import PolicyID, SampleBatchType, ModelGradients
+from ray.rllib.utils.typing import PolicyID, SampleBatchType, ModelGradients
 
 logger = logging.getLogger(__name__)
 

rllib/execution/train_ops.py

@@ -18,7 +18,7 @@ from ray.rllib.policy.sample_batch import SampleBatch, DEFAULT_POLICY_ID, \
     MultiAgentBatch
 from ray.rllib.utils.framework import try_import_tf
 from ray.rllib.utils.sgd import do_minibatch_sgd, averaged
-from ray.rllib.utils.types import PolicyID, SampleBatchType
+from ray.rllib.utils.typing import PolicyID, SampleBatchType
 
 tf1, tf, tfv = try_import_tf()
 

rllib/execution/tree_agg.py

@@ -10,7 +10,7 @@ from ray.rllib.execution.rollout_ops import ParallelRollouts, ConcatBatches
 from ray.rllib.utils.actors import create_colocated
 from ray.util.iter import ParallelIterator, ParallelIteratorWorker, \
     from_actors
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 logger = logging.getLogger(__name__)
 

rllib/models/action_dist.py

@@ -3,7 +3,7 @@ import gym
 
 from ray.rllib.models.modelv2 import ModelV2
 from ray.rllib.utils.annotations import DeveloperAPI
-from ray.rllib.utils.types import TensorType, List, Union, ModelConfigDict
+from ray.rllib.utils.typing import TensorType, List, Union, ModelConfigDict
 
 
 @DeveloperAPI

rllib/models/catalog.py

@@ -27,7 +27,7 @@ from ray.rllib.utils.error import UnsupportedSpaceException
 from ray.rllib.utils.framework import try_import_tf
 from ray.rllib.utils.spaces.simplex import Simplex
 from ray.rllib.utils.spaces.space_utils import flatten_space
-from ray.rllib.utils.types import ModelConfigDict, TensorType
+from ray.rllib.utils.typing import ModelConfigDict, TensorType
 
 tf1, tf, tfv = try_import_tf()
 

rllib/models/modelv2.py

@@ -13,7 +13,7 @@ from ray.rllib.utils.annotations import DeveloperAPI, PublicAPI
 from ray.rllib.utils.framework import try_import_tf, try_import_torch, \
     TensorType
 from ray.rllib.utils.spaces.repeated import Repeated
-from ray.rllib.utils.types import ModelConfigDict, TensorStructType
+from ray.rllib.utils.typing import ModelConfigDict, TensorStructType
 
 tf1, tf, tfv = try_import_tf()
 torch, _ = try_import_torch()

rllib/models/tf/tf_action_dist.py

@@ -10,7 +10,7 @@ from ray.rllib.utils import MIN_LOG_NN_OUTPUT, MAX_LOG_NN_OUTPUT, \
 from ray.rllib.utils.annotations import override, DeveloperAPI
 from ray.rllib.utils.framework import try_import_tf, try_import_tfp
 from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space
-from ray.rllib.utils.types import TensorType, List
+from ray.rllib.utils.typing import TensorType, List
 
 tf1, tf, tfv = try_import_tf()
 tfp = try_import_tfp()

rllib/models/tf/tf_modelv2.py

@@ -5,7 +5,7 @@ from typing import List
 from ray.rllib.models.modelv2 import ModelV2
 from ray.rllib.utils.annotations import override, PublicAPI
 from ray.rllib.utils.framework import try_import_tf
-from ray.rllib.utils.types import ModelConfigDict, TensorType
+from ray.rllib.utils.typing import ModelConfigDict, TensorType
 
 tf1, tf, tfv = try_import_tf()
 

rllib/models/torch/torch_action_dist.py

@@ -11,7 +11,7 @@ from ray.rllib.utils.numpy import SMALL_NUMBER, MIN_LOG_NN_OUTPUT, \
     MAX_LOG_NN_OUTPUT
 from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space
 from ray.rllib.utils.torch_ops import atanh
-from ray.rllib.utils.types import TensorType, List
+from ray.rllib.utils.typing import TensorType, List
 
 torch, nn = try_import_torch()
 

rllib/models/torch/torch_modelv2.py

@@ -4,7 +4,7 @@ from typing import List
 from ray.rllib.models.modelv2 import ModelV2
 from ray.rllib.utils.annotations import override, PublicAPI
 from ray.rllib.utils.framework import try_import_torch
-from ray.rllib.utils.types import ModelConfigDict, TensorType
+from ray.rllib.utils.typing import ModelConfigDict, TensorType
 
 _, nn = try_import_torch()
 

rllib/offline/input_reader.py

@@ -6,7 +6,7 @@ from ray.rllib.policy.sample_batch import MultiAgentBatch
 from ray.rllib.utils.annotations import PublicAPI
 from ray.rllib.utils.framework import try_import_tf
 from typing import Dict, List
-from ray.rllib.utils.types import TensorType, SampleBatchType
+from ray.rllib.utils.typing import TensorType, SampleBatchType
 
 tf1, tf, tfv = try_import_tf()
 

rllib/offline/is_estimator.py

@@ -1,7 +1,7 @@
 from ray.rllib.offline.off_policy_estimator import OffPolicyEstimator, \
     OffPolicyEstimate
 from ray.rllib.utils.annotations import override
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 
 class ImportanceSamplingEstimator(OffPolicyEstimator):

rllib/offline/json_reader.py

@@ -16,7 +16,7 @@ from ray.rllib.policy.sample_batch import MultiAgentBatch, SampleBatch, \
     DEFAULT_POLICY_ID
 from ray.rllib.utils.annotations import override, PublicAPI
 from ray.rllib.utils.compression import unpack_if_needed
-from ray.rllib.utils.types import FileType, SampleBatchType
+from ray.rllib.utils.typing import FileType, SampleBatchType
 from typing import List
 
 logger = logging.getLogger(__name__)

rllib/offline/json_writer.py

@@ -16,7 +16,7 @@ from ray.rllib.offline.io_context import IOContext
 from ray.rllib.offline.output_writer import OutputWriter
 from ray.rllib.utils.annotations import override, PublicAPI
 from ray.rllib.utils.compression import pack, compression_supported
-from ray.rllib.utils.types import FileType, SampleBatchType
+from ray.rllib.utils.typing import FileType, SampleBatchType
 from typing import Any, List
 
 logger = logging.getLogger(__name__)

rllib/offline/mixed_input.py

@@ -4,7 +4,7 @@ from ray.rllib.offline.input_reader import InputReader
 from ray.rllib.offline.json_reader import JsonReader
 from ray.rllib.offline.io_context import IOContext
 from ray.rllib.utils.annotations import override, DeveloperAPI
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 from typing import Dict
 
 

rllib/offline/off_policy_estimator.py

@@ -5,7 +5,7 @@ from ray.rllib.policy.sample_batch import MultiAgentBatch, SampleBatch
 from ray.rllib.policy import Policy
 from ray.rllib.utils.annotations import DeveloperAPI
 from ray.rllib.offline.io_context import IOContext
-from ray.rllib.utils.types import TensorType, SampleBatchType
+from ray.rllib.utils.typing import TensorType, SampleBatchType
 from typing import List
 
 logger = logging.getLogger(__name__)

rllib/offline/output_writer.py

@@ -1,6 +1,6 @@
 from ray.rllib.utils.annotations import override
 from ray.rllib.utils.annotations import PublicAPI
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 
 @PublicAPI

rllib/offline/shuffled_input.py

@@ -3,7 +3,7 @@ import random
 
 from ray.rllib.offline.input_reader import InputReader
 from ray.rllib.utils.annotations import override, DeveloperAPI
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 logger = logging.getLogger(__name__)
 

rllib/offline/wis_estimator.py

@@ -2,7 +2,7 @@ from ray.rllib.offline.off_policy_estimator import OffPolicyEstimator, \
     OffPolicyEstimate
 from ray.rllib.policy import Policy
 from ray.rllib.utils.annotations import override
-from ray.rllib.utils.types import SampleBatchType
+from ray.rllib.utils.typing import SampleBatchType
 
 
 class WeightedImportanceSamplingEstimator(OffPolicyEstimator):

rllib/policy/dynamic_tf_policy.py

@@ -14,7 +14,8 @@ from ray.rllib.utils.annotations import override, DeveloperAPI
 from ray.rllib.utils.debug import summarize
 from ray.rllib.utils.framework import try_import_tf
 from ray.rllib.utils.tracking_dict import UsageTrackingDict
-from ray.rllib.utils.types import ModelGradients, TensorType, TrainerConfigDict
+from ray.rllib.utils.typing import ModelGradients, TensorType, \
+    TrainerConfigDict
 
 tf1, tf, tfv = try_import_tf()
 

rllib/policy/policy.py

@@ -11,7 +11,7 @@ from ray.rllib.utils.framework import try_import_torch
 from ray.rllib.utils.from_config import from_config
 from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space, \
     unbatch
-from ray.rllib.utils.types import AgentID, ModelGradients, ModelWeights, \
+from ray.rllib.utils.typing import AgentID, ModelGradients, ModelWeights, \
     TensorType, TrainerConfigDict, Tuple, Union
 
 torch, _ = try_import_torch()

rllib/policy/sample_batch.py

@@ -8,7 +8,7 @@ from ray.rllib.utils.annotations import PublicAPI, DeveloperAPI
 from ray.rllib.utils.compression import pack, unpack, is_compressed
 from ray.rllib.utils.memory import concat_aligned
 from ray.rllib.utils.deprecation import deprecation_warning
-from ray.rllib.utils.types import TensorType
+from ray.rllib.utils.typing import TensorType
 
 # Default policy id for single agent environments
 DEFAULT_POLICY_ID = "default_policy"

rllib/policy/tf_policy.py

@@ -17,7 +17,8 @@ from ray.rllib.utils.debug import summarize
 from ray.rllib.utils.framework import try_import_tf, get_variable
 from ray.rllib.utils.schedules import ConstantSchedule, PiecewiseSchedule
 from ray.rllib.utils.tf_run_builder import TFRunBuilder
-from ray.rllib.utils.types import ModelGradients, TensorType, TrainerConfigDict
+from ray.rllib.utils.typing import ModelGradients, TensorType, \
+    TrainerConfigDict
 
 tf1, tf, tfv = try_import_tf()
 logger = logging.getLogger(__name__)

rllib/policy/tf_policy_template.py

@@ -9,7 +9,8 @@ from ray.rllib.policy.sample_batch import SampleBatch
 from ray.rllib.policy.tf_policy import TFPolicy
 from ray.rllib.utils import add_mixins
 from ray.rllib.utils.annotations import override, DeveloperAPI
-from ray.rllib.utils.types import ModelGradients, TensorType, TrainerConfigDict
+from ray.rllib.utils.typing import ModelGradients, TensorType, \
+    TrainerConfigDict
 
 
 @DeveloperAPI

rllib/policy/torch_policy.py

@@ -19,7 +19,7 @@ from ray.rllib.utils.schedules import ConstantSchedule, PiecewiseSchedule
 from ray.rllib.utils.torch_ops import convert_to_non_torch_type, \
     convert_to_torch_tensor
 from ray.rllib.utils.tracking_dict import UsageTrackingDict
-from ray.rllib.utils.types import ModelGradients, ModelWeights, \
+from ray.rllib.utils.typing import ModelGradients, ModelWeights, \
     TensorType, TrainerConfigDict
 
 torch, _ = try_import_torch()

rllib/policy/torch_policy_template.py

@@ -13,7 +13,7 @@ from ray.rllib.utils import add_mixins, force_list
 from ray.rllib.utils.annotations import override, DeveloperAPI
 from ray.rllib.utils.framework import try_import_torch
 from ray.rllib.utils.torch_ops import convert_to_non_torch_type
-from ray.rllib.utils.types import TensorType, TrainerConfigDict
+from ray.rllib.utils.typing import TensorType, TrainerConfigDict
 
 torch, _ = try_import_torch()
 

rllib/utils/exploration/curiosity.py

@@ -27,7 +27,7 @@ from ray.rllib.models.torch.misc import SlimFC
 from ray.rllib.utils.exploration.exploration import Exploration
 from ray.rllib.utils.framework import try_import_torch, TensorType
 from ray.rllib.utils.from_config import from_config
-from ray.rllib.utils.types import SampleBatchType, TrainerConfigDict
+from ray.rllib.utils.typing import SampleBatchType, TrainerConfigDict
 
 torch, nn = try_import_torch()
 

rllib/utils/framework.py

@@ -3,7 +3,7 @@ import os
 import sys
 from typing import Any, Optional
 
-from ray.rllib.utils.types import TensorStructType, TensorShape, TensorType
+from ray.rllib.utils.typing import TensorStructType, TensorShape, TensorType
 
 logger = logging.getLogger(__name__)
 

rllib/utils/schedules/polynomial_schedule.py

@@ -3,7 +3,7 @@ from typing import Union
 from ray.rllib.utils.annotations import override
 from ray.rllib.utils.framework import try_import_tf, try_import_torch
 from ray.rllib.utils.schedules.schedule import Schedule
-from ray.rllib.utils.types import TensorType
+from ray.rllib.utils.typing import TensorType
 
 tf1, tf, tfv = try_import_tf()
 torch, _ = try_import_torch()