Resolves #812 (#815)

Author: LuNoX

keras_tuner/distribute/oracle_client.py

@@ -23,7 +23,7 @@
 from keras_tuner.protos import service_pb2_grpc
 
 
-class OracleClient(object):
+class OracleClient:
     """Wraps an `Oracle` on a worker to send requests to the chief."""
 
     def __init__(self, oracle):

keras_tuner/engine/base_tuner_test.py

@@ -47,7 +47,7 @@ def get_best_models(self, num_models=1):
             return models
 
     def build_model(hp):
-        class MyModel(object):
+        class MyModel:
             def __init__(self):
                 self.factor = hp.Float("a", 0, 10)
 

keras_tuner/engine/conditions.py

@@ -24,7 +24,7 @@
 
 
 @six.add_metaclass(abc.ABCMeta)
-class Condition(object):
+class Condition:
     """Abstract condition for a conditional hyperparameter.
 
     Subclasses of this object can be passed to a `HyperParameter` to specify

keras_tuner/engine/hypermodel.py

@@ -16,7 +16,7 @@
 from keras_tuner import errors
 
 
-class HyperModel(object):
+class HyperModel:
     """Defines a search space of models.
 
     A search space is a collection of models. The `build` function will build

keras_tuner/engine/hyperparameters/hyperparameter.py

@@ -18,7 +18,7 @@
 from keras_tuner.engine import conditions as conditions_mod
 
 
-class HyperParameter(object):
+class HyperParameter:
     """Hyperparameter base class.
 
     A `HyperParameter` instance is uniquely identified by its `name` and

keras_tuner/engine/hyperparameters/hyperparameters.py

@@ -25,7 +25,7 @@
 from keras_tuner.protos import keras_tuner_pb2
 
 
-class HyperParameters(object):
+class HyperParameters:
     """Container for both a hyperparameter space, and current values.
 
     A `HyperParameters` instance can be pass to `HyperModel.build(hp)` as an

keras_tuner/engine/logger.py

@@ -27,7 +27,7 @@
 UPLOAD_ERROR = 4
 
 
-class Logger(object):
+class Logger:
     def register_tuner(self, tuner_state):
         """Informs the logger that a new search is starting."""
         raise NotImplementedError

keras_tuner/engine/logger_test.py

@@ -20,11 +20,11 @@
 import keras_tuner
 
 
-class OkResponse(object):
+class OkResponse:
     ok = True
 
 
-class MockPost(object):
+class MockPost:
     def __init__(self):
         self.url_calls = []
 

keras_tuner/engine/metrics_tracking.py

@@ -20,7 +20,7 @@
 from keras_tuner.protos import keras_tuner_pb2
 
 
-class MetricObservation(object):
+class MetricObservation:
     """Metric value at a given step of training across multiple executions.
 
     If the model is trained multiple
@@ -73,7 +73,7 @@ def from_proto(cls, proto):
         return cls(value=list(proto.value), step=proto.step)
 
 
-class MetricHistory(object):
+class MetricHistory:
     """Record of multiple executions of a single metric.
 
     It contains a collection of `MetricObservation` instances.
@@ -176,7 +176,7 @@ def from_proto(cls, proto):
         return instance
 
 
-class MetricsTracker(object):
+class MetricsTracker:
     """Record of the values of multiple executions of all metrics.
 
     It contains `MetricHistory` instances for the metrics.

keras_tuner/engine/stateful.py

@@ -19,7 +19,7 @@
 import tensorflow as tf
 
 
-class Stateful(object):
+class Stateful:
     """The base class for saving and restoring the state.
 
     The functionalities in this class is for the user to resume a previously