Merge pull request #47873 from zenogantner:keras-losses-python3

PiperOrigin-RevId: 365854152
Change-Id: Ib6a4f0beb6a49903496186416ffc316f12723549

tensorflow/python/keras/losses.py

@@ -238,7 +238,7 @@ def __init__(self,
       name: (Optional) name for the loss.
       **kwargs: The keyword arguments that are passed on to `fn`.
     """
-    super(LossFunctionWrapper, self).__init__(reduction=reduction, name=name)
+    super().__init__(reduction=reduction, name=name)
     self.fn = fn
     self._fn_kwargs = kwargs
 
@@ -262,7 +262,7 @@ def get_config(self):
     config = {}
     for k, v in self._fn_kwargs.items():
       config[k] = backend.eval(v) if tf_utils.is_tensor_or_variable(v) else v
-    base_config = super(LossFunctionWrapper, self).get_config()
+    base_config = super().get_config()
     return dict(list(base_config.items()) + list(config.items()))
 
 
@@ -321,8 +321,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'mean_squared_error'.
     """
-    super(MeanSquaredError, self).__init__(
-        mean_squared_error, name=name, reduction=reduction)
+    super().__init__(mean_squared_error, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.MeanAbsoluteError')
@@ -380,8 +379,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'mean_absolute_error'.
     """
-    super(MeanAbsoluteError, self).__init__(
-        mean_absolute_error, name=name, reduction=reduction)
+    super().__init__(mean_absolute_error, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.MeanAbsolutePercentageError')
@@ -441,7 +439,7 @@ def __init__(self,
       name: Optional name for the op. Defaults to
         'mean_absolute_percentage_error'.
     """
-    super(MeanAbsolutePercentageError, self).__init__(
+    super().__init__(
         mean_absolute_percentage_error, name=name, reduction=reduction)
 
 
@@ -502,7 +500,7 @@ def __init__(self,
       name: Optional name for the op. Defaults to
         'mean_squared_logarithmic_error'.
     """
-    super(MeanSquaredLogarithmicError, self).__init__(
+    super().__init__(
         mean_squared_logarithmic_error, name=name, reduction=reduction)
 
 
@@ -596,7 +594,7 @@ def __init__(self,
             more details.
       name: (Optional) Name for the op. Defaults to 'binary_crossentropy'.
     """
-    super(BinaryCrossentropy, self).__init__(
+    super().__init__(
         binary_crossentropy,
         name=name,
         reduction=reduction,
@@ -675,7 +673,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'categorical_crossentropy'.
     """
-    super(CategoricalCrossentropy, self).__init__(
+    super().__init__(
         categorical_crossentropy,
         name=name,
         reduction=reduction,
@@ -752,7 +750,7 @@ def __init__(self,
       name: Optional name for the op. Defaults to
         'sparse_categorical_crossentropy'.
     """
-    super(SparseCategoricalCrossentropy, self).__init__(
+    super().__init__(
         sparse_categorical_crossentropy,
         name=name,
         reduction=reduction,
@@ -815,7 +813,7 @@ def __init__(self, reduction=losses_utils.ReductionV2.AUTO, name='hinge'):
             more details.
       name: Optional name for the op. Defaults to 'hinge'.
     """
-    super(Hinge, self).__init__(hinge, name=name, reduction=reduction)
+    super().__init__(hinge, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.SquaredHinge')
@@ -876,8 +874,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'squared_hinge'.
     """
-    super(SquaredHinge, self).__init__(
-        squared_hinge, name=name, reduction=reduction)
+    super().__init__(squared_hinge, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.CategoricalHinge')
@@ -936,8 +933,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'categorical_hinge'.
     """
-    super(CategoricalHinge, self).__init__(
-        categorical_hinge, name=name, reduction=reduction)
+    super().__init__(categorical_hinge, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.Poisson')
@@ -993,7 +989,7 @@ def __init__(self, reduction=losses_utils.ReductionV2.AUTO, name='poisson'):
             more details.
       name: Optional name for the op. Defaults to 'poisson'.
     """
-    super(Poisson, self).__init__(poisson, name=name, reduction=reduction)
+    super().__init__(poisson, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.LogCosh')
@@ -1050,7 +1046,7 @@ def __init__(self, reduction=losses_utils.ReductionV2.AUTO, name='log_cosh'):
             more details.
       name: Optional name for the op. Defaults to 'log_cosh'.
     """
-    super(LogCosh, self).__init__(log_cosh, name=name, reduction=reduction)
+    super().__init__(log_cosh, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.KLDivergence')
@@ -1110,8 +1106,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'kl_divergence'.
     """
-    super(KLDivergence, self).__init__(
-        kl_divergence, name=name, reduction=reduction)
+    super().__init__(kl_divergence, name=name, reduction=reduction)
 
 
 @keras_export('keras.losses.Huber')
@@ -1178,8 +1173,7 @@ def __init__(self,
             more details.
       name: Optional name for the op. Defaults to 'huber_loss'.
     """
-    super(Huber, self).__init__(
-        huber, name=name, reduction=reduction, delta=delta)
+    super().__init__(huber, name=name, reduction=reduction, delta=delta)
 
 
 @keras_export('keras.metrics.mean_squared_error', 'keras.metrics.mse',
@@ -1979,7 +1973,7 @@ def __init__(self,
                axis=-1,
                reduction=losses_utils.ReductionV2.AUTO,
                name='cosine_similarity'):
-    super(CosineSimilarity, self).__init__(
+    super().__init__(
         cosine_similarity, reduction=reduction, name=name, axis=axis)
 
 
@@ -2078,11 +2072,10 @@ def get(identifier):
     return deserialize(identifier)
   if isinstance(identifier, dict):
     return deserialize(identifier)
-  elif callable(identifier):
+  if callable(identifier):
     return identifier
-  else:
-    raise ValueError(
-        'Could not interpret loss function identifier: {}'.format(identifier))
+  raise ValueError(
+      f'Could not interpret loss function identifier: {identifier}')
 
 
 LABEL_DTYPES_FOR_LOSSES = {

tensorflow/python/keras/losses_test.py

@@ -1783,7 +1783,7 @@ def test_loss_with_non_default_dtype(self):
 class BinaryTruePositivesViaControlFlow(losses.Loss):
 
   def __init__(self, reduction=losses_utils.ReductionV2.AUTO):
-    super(BinaryTruePositivesViaControlFlow, self).__init__(reduction=reduction)
+    super().__init__(reduction=reduction)
 
   def call(self, y_true, y_pred):
     y_true = math_ops.cast(y_true, dtypes.bool)