Replace add_variable() with add_weight() in official keras layers.

Make it easier for analysis and code search.

PiperOrigin-RevId: 199736646

3 files changed, 63 insertions, 56 deletions

diff --git a/tensorflow/python/keras/layers/convolutional.py b/tensorflow/python/keras/layers/convolutional.py
index ce1c84e98d..9ea341139e 100644
--- a/tensorflow/python/keras/layers/convolutional.py
+++ b/tensorflow/python/keras/layers/convolutional.py
@@ -151,21 +151,23 @@ class Conv(Layer):
     input_dim = int(input_shape[channel_axis])
     kernel_shape = self.kernel_size + (input_dim, self.filters)
 
-    self.kernel = self.add_variable(name='kernel',
-                                    shape=kernel_shape,
-                                    initializer=self.kernel_initializer,
-                                    regularizer=self.kernel_regularizer,
-                                    constraint=self.kernel_constraint,
-                                    trainable=True,
-                                    dtype=self.dtype)
+    self.kernel = self.add_weight(
+        name='kernel',
+        shape=kernel_shape,
+        initializer=self.kernel_initializer,
+        regularizer=self.kernel_regularizer,
+        constraint=self.kernel_constraint,
+        trainable=True,
+        dtype=self.dtype)
     if self.use_bias:
-      self.bias = self.add_variable(name='bias',
-                                    shape=(self.filters,),
-                                    initializer=self.bias_initializer,
-                                    regularizer=self.bias_regularizer,
-                                    constraint=self.bias_constraint,
-                                    trainable=True,
-                                    dtype=self.dtype)
+      self.bias = self.add_weight(
+          name='bias',
+          shape=(self.filters,),
+          initializer=self.bias_initializer,
+          regularizer=self.bias_regularizer,
+          constraint=self.bias_constraint,
+          trainable=True,
+          dtype=self.dtype)
     else:
       self.bias = None
     self.input_spec = InputSpec(ndim=self.rank + 2,
@@ -720,21 +722,23 @@ class Conv2DTranspose(Conv2D):
     self.input_spec = InputSpec(ndim=4, axes={channel_axis: input_dim})
     kernel_shape = self.kernel_size + (self.filters, input_dim)
 
-    self.kernel = self.add_variable(name='kernel',
-                                    shape=kernel_shape,
-                                    initializer=self.kernel_initializer,
-                                    regularizer=self.kernel_regularizer,
-                                    constraint=self.kernel_constraint,
-                                    trainable=True,
-                                    dtype=self.dtype)
+    self.kernel = self.add_weight(
+        name='kernel',
+        shape=kernel_shape,
+        initializer=self.kernel_initializer,
+        regularizer=self.kernel_regularizer,
+        constraint=self.kernel_constraint,
+        trainable=True,
+        dtype=self.dtype)
     if self.use_bias:
-      self.bias = self.add_variable(name='bias',
-                                    shape=(self.filters,),
-                                    initializer=self.bias_initializer,
-                                    regularizer=self.bias_regularizer,
-                                    constraint=self.bias_constraint,
-                                    trainable=True,
-                                    dtype=self.dtype)
+      self.bias = self.add_weight(
+          name='bias',
+          shape=(self.filters,),
+          initializer=self.bias_initializer,
+          regularizer=self.bias_regularizer,
+          constraint=self.bias_constraint,
+          trainable=True,
+          dtype=self.dtype)
     else:
       self.bias = None
     self.built = True
@@ -961,7 +965,7 @@ class Conv3DTranspose(Conv3D):
     kernel_shape = self.kernel_size + (self.filters, input_dim)
     self.input_spec = InputSpec(ndim=5, axes={channel_axis: input_dim})
 
-    self.kernel = self.add_variable(
+    self.kernel = self.add_weight(
         'kernel',
         shape=kernel_shape,
         initializer=self.kernel_initializer,
@@ -970,7 +974,7 @@ class Conv3DTranspose(Conv3D):
         trainable=True,
         dtype=self.dtype)
     if self.use_bias:
-      self.bias = self.add_variable(
+      self.bias = self.add_weight(
           'bias',
           shape=(self.filters,),
           initializer=self.bias_initializer,
@@ -1222,7 +1226,7 @@ class SeparableConv(Conv):
     pointwise_kernel_shape = (
         1,) * self.rank + (self.depth_multiplier * input_dim, self.filters)
 
-    self.depthwise_kernel = self.add_variable(
+    self.depthwise_kernel = self.add_weight(
         name='depthwise_kernel',
         shape=depthwise_kernel_shape,
         initializer=self.depthwise_initializer,
@@ -1230,7 +1234,7 @@ class SeparableConv(Conv):
         constraint=self.depthwise_constraint,
         trainable=True,
         dtype=self.dtype)
-    self.pointwise_kernel = self.add_variable(
+    self.pointwise_kernel = self.add_weight(
         name='pointwise_kernel',
         shape=pointwise_kernel_shape,
         initializer=self.pointwise_initializer,
@@ -1239,13 +1243,14 @@ class SeparableConv(Conv):
         trainable=True,
         dtype=self.dtype)
     if self.use_bias:
-      self.bias = self.add_variable(name='bias',
-                                    shape=(self.filters,),
-                                    initializer=self.bias_initializer,
-                                    regularizer=self.bias_regularizer,
-                                    constraint=self.bias_constraint,
-                                    trainable=True,
-                                    dtype=self.dtype)
+      self.bias = self.add_weight(
+          name='bias',
+          shape=(self.filters,),
+          initializer=self.bias_initializer,
+          regularizer=self.bias_regularizer,
+          constraint=self.bias_constraint,
+          trainable=True,
+          dtype=self.dtype)
     else:
       self.bias = None
     self.built = True
diff --git a/tensorflow/python/keras/layers/core.py b/tensorflow/python/keras/layers/core.py
index df4c3915a3..5061825d38 100644
--- a/tensorflow/python/keras/layers/core.py
+++ b/tensorflow/python/keras/layers/core.py
@@ -882,21 +882,23 @@ class Dense(Layer):
                        'should be defined. Found `None`.')
     self.input_spec = InputSpec(min_ndim=2,
                                 axes={-1: input_shape[-1].value})
-    self.kernel = self.add_variable('kernel',
-                                    shape=[input_shape[-1].value, self.units],
-                                    initializer=self.kernel_initializer,
-                                    regularizer=self.kernel_regularizer,
-                                    constraint=self.kernel_constraint,
-                                    dtype=self.dtype,
-                                    trainable=True)
+    self.kernel = self.add_weight(
+        'kernel',
+        shape=[input_shape[-1].value, self.units],
+        initializer=self.kernel_initializer,
+        regularizer=self.kernel_regularizer,
+        constraint=self.kernel_constraint,
+        dtype=self.dtype,
+        trainable=True)
     if self.use_bias:
-      self.bias = self.add_variable('bias',
-                                    shape=[self.units,],
-                                    initializer=self.bias_initializer,
-                                    regularizer=self.bias_regularizer,
-                                    constraint=self.bias_constraint,
-                                    dtype=self.dtype,
-                                    trainable=True)
+      self.bias = self.add_weight(
+          'bias',
+          shape=[self.units,],
+          initializer=self.bias_initializer,
+          regularizer=self.bias_regularizer,
+          constraint=self.bias_constraint,
+          dtype=self.dtype,
+          trainable=True)
     else:
       self.bias = None
     self.built = True
diff --git a/tensorflow/python/keras/layers/normalization.py b/tensorflow/python/keras/layers/normalization.py
index 7743d00c0f..ff51eadee9 100644
--- a/tensorflow/python/keras/layers/normalization.py
+++ b/tensorflow/python/keras/layers/normalization.py
@@ -183,7 +183,7 @@ class BatchNormalization(Layer):
   def _add_tower_local_variable(self, *args, **kwargs):
     tower_context = distribute_lib.get_tower_context()
     with tower_context.tower_local_var_scope('mean'):
-      return self.add_variable(*args, **kwargs)
+      return self.add_weight(*args, **kwargs)
 
   def build(self, input_shape):
     input_shape = tensor_shape.TensorShape(input_shape)
@@ -276,7 +276,7 @@ class BatchNormalization(Layer):
           self.axis[idx] = x + 1      # Account for added dimension
 
     if self.scale:
-      self.gamma = self.add_variable(
+      self.gamma = self.add_weight(
           name='gamma',
           shape=param_shape,
           dtype=param_dtype,
@@ -291,7 +291,7 @@ class BatchNormalization(Layer):
             1.0, dtype=param_dtype, shape=param_shape)
 
     if self.center:
-      self.beta = self.add_variable(
+      self.beta = self.add_weight(
           name='beta',
           shape=param_shape,
           dtype=param_dtype,