Switch class definitions to py3 conventions.

PiperOrigin-RevId: 387224410

keras/backend_test.py

@@ -2143,7 +2143,7 @@ def test_function_tf_run_options_with_run_metadata(self):
 
   def test_function_fetch_callbacks(self):
 
-    class CallbackStub(object):
+    class CallbackStub:
 
       def __init__(self):
         self.times_called = 0

keras/benchmarks/distribution_util.py

@@ -176,7 +176,7 @@ def get_strategy_scope(strategy):
   return strategy_scope
 
 
-class DummyContextManager(object):
+class DummyContextManager:
 
   def __enter__(self):
     pass

keras/callbacks_test.py

@@ -1215,7 +1215,7 @@ def test_EarlyStopping_with_baseline(self):
 
   def test_EarlyStopping_final_weights_when_restoring_model_weights(self):
 
-    class DummyModel(object):
+    class DummyModel:
 
       def __init__(self):
         self.stop_training = False
@@ -1415,12 +1415,12 @@ def make_model():
 
   def test_ReduceLROnPlateau_patience(self):
 
-    class DummyOptimizer(object):
+    class DummyOptimizer:
 
       def __init__(self):
         self.lr = keras.backend.variable(1.0)
 
-    class DummyModel(object):
+    class DummyModel:
 
       def __init__(self):
         self.optimizer = DummyOptimizer()
@@ -2015,7 +2015,7 @@ def on_train_batch_end(self, batch, logs=None):
 _ObservedSummary = collections.namedtuple('_ObservedSummary', ('logdir', 'tag'))
 
 
-class _SummaryFile(object):
+class _SummaryFile:
   """A record of summary tags and the files to which they were written.
 
   Fields `scalars`, `images`, `histograms`, and `tensors` are sets

keras/callbacks_v1_test.py

@@ -226,7 +226,7 @@ def callbacks_factory(histogram_freq):
 
   def test_Tensorboard_histogram_summaries_in_test_function(self):
 
-    class FileWriterStub(object):
+    class FileWriterStub:
 
       def __init__(self, logdir, graph=None):
         self.logdir = logdir
@@ -387,7 +387,7 @@ def test_TensorBoard_with_ReduceLROnPlateau(self):
 
   def test_Tensorboard_batch_logging(self):
 
-    class FileWriterStub(object):
+    class FileWriterStub:
 
       def __init__(self, logdir, graph=None):
         self.logdir = logdir
@@ -422,7 +422,7 @@ def close(self):
 
   def test_Tensorboard_epoch_and_batch_logging(self):
 
-    class FileWriterStub(object):
+    class FileWriterStub:
 
       def __init__(self, logdir, graph=None):
         self.logdir = logdir
@@ -496,7 +496,7 @@ def test_Tensorboard_eager(self):
 
   def test_TensorBoard_update_freq(self):
 
-    class FileWriterStub(object):
+    class FileWriterStub:
 
       def __init__(self, logdir, graph=None):
         self.logdir = logdir

keras/distribute/ctl_correctness_test.py

@@ -30,7 +30,7 @@
 _STEPS_PER_EPOCH = 2
 
 
-class MaybeStrategyScope(object):
+class MaybeStrategyScope:
   """Provides a context allowing no distribution strategy."""
 
   def __init__(self, strategy):

keras/distribute/distribute_coordinator_utils.py

@@ -47,7 +47,7 @@ def get_current_worker_context():
     return None
 
 
-class _TaskType(object):
+class _TaskType:
   PS = "ps"
   WORKER = "worker"
   CHIEF = "chief"
@@ -63,7 +63,7 @@ def _get_num_workers(cluster_spec):
       cluster_spec.as_dict().get(_TaskType.CHIEF, []))
 
 
-class _WorkerContext(object):
+class _WorkerContext:
   """The worker context class.
 
   This context object provides configuration information for each task. One
@@ -377,7 +377,7 @@ def _run_std_server(cluster_spec=None,
   if rpc_layer:
     target = rpc_layer + "://" + target
 
-  class _FakeServer(object):
+  class _FakeServer:
     """A fake server that runs a master session."""
 
     def start(self):

keras/distribute/distributed_file_utils_test.py

@@ -23,25 +23,25 @@
 
 class DistributedFileUtilsTest(tf.test.TestCase):
 
-  class MockedExtended(object):
+  class MockedExtended:
     pass
 
-  class MockedChiefStrategy(object):
+  class MockedChiefStrategy:
 
     def __init__(self):
       self.extended = DistributedFileUtilsTest.MockedExtended()
       self.extended._in_multi_worker_mode = lambda: True
       self.extended.should_checkpoint = True
 
-  class MockedWorkerStrategy(object):
+  class MockedWorkerStrategy:
 
     def __init__(self):
       self.extended = DistributedFileUtilsTest.MockedExtended()
       self.extended._in_multi_worker_mode = lambda: True
       self.extended.should_checkpoint = False
       self.extended._task_id = 3
 
-  class MockedSingleWorkerStrategy(object):
+  class MockedSingleWorkerStrategy:
 
     def __init__(self):
       self.extended = DistributedFileUtilsTest.MockedExtended()

keras/distribute/keras_correctness_test_base.py

@@ -114,7 +114,7 @@ def multi_worker_mirrored_eager_and_graph():
       eager_mode_test_configuration() + graph_mode_test_configuration())
 
 
-class MaybeDistributionScope(object):
+class MaybeDistributionScope:
   """Provides a context allowing no distribution strategy."""
 
   def __init__(self, distribution):

keras/distribute/sidecar_evaluator.py

@@ -44,7 +44,7 @@ def list_checkpoint_attributes(ckpt_dir_or_file):
 
 
 @keras_export('keras.experimental.SidecarEvaluator', v1=[])
-class SidecarEvaluator(object):
+class SidecarEvaluator:
   """A class designed for a dedicated evaluator task.
 
   `SidecarEvaluator` is expected to be run in a process on a separate machine

keras/distribute/worker_training_state.py

@@ -28,7 +28,7 @@
 CKPT_SAVED_EPOCH_UNUSED_VALUE = -1
 
 
-class WorkerTrainingState(object):
+class WorkerTrainingState:
   """Training state management class.
 
   This class provides apis for backing up and restoring the training state.

keras/engine/base_layer_utils.py

@@ -423,7 +423,7 @@ def call_context():
 tf.__internal__.register_call_context_function(call_context)
 
 
-class CallContext(object):
+class CallContext:
   """Keeps track of properties currently inside a Layer/Model's `call`.
 
   Attributes:
@@ -512,7 +512,7 @@ def in_keras_graph(self):
             getattr(backend.get_graph(), 'name', None) == 'keras_graph')
 
 
-class CallContextManager(object):
+class CallContextManager:
   """Context manager for `CallContext`."""
 
   def __init__(self, call_ctx, state):
@@ -769,7 +769,7 @@ def v2_dtype_behavior_enabled():
   return V2_DTYPE_BEHAVIOR
 
 
-class TrackableWeightHandler(object):
+class TrackableWeightHandler:
   """Keras wrapper for handling tracking.Trackable object saving and restoring.
 
   This class handles Trackables in both V1 and V2 modes, ensuring that they can

keras/engine/compile_utils.py

@@ -24,7 +24,7 @@
 from keras.utils import tf_utils
 
 
-class Container(object):
+class Container:
   """Base Container class."""
 
   def __init__(self, output_names=None):

keras/engine/compile_utils_test.py

@@ -346,7 +346,7 @@ def test_custom_loss_callables(self):
     def custom_loss_fn(y_true, y_pred):
       return tf.reduce_sum(y_true - y_pred)
 
-    class CustomLossClass(object):
+    class CustomLossClass:
 
       def __call__(self, y_true, y_pred):
         return tf.reduce_sum(y_true - y_pred)
@@ -771,7 +771,7 @@ def test_custom_metric_callables(self):
     def custom_metric_fn(y_true, y_pred):
       return tf.reduce_sum(y_true - y_pred)
 
-    class CustomMetricClass(object):
+    class CustomMetricClass:
 
       def __call__(self, y_true, y_pred):
         return tf.reduce_sum(y_true - y_pred)

keras/engine/data_adapter.py

@@ -1086,7 +1086,7 @@ def broadcast_sample_weight_modes(target_structure, sample_weight_modes):
   return sample_weight_modes
 
 
-class DataHandler(object):
+class DataHandler:
   """Handles iterating over epoch-level `tf.data.Iterator` objects."""
 
   def __init__(self,

keras/engine/data_adapter_test.py

@@ -28,7 +28,7 @@
 from keras.utils import data_utils
 
 
-class DummyArrayLike(object):
+class DummyArrayLike:
   """Dummy array-like object."""
 
   def __init__(self, data):

keras/engine/functional_test.py

@@ -1083,7 +1083,7 @@ class Double(layers.Layer):
       def call(self, x1, kwarg=None):
         return x1 + x1
 
-    class NonSerializable(object):
+    class NonSerializable:
 
       def __init__(self, foo=None):
         self.foo = foo
@@ -2443,7 +2443,7 @@ def __init__(self, *args, **kwargs):
     super().__init__(inputs=[my_input], outputs=outputs, *args, **kwargs)
 
 
-class MixinClass(object):
+class MixinClass:
 
   def __init__(self, foo, **kwargs):
     self._foo = foo

keras/engine/input_spec.py

@@ -26,7 +26,7 @@
               v1=['keras.layers.InputSpec',
                   'keras.__internal__.legacy.layers.InputSpec'])
 @tf_export(v1=['layers.InputSpec'])
-class InputSpec(object):
+class InputSpec:
   """Specifies the rank, dtype and shape of every input to a layer.
 
   Layers can expose (if appropriate) an `input_spec` attribute:

keras/engine/keras_tensor.py

@@ -27,7 +27,7 @@
 _MAX_TENSOR_RANK = 254
 
 
-class KerasTensor(object):
+class KerasTensor:
   """A representation of a Keras in/output during Functional API construction.
 
   `KerasTensor`s are tensor-like objects that represent the symbolic inputs
@@ -535,7 +535,7 @@ def _to_placeholder(self):
     return self._user_registered_symbolic_object
 
 
-class _KerasTensorIterator(object):
+class _KerasTensorIterator:
   """Iterates over the leading dim of a KerasTensor. Performs 0 error checks."""
 
   def __init__(self, tensor, dim0):

keras/engine/partial_batch_padding_handler.py

@@ -21,7 +21,7 @@
 from keras import backend
 
 
-class PartialBatchPaddingHandler(object):
+class PartialBatchPaddingHandler:
   """A container that holds info about partial batches for `predict()`."""
 
   def __init__(self, output_shape):

keras/engine/training_dataset_test.py

@@ -393,7 +393,7 @@ def test_finite_dataset_unknown_cardinality_no_steps_arg(self):
   @keras_parameterized.run_all_keras_modes(always_skip_v1=True)
   def test_finite_dataset_unknown_cardinality_no_step_with_train_and_val(self):
 
-    class CaptureStdout(object):
+    class CaptureStdout:
 
       def __enter__(self):
         self._stdout = sys.stdout

keras/engine/training_utils.py

@@ -115,7 +115,7 @@ def handle_partial_sample_weights(outputs, sample_weights, sample_weight_modes,
           any_sample_weight, partial_sample_weight)
 
 
-class RespectCompiledTrainableState(object):
+class RespectCompiledTrainableState:
   """Set and restore trainable state if it has changed since compile.
 
   The keras API guarantees that the value of each Layer's `trainable` property

keras/engine/training_utils_v1.py

@@ -1694,7 +1694,7 @@ def infer_steps_for_dataset(model,
   return steps
 
 
-class ModelInputs(object):
+class ModelInputs:
   """Encapsulates model inputs.
 
   Allows for transforming model inputs while keeping the same structure.
@@ -1885,7 +1885,7 @@ def unpack_validation_data(validation_data, raise_if_ambiguous=True):
   return val_x, val_y, val_sample_weight
 
 
-class TrainingLoop(object):
+class TrainingLoop:
   """TrainingLoop is a wrapper class around the training logic.
 
   This class is trying to encapsulate the different logic of fit/eval/predict

keras/engine/training_v1.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ==============================================================================
 """V1 Training-related part of the Keras engine."""
-
+# pylint: disable=g-classes-have-attributes
 import tensorflow.compat.v2 as tf
 
 import collections
@@ -2867,7 +2867,7 @@ def __getattr__(self, item):
     return super(DistributedCallbackModel, self).__getattr__(item)
 
 
-class _TrainingEndpoint(object):
+class _TrainingEndpoint:
   """A container for the training output/target and related entities.
 
   In the case of model with multiple outputs, there is a one-to-one mapping
@@ -3099,7 +3099,7 @@ def populate_sample_weight(self, sample_weight, sample_weight_mode):
           name=self.output_name + '_sample_weights')
 
 
-class _TrainingTarget(object):
+class _TrainingTarget:
   """Container for a target tensor (y_true) and its metadata (shape, loss...).
 
   Args:

keras/initializers/initializers_v2.py

@@ -27,7 +27,7 @@
 
 
 @keras_export('keras.initializers.Initializer')
-class Initializer(object):
+class Initializer:
   """Initializer base class: all Keras initializers inherit from this class.
 
   Initializers should implement a `__call__` method with the following
@@ -943,7 +943,7 @@ def _assert_float_dtype(dtype):
   return dtype
 
 
-class _RandomGenerator(object):
+class _RandomGenerator:
   """Random generator that selects appropriate random ops."""
 
   def __init__(self, seed=None):

keras/layers/__init__.py

@@ -253,7 +253,7 @@
 from keras.layers.serialization import serialize
 
 
-class VersionAwareLayers(object):
+class VersionAwareLayers:
   """Utility to be used internally to access layers in a V1/V2-aware fashion.
 
   When using layers within the Keras codebase, under the constraint that