Remove (object) from class declarations. (#6658)

python/ray/experimental/actor_pool.py

@@ -5,7 +5,7 @@ from __future__ import print_function
 import ray
 
 
-class ActorPool(object):
+class ActorPool:
     """Utility class to operate on a fixed pool of actors.
 
     Arguments:

python/ray/experimental/array/distributed/core.py

@@ -9,7 +9,7 @@ import ray
 BLOCK_SIZE = 10
 
 
-class DistArray(object):
+class DistArray:
     def __init__(self, shape, objectids=None):
         self.shape = shape
         self.ndim = len(shape)

python/ray/experimental/async_api.py

@@ -15,7 +15,7 @@ transport = None
 protocol = None
 
 
-class _ThreadSafeProxy(object):
+class _ThreadSafeProxy:
     """This class is used to create a thread-safe proxy for a given object.
         Every method call will be guarded with a lock.
 

python/ray/experimental/gcs_flush_policy.py

@@ -9,7 +9,7 @@ import ray
 import ray.cloudpickle as pickle
 
 
-class GcsFlushPolicy(object):
+class GcsFlushPolicy:
     """Experimental: a policy to control GCS flushing.
 
     Used by Monitor to enable automatic control of memory usage.

python/ray/experimental/multiprocessing/pool.py

@@ -105,7 +105,7 @@ class ResultThread(threading.Thread):
             raise TimeoutError
 
 
-class AsyncResult(object):
+class AsyncResult:
     """An asynchronous interface to task results.
 
     This should not be constructed directly.
@@ -168,7 +168,7 @@ class AsyncResult(object):
         return not self._result_thread.got_error()
 
 
-class IMapIterator(object):
+class IMapIterator:
     """Base class for OrderedIMapIterator and UnorderedIMapIterator."""
 
     def __init__(self, pool, func, iterable, chunksize=None):
@@ -273,7 +273,7 @@ class UnorderedIMapIterator(IMapIterator):
 
 
 @ray.remote
-class PoolActor(object):
+class PoolActor:
     """Actor used to process tasks submitted to a Pool."""
 
     def __init__(self, initializer=None, initargs=None):
@@ -298,7 +298,7 @@ class PoolActor(object):
 
 
 # https://docs.python.org/3/library/multiprocessing.html#module-multiprocessing.pool
-class Pool(object):
+class Pool:
     """A pool of actor processes that is used to process tasks in parallel.
 
     Args:

python/ray/experimental/no_return.py

@@ -3,7 +3,7 @@ from __future__ import division
 from __future__ import print_function
 
 
-class NoReturn(object):
+class NoReturn:
     """Do not store the return value in the object store.
 
     If a task returns this object, then Ray will not store this object in the

python/ray/experimental/queue.py

@@ -16,7 +16,7 @@ class Full(Exception):
     pass
 
 
-class Queue(object):
+class Queue:
     """Queue implementation on Ray.
 
     Args:
@@ -132,7 +132,7 @@ class Queue(object):
 
 
 @ray.remote
-class _QueueActor(object):
+class _QueueActor:
     def __init__(self, maxsize):
         self.maxsize = maxsize
         self._init(maxsize)

python/ray/experimental/serve/tests/test_metric.py

@@ -8,7 +8,7 @@ from ray.experimental.serve.metric import MetricMonitor
 @pytest.fixture(scope="session")
 def start_target_actor(ray_instance):
     @ray.remote
-    class Target(object):
+    class Target:
         def __init__(self):
             self.counter_value = 0
 

python/ray/experimental/sgd/pytorch/pytorch_runner.py

@@ -17,7 +17,7 @@ from ray.experimental.sgd import utils
 logger = logging.getLogger(__name__)
 
 
-class PyTorchRunner(object):
+class PyTorchRunner:
     """Manages a PyTorch model for training."""
 
     def __init__(self,

python/ray/experimental/sgd/pytorch/pytorch_trainer.py

@@ -21,7 +21,7 @@ from ray.experimental.sgd.pytorch.pytorch_runner import PyTorchRunner
 logger = logging.getLogger(__name__)
 
 
-class PyTorchTrainer(object):
+class PyTorchTrainer:
     """Train a PyTorch model using distributed PyTorch.
 
     Launches a set of actors which connect via distributed PyTorch and

python/ray/experimental/sgd/pytorch/utils.py

@@ -108,7 +108,7 @@ def validate(model, val_iterator, criterion, config):
     return stats
 
 
-class AverageMeter(object):
+class AverageMeter:
     """Computes and stores the average and current value."""
 
     def __init__(self):

python/ray/experimental/sgd/tf/tf_runner.py

@@ -20,7 +20,7 @@ def _try_import_strategy():
     return tf.distribute.experimental.MultiWorkerMirroredStrategy
 
 
-class TFRunner(object):
+class TFRunner:
     """Manages a TensorFlow model for training."""
 
     def __init__(self, model_creator, data_creator, config=None,

python/ray/experimental/sgd/tf/tf_trainer.py

@@ -16,7 +16,7 @@ from ray.experimental.sgd.tf.tf_runner import TFRunner
 logger = logging.getLogger(__name__)
 
 
-class TFTrainer(object):
+class TFTrainer:
     def __init__(self,
                  model_creator,
                  data_creator,

python/ray/experimental/sgd/utils.py

@@ -8,7 +8,7 @@ import socket
 import time
 
 
-class TimerStat(object):
+class TimerStat:
     """A running stat for conveniently logging the duration of a code block.
 
     Note that this class is *not* thread-safe.
@@ -108,7 +108,7 @@ def find_free_port():
         return s.getsockname()[1]
 
 
-class AverageMeter(object):
+class AverageMeter:
     """Computes and stores the average and current value."""
 
     def __init__(self):

python/ray/experimental/signal.py

@@ -18,7 +18,7 @@ ACTOR_DIED_STR = "ACTOR_DIED_SIGNAL"
 logger = logging.getLogger(__name__)
 
 
-class Signal(object):
+class Signal:
     """Base class for Ray signals."""
     pass
 

python/ray/experimental/tf_utils.py

@@ -22,7 +22,7 @@ def unflatten(vector, shapes):
     return arrays
 
 
-class TensorFlowVariables(object):
+class TensorFlowVariables:
     """A class used to set and get weights for Tensorflow networks.
 
     Attributes: