Add _build_at_init in Layer and use it everywhere.

keras/src/backend/tensorflow/saved_model_test.py

@@ -215,7 +215,7 @@ def test_multi_input_custom_model_and_layer(self):
         @object_registration.register_keras_serializable(package="my_package")
         class CustomLayer(layers.Layer):
             def build(self, *input_shape):
-                self.built = True
+                pass
 
             def call(self, *input_list):
                 self.add_loss(input_list[-2] * 2)
@@ -226,7 +226,6 @@ class CustomModel(models.Model):
             def build(self, *input_shape):
                 self.layer = CustomLayer()
                 self.layer.build(*input_shape)
-                self.built = True
 
             @tf.function
             def call(self, *inputs):

keras/src/export/tfsm_layer.py

@@ -116,7 +116,8 @@ def __init__(
             self._add_existing_weight(v)
         for v in ntvs:
             self._add_existing_weight(v)
-        self.built = True
+
+        self._build_at_init()
 
     def _add_existing_weight(self, weight):
         """Tracks an existing weight."""

keras/src/layers/activations/activation.py

@@ -1,5 +1,4 @@
 from keras.src import activations
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -28,12 +27,7 @@ def __init__(self, activation, **kwargs):
         self.supports_masking = True
         self.activation = activations.get(activation)
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return self.activation(inputs)

keras/src/layers/activations/elu.py

@@ -1,5 +1,4 @@
 from keras.src import activations
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -25,12 +24,7 @@ def __init__(self, alpha=1.0, **kwargs):
         self.alpha = alpha
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return activations.elu(inputs, alpha=self.alpha)

keras/src/layers/activations/leaky_relu.py

@@ -1,7 +1,6 @@
 import warnings
 
 from keras.src import activations
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -52,12 +51,7 @@ def __init__(self, negative_slope=0.3, **kwargs):
         self.negative_slope = negative_slope
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return activations.leaky_relu(

keras/src/layers/activations/relu.py

@@ -1,5 +1,4 @@
 from keras.src import activations
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -63,12 +62,7 @@ def __init__(
         self.threshold = threshold
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return activations.relu(

keras/src/layers/activations/softmax.py

@@ -1,6 +1,5 @@
 from keras.src import activations
 from keras.src import backend
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -49,12 +48,7 @@ def __init__(self, axis=-1, **kwargs):
         self.axis = axis
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs, mask=None):
         if mask is not None:

keras/src/layers/core/identity.py

@@ -1,5 +1,4 @@
 from keras.src import tree
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.backend import KerasTensor
 from keras.src.layers.layer import Layer
@@ -17,12 +16,7 @@ def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return inputs

keras/src/layers/core/masking.py

@@ -1,6 +1,5 @@
 from keras.src import backend
 from keras.src import ops
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 from keras.src.saving.serialization_lib import deserialize_keras_object
@@ -53,12 +52,7 @@ def __init__(self, mask_value=0.0, **kwargs):
         self.mask_value = mask_value
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def compute_mask(self, inputs, mask=None):
         return ops.any(ops.not_equal(inputs, self.mask_value), axis=-1)

keras/src/layers/layer.py

@@ -372,6 +372,18 @@ def _initialize_tracker(self):
             # Reset attribute tracking (TF-specific)
             self._self_setattr_tracking = _self_setattr_tracking
 
+    def _build_at_init(self):
+        """Build the layer at `Layer.__init__`.
+
+        We can only safely mark the layer as `built=True` in `Layer.__init__` if
+        `build` is not overridden. Otherwise, it might cause the subclasses to
+        ignore the user's `build`.
+        """
+        if utils.is_default(self.build):
+            self.built = True
+            self._post_build()
+            self._lock_state()
+
     @property
     def path(self):
         """The path of the layer.
@@ -919,8 +931,7 @@ def maybe_convert(x):
                             outputs, layout
                         )
 
-                if not self.built:
-                    self.built = True
+                self.built = True
                 # Record activity regularizer loss.
                 if self.activity_regularizer is not None:
                     for output in tree.flatten(outputs):

keras/src/layers/layer_test.py

@@ -647,7 +647,7 @@ def __init__(self):
                     trainable=True,
                     dtype="float32",
                 )
-                self.built = True
+                self._build_at_init()
 
             def call(self, x):
                 # Should not autocast.
@@ -663,7 +663,7 @@ def __init__(self):
                     initializer="ones",
                     trainable=True,
                 )
-                self.built = True
+                self._build_at_init()
 
             def call(self, x):
                 # Should not autocast.
@@ -681,7 +681,7 @@ def __init__(self):
                     trainable=True,
                     autocast=False,
                 )
-                self.built = True
+                self._build_at_init()
 
             def call(self, x):
                 # Should not autocast `self.v`.
@@ -700,7 +700,7 @@ def __init__(self):
                 self.inner_one = InnerLayerOne()
                 self.inner_two = InnerLayerTwo()
                 self.inner_three = InnerLayerThree()
-                self.built = True
+                self._build_at_init()
 
             def call(self, x):
                 # Should autocast.
@@ -864,7 +864,7 @@ def __init__(self):
                     trainable=True,
                     regularizer="l1",
                 )
-                self.built = True
+                self._build_at_init()
 
             def call(self, x):
                 x = backend.convert_to_tensor(x, dtype="float32")
@@ -1009,7 +1009,6 @@ class MatchingArguments(layers.Layer):
             def build(self, bar_shape, foo_shape):
                 self.foo_shape = foo_shape
                 self.bar_shape = bar_shape
-                self.built = True
 
             def call(self, foo, bar):
                 return foo[:, 0] + bar[:, 0]
@@ -1018,15 +1017,13 @@ class SubsetArguments(layers.Layer):
             def build(self, baz_shape, foo_shape):
                 self.foo_shape = foo_shape
                 self.baz_shape = baz_shape
-                self.built = True
 
             def call(self, foo, bar=None, baz=None):
                 return foo[:, 0] + bar[:, 0] + baz[:, 0]
 
         class SingleArgument(layers.Layer):
             def build(self, anything_whatsoever):
                 self.foo_shape = anything_whatsoever
-                self.built = True
 
             def call(self, foo, bar):
                 return foo[:, 0] + bar[:, 0]

keras/src/layers/normalization/unit_normalization.py

@@ -1,5 +1,4 @@
 from keras.src import ops
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -39,12 +38,7 @@ def __init__(self, axis=-1, **kwargs):
             )
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return ops.normalize(inputs, axis=self.axis, order=2, epsilon=1e-12)

keras/src/layers/pooling/base_global_pooling.py

@@ -1,5 +1,4 @@
 from keras.src import backend
-from keras.src import utils
 from keras.src.layers.input_spec import InputSpec
 from keras.src.layers.layer import Layer
 
@@ -16,12 +15,7 @@ def __init__(
         self.keepdims = keepdims
         self.input_spec = InputSpec(ndim=pool_dimensions + 2)
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         raise NotImplementedError

keras/src/layers/pooling/base_pooling.py

@@ -1,6 +1,5 @@
 from keras.src import backend
 from keras.src import ops
-from keras.src import utils
 from keras.src.layers.input_spec import InputSpec
 from keras.src.layers.layer import Layer
 from keras.src.ops.operation_utils import compute_pooling_output_shape
@@ -36,12 +35,7 @@ def __init__(
 
         self.input_spec = InputSpec(ndim=pool_dimensions + 2)
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         if self.pool_mode == "max":

keras/src/layers/regularization/activity_regularization.py

@@ -1,5 +1,4 @@
 from keras.src import regularizers
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -29,12 +28,7 @@ def __init__(self, l1=0.0, l2=0.0, **kwargs):
         self.l1 = l1
         self.l2 = l2
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs):
         return inputs

keras/src/layers/regularization/alpha_dropout.py

@@ -1,6 +1,5 @@
 from keras.src import backend
 from keras.src import ops
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -48,12 +47,7 @@ def __init__(self, rate, noise_shape=None, seed=None, **kwargs):
             self.seed_generator = backend.random.SeedGenerator(seed)
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs, training=False):
         if training and self.rate > 0:

keras/src/layers/regularization/dropout.py

@@ -1,5 +1,4 @@
 from keras.src import backend
-from keras.src import utils
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 
@@ -54,12 +53,7 @@ def __init__(self, rate, noise_shape=None, seed=None, **kwargs):
             self.seed_generator = backend.random.SeedGenerator(seed)
         self.supports_masking = True
 
-        # We can only safely mark the layer as built when build is not
-        # overridden.
-        if utils.is_default(self.build):
-            self.built = True
-            self._post_build()
-            self._lock_state()
+        self._build_at_init()
 
     def call(self, inputs, training=False):
         if training and self.rate > 0: