Style Fix (#4923)

* Style Fix

* Style Fix

docs/autogen.py

@@ -312,7 +312,7 @@ def get_function_signature(function, method=True):
     for a in args:
         st += str(a) + ', '
     for a, v in kwargs:
-        if type(v) == str:
+        if isinstance(v, str):
             v = '\'' + v + '\''
         st += str(a) + '=' + str(v) + ', '
     if kwargs or args:

examples/deep_dream.py

@@ -140,7 +140,7 @@ loss += settings['dream_l2'] * K.sum(K.square(dream)) / np.prod(img_size)
 grads = K.gradients(loss, dream)
 
 outputs = [loss]
-if type(grads) in {list, tuple}:
+if isinstance(grads, (list, tuple)):
     outputs += grads
 else:
     outputs.append(grads)

examples/neural_doodle.py

@@ -301,7 +301,7 @@ loss_grads = K.gradients(loss, target_image)
 
 # Evaluator class for computing efficiency
 outputs = [loss]
-if type(loss_grads) in {list, tuple}:
+if isinstance(loss_grads, (list, tuple)):
     outputs += loss_grads
 else:
     outputs.append(loss_grads)

examples/neural_style_transfer.py

@@ -208,7 +208,7 @@ loss += total_variation_weight * total_variation_loss(combination_image)
 grads = K.gradients(loss, combination_image)
 
 outputs = [loss]
-if type(grads) in {list, tuple}:
+if isinstance(grads, (list, tuple)):
     outputs += grads
 else:
     outputs.append(grads)

keras/layers/advanced_activations.py

@@ -71,7 +71,7 @@ class PReLU(Layer):
         self.supports_masking = True
         self.init = initializations.get(init)
         self.initial_weights = weights
-        if type(shared_axes) is not list and type(shared_axes) is not tuple:
+        if not isinstance(shared_axes, (list, tuple)):
             self.shared_axes = [shared_axes]
         else:
             self.shared_axes = list(shared_axes)
@@ -174,7 +174,7 @@ class ParametricSoftplus(Layer):
         self.alpha_init = K.cast_to_floatx(alpha_init)
         self.beta_init = K.cast_to_floatx(beta_init)
         self.initial_weights = weights
-        if type(shared_axes) is not list and type(shared_axes) is not tuple:
+        if not isinstance(shared_axes, (list, tuple)):
             self.shared_axes = [shared_axes]
         else:
             self.shared_axes = list(shared_axes)
@@ -279,7 +279,7 @@ class SReLU(Layer):
         self.a_left_init = a_left_init
         self.t_right_init = t_right_init
         self.a_right_init = a_right_init
-        if type(shared_axes) is not list and type(shared_axes) is not tuple:
+        if not isinstance(shared_axes, (list, tuple)):
             self.shared_axes = [shared_axes]
         else:
             self.shared_axes = list(shared_axes)

keras/utils/layer_utils.py

@@ -126,7 +126,7 @@ def count_total_params(layers, layer_set=None):
         if layer in layer_set:
             continue
         layer_set.add(layer)
-        if type(layer) in (Model, Sequential):
+        if isinstance(layer, (Model, Sequential)):
             t, nt = count_total_params(layer.layers, layer_set)
             trainable_count += t
             non_trainable_count += nt