refactor-ruff-b024

Signed-off-by: SimoTw <[email protected]>

add

Signed-off-by: SimoTw <[email protected]>

pyproject.toml

@@ -34,7 +34,6 @@ ignore = [
     "F841",
     "B018",
     "B023",
-    "B024",
     "B026",
     "B027",
     "B035",

python/ray/_private/runtime_env/plugin.py

@@ -21,7 +21,7 @@
 
 
 @DeveloperAPI
-class RuntimeEnvPlugin(ABC):
+class RuntimeEnvPlugin(ABC):  # noqa: B024
     """Abstract base class for runtime environment plugins."""
 
     name: str = None

python/ray/air/_internal/device_manager/torch_device_manager.py

@@ -2,39 +2,47 @@
 from typing import List, Union
 
 import torch
+import abc
 
 
 class TorchDeviceManager(ABC):
     """This class contains the function needed for supporting
     an acclerator family in Ray AI Library.
     """
 
+    @abc.abstractmethod
     def is_available(self) -> bool:
         """Validate if device is available."""
-        ...
+        raise NotImplementedError
 
+    @abc.abstractmethod
     def get_devices(self) -> List[torch.device]:
         """Gets the correct torch device configured for this process"""
-        ...
+        raise NotImplementedError
 
+    @abc.abstractmethod
     def set_device(self, device: Union[torch.device, int, str, None]):
         """Set the correct device for this process"""
-        ...
+        raise NotImplementedError
 
+    @abc.abstractmethod
     def supports_stream(self) -> bool:
         """Validate if the device type support create a stream"""
-        ...
+        raise NotImplementedError
 
+    @abc.abstractmethod
     def create_stream(self, device: torch.device):
         """Create a device stream"""
-        ...
+        raise NotImplementedError
 
+    @abc.abstractmethod
     def get_stream_context(self, stream):
         """Get a stream context of device. If device didn't support stream,
-        this should return a empty context manager instead of  None.
+        this should return a empty context manager instead of None.
         """
-        ...
+        raise NotImplementedError
 
+    @abc.abstractmethod
     def get_current_stream(self):
         """Get current stream on accelerators like torch.cuda.current_stream"""
-        ...
+        raise NotImplementedError

python/ray/air/execution/resources/resource_manager.py

@@ -62,6 +62,7 @@ class ResourceManager(abc.ABC):
 
     """
 
+    @abc.abstractmethod
     def request_resources(self, resource_request: ResourceRequest):
         """Request resources.
 
@@ -75,6 +76,7 @@ def request_resources(self, resource_request: ResourceRequest):
         """
         raise NotImplementedError
 
+    @abc.abstractmethod
     def cancel_resource_request(self, resource_request: ResourceRequest):
         """Cancel resource request.
 
@@ -84,10 +86,12 @@ def cancel_resource_request(self, resource_request: ResourceRequest):
         """
         raise NotImplementedError
 
+    @abc.abstractmethod
     def has_resources_ready(self, resource_request: ResourceRequest) -> bool:
         """Returns True if resources for the given request are ready to be acquired."""
         raise NotImplementedError
 
+    @abc.abstractmethod
     def acquire_resources(
         self, resource_request: ResourceRequest
     ) -> Optional[AcquiredResources]:
@@ -98,6 +102,7 @@ def acquire_resources(
         """
         raise NotImplementedError
 
+    @abc.abstractmethod
     def free_resources(self, acquired_resource: AcquiredResources):
         """Free acquired resources from usage and return them to the resource manager.
 
@@ -132,6 +137,7 @@ def update_state(self):
         """
         pass
 
+    @abc.abstractmethod
     def clear(self):
         """Reset internal state and clear all resources.
 

python/ray/air/util/torch_dist.py

@@ -6,7 +6,6 @@
 """
 
 import os
-from abc import ABC
 from collections import defaultdict
 from datetime import timedelta
 from typing import Callable, List, T
@@ -20,7 +19,7 @@
 from ray.train._internal.utils import get_address_and_port
 
 
-class TorchDistributedWorker(ABC):
+class TorchDistributedWorker:
     """Defines the interfaces required by the init_torch_dist_process_group().
 
     This is modeled after RayTrainerWorker, which allows arbitrary functions

python/ray/data/preprocessor.py

@@ -184,6 +184,7 @@ def transform_batch(self, data: "DataBatchType") -> "DataBatchType":
         return self._transform_batch(data)
 
     @DeveloperAPI
+    @abc.abstractmethod
     def _fit(self, ds: "Dataset") -> "Preprocessor":
         """Sub-classes should override this instead of fit()."""
         raise NotImplementedError()

python/ray/tests/spark/test_basic.py

@@ -7,7 +7,6 @@
 import pytest
 import sys
 from unittest import mock
-from abc import ABC
 
 import ray
 
@@ -66,7 +65,7 @@ def _setup_ray_cluster(*args, **kwds):
 _logger = logging.getLogger(__name__)
 
 
-class RayOnSparkCPUClusterTestBase(ABC):
+class RayOnSparkCPUClusterTestBase:
     spark = None
     num_total_cpus = None
     num_total_gpus = None

python/ray/train/_internal/accelerator.py

@@ -1,5 +1,5 @@
 import abc
 
 
-class Accelerator(abc.ABC):
+class Accelerator(abc.ABC):  # noqa: B024
     """A utility that contains methods to accelerate training."""

python/ray/tune/logger/logger.py

@@ -54,6 +54,7 @@ def __init__(self, config: Dict, logdir: str, trial: Optional["Trial"] = None):
     def _init(self):
         pass
 
+    @abc.abstractmethod
     def on_result(self, result):
         """Given a result, appends it to the existing log."""
 

python/ray/tune/stopper/stopper.py

@@ -44,10 +44,12 @@ class Stopper(abc.ABC):
 
     """
 
+    @abc.abstractmethod
     def __call__(self, trial_id: str, result: Dict[str, Any]) -> bool:
         """Returns true if the trial should be terminated given the result."""
         raise NotImplementedError
 
+    @abc.abstractmethod
     def stop_all(self) -> bool:
         """Returns true if the experiment should be terminated."""
         raise NotImplementedError

python/ray/tune/tune.py

@@ -258,6 +258,7 @@ def _ray_auto_init(entrypoint: str):
 
 
 class _Config(abc.ABC):
+    @abc.abstractmethod
     def to_dict(self) -> dict:
         """Converts this configuration to a dict format."""
         raise NotImplementedError

python/ray/util/state/common.py

@@ -3,7 +3,6 @@
 import logging
 import sys
 import warnings
-from abc import ABC
 from dataclasses import asdict, field, fields
 from enum import Enum, unique
 from typing import Any, Dict, List, Optional, Set, Tuple, Union
@@ -244,7 +243,7 @@ def state_column(*, filterable: bool, detail: bool = False, format_fn=None, **kw
     return field(**kwargs)
 
 
-class StateSchema(ABC):
+class StateSchema:
     """Schema class for Ray resource abstraction.
 
     The child class must be dataclass. All child classes

release/ray_release/cluster_manager/cluster_manager.py

@@ -119,12 +119,15 @@ def _annotate_cluster_compute(
         )
         return cluster_compute
 
+    @abc.abstractmethod
     def build_configs(self, timeout: float = 30.0):
         raise NotImplementedError
 
+    @abc.abstractmethod
     def delete_configs(self):
         raise NotImplementedError
 
+    @abc.abstractmethod
     def start_cluster(self, timeout: float = 600.0):
         raise NotImplementedError
 
@@ -134,9 +137,11 @@ def terminate_cluster(self, wait: bool = False):
         except Exception as e:
             logger.exception(f"Could not terminate cluster: {e}")
 
+    @abc.abstractmethod
     def terminate_cluster_ex(self, wait: bool = False):
         raise NotImplementedError
 
+    @abc.abstractmethod
     def get_cluster_address(self) -> str:
         raise NotImplementedError
 

release/ray_release/command_runner/command_runner.py

@@ -57,14 +57,17 @@ def get_full_command_env(self, env: Optional[Dict] = None):
 
         return full_env
 
+    @abc.abstractmethod
     def prepare_local_env(self, ray_wheels_url: Optional[str] = None):
         """Prepare local environment, e.g. install dependencies."""
         raise NotImplementedError
 
+    @abc.abstractmethod
     def prepare_remote_env(self):
         """Prepare remote environment, e.g. upload files."""
         raise NotImplementedError
 
+    @abc.abstractmethod
     def wait_for_nodes(self, num_nodes: int, timeout: float = 900.0):
         """Wait for cluster nodes to be up.
 
@@ -81,6 +84,7 @@ def wait_for_nodes(self, num_nodes: int, timeout: float = 900.0):
         """
         raise NotImplementedError
 
+    @abc.abstractmethod
     def save_metrics(self, start_time: float, timeout: float = 900.0):
         """Obtains Prometheus metrics from head node and saves them
         to ``self.metrics_output_json``.
@@ -94,6 +98,7 @@ def save_metrics(self, start_time: float, timeout: float = 900.0):
         """
         raise NotImplementedError
 
+    @abc.abstractmethod
     def run_command(
         self,
         command: str,
@@ -127,14 +132,18 @@ def get_last_logs(self) -> Optional[str]:
             logger.exception(f"Error fetching logs: {e}")
             return None
 
+    @abc.abstractmethod
     def get_last_logs_ex(self):
         raise NotImplementedError
 
+    @abc.abstractmethod
     def fetch_results(self) -> Dict[str, Any]:
         raise NotImplementedError
 
+    @abc.abstractmethod
     def fetch_metrics(self) -> Dict[str, Any]:
         raise NotImplementedError
 
+    @abc.abstractmethod
     def fetch_artifact(self, artifact_path):
         raise NotImplementedError

release/ray_release/file_manager/file_manager.py

@@ -8,13 +8,15 @@ class FileManager(abc.ABC):
     def __init__(self, cluster_manager: ClusterManager):
         self.cluster_manager = cluster_manager
 
+    @abc.abstractmethod
     def upload(self, source: Optional[str] = None, target: Optional[str] = None):
         """Upload source to target.
 
         Infers target dir from basename if not stated.
         """
         raise NotImplementedError
 
+    @abc.abstractmethod
     def download(self, source: str, target: str):
         """Download source_dir to target_dir."""
         raise NotImplementedError

rllib/connectors/connector.py

@@ -105,6 +105,7 @@ def in_eval(self):
     def __str__(self, indentation: int = 0):
         return " " * indentation + self.__class__.__name__
 
+    @abc.abstractmethod
     def to_state(self) -> Tuple[str, Any]:
         """Serialize a connector into a JSON serializable Tuple.
 
@@ -333,7 +334,7 @@ def transform(self, ac_data: ActionConnectorDataType) -> ActionConnectorDataType
 
 
 @OldAPIStack
-class ConnectorPipeline(abc.ABC):
+class ConnectorPipeline:
     """Utility class for quick manipulation of a connector pipeline."""
 
     def __init__(self, ctx: ConnectorContext, connectors: List[Connector]):