Remove layer from keras.__init__.py

PiperOrigin-RevId: 277133404
Change-Id: Iff8cc6a605c0ac57d944ea91a2c1dd71d56385af

tensorflow/python/keras/__init__.py

@@ -23,10 +23,12 @@ from __future__ import print_function
 
 from tensorflow.python import tf2
 
-from tensorflow.python.keras import layers
-from tensorflow.python.keras.layers import Input
-from tensorflow.python.keras.models import Model
-from tensorflow.python.keras.models import Sequential
+# See b/110718070#comment18 for more details about this import.
+from tensorflow.python.keras import models
+
+from tensorflow.python.keras.engine.input_layer import Input
+from tensorflow.python.keras.engine.sequential import Sequential
+from tensorflow.python.keras.engine.training import Model
 
 from tensorflow.python.util.tf_export import keras_export
 

tensorflow/python/keras/api/BUILD

@@ -27,6 +27,7 @@ keras_packages = [
     "tensorflow.python.keras.applications.vgg19",
     "tensorflow.python.keras.applications.xception",
     "tensorflow.python.keras.backend",
+    "tensorflow.python.keras.backend_config",
     "tensorflow.python.keras.callbacks",
     "tensorflow.python.keras.callbacks_v1",
     "tensorflow.python.keras.constraints",
@@ -37,12 +38,46 @@ keras_packages = [
     "tensorflow.python.keras.datasets.imdb",
     "tensorflow.python.keras.datasets.mnist",
     "tensorflow.python.keras.datasets.reuters",
+    "tensorflow.python.keras.engine.base_layer",
+    "tensorflow.python.keras.engine.input_layer",
+    "tensorflow.python.keras.engine.input_spec",
+    "tensorflow.python.keras.engine.sequential",
+    "tensorflow.python.keras.engine.training",
     "tensorflow.python.keras.estimator",
     "tensorflow.python.keras.initializers",
+    "tensorflow.python.keras.layers.advanced_activations",
+    "tensorflow.python.keras.layers.convolutional",
+    "tensorflow.python.keras.layers.convolutional_recurrent",
+    "tensorflow.python.keras.layers.core",
+    "tensorflow.python.keras.layers.cudnn_recurrent",
+    "tensorflow.python.keras.layers.dense_attention",
+    "tensorflow.python.keras.layers.embeddings",
+    "tensorflow.python.keras.layers.local",
+    "tensorflow.python.keras.layers.merge",
+    "tensorflow.python.keras.layers.noise",
+    "tensorflow.python.keras.layers.normalization",
+    "tensorflow.python.keras.layers.normalization_v2",
+    "tensorflow.python.keras.layers.pooling",
+    "tensorflow.python.keras.layers.recurrent",
+    "tensorflow.python.keras.layers.recurrent_v2",
+    "tensorflow.python.keras.layers.serialization",
+    "tensorflow.python.keras.layers.wrappers",
     "tensorflow.python.keras.losses",
     "tensorflow.python.keras.metrics",
+    "tensorflow.python.keras.mixed_precision.experimental.loss_scale_optimizer",
+    "tensorflow.python.keras.mixed_precision.experimental.policy",
     "tensorflow.python.keras.models",
     "tensorflow.python.keras.ops",
+    "tensorflow.python.keras.optimizer_v2.adadelta",
+    "tensorflow.python.keras.optimizer_v2.adagrad",
+    "tensorflow.python.keras.optimizer_v2.adam",
+    "tensorflow.python.keras.optimizer_v2.adamax",
+    "tensorflow.python.keras.optimizer_v2.ftrl",
+    "tensorflow.python.keras.optimizer_v2.gradient_descent",
+    "tensorflow.python.keras.optimizer_v2.learning_rate_schedule",
+    "tensorflow.python.keras.optimizer_v2.nadam",
+    "tensorflow.python.keras.optimizer_v2.optimizer_v2",
+    "tensorflow.python.keras.optimizer_v2.rmsprop",
     "tensorflow.python.keras.optimizers",
     "tensorflow.python.keras.premade.linear",
     "tensorflow.python.keras.premade.wide_deep",
@@ -57,6 +92,7 @@ keras_packages = [
     "tensorflow.python.keras.utils.generic_utils",
     "tensorflow.python.keras.utils.io_utils",
     "tensorflow.python.keras.utils.layer_utils",
+    "tensorflow.python.keras.utils.losses_utils",
     "tensorflow.python.keras.utils.multi_gpu_utils",
     "tensorflow.python.keras.utils.np_utils",
     "tensorflow.python.keras.utils.vis_utils",

tensorflow/python/keras/engine/__init__.py

@@ -1,31 +0,0 @@
-# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""The Keras Engine: graph topology and training loop functionality.
-"""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-# TODO(fchollet): Remove hourglass imports once external code is done importing
-# non-public APIs.
-from tensorflow.python.keras.engine.base_layer import Layer
-from tensorflow.python.keras.engine.input_layer import Input
-from tensorflow.python.keras.engine.input_layer import InputLayer
-from tensorflow.python.keras.engine.input_spec import InputSpec
-from tensorflow.python.keras.utils.layer_utils import get_source_inputs
-
-del absolute_import
-del division
-del print_function

tensorflow/python/keras/engine/network_test.py

@@ -32,6 +32,7 @@ from tensorflow.python.keras.engine import base_layer
 from tensorflow.python.keras.engine import input_layer as input_layer_lib
 from tensorflow.python.keras.engine import network as network_lib
 from tensorflow.python.keras.engine import training
+from tensorflow.python.keras.utils import layer_utils
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import state_ops
@@ -479,7 +480,7 @@ class NetworkConstructionTest(keras_parameterized.TestCase):
       self.assertListEqual([x.shape for x in fn_outputs], [(10, 64), (10, 5)])
 
       # test get_source_inputs
-      self._assertAllIs(keras.engine.get_source_inputs(c), [a, b])
+      self._assertAllIs(layer_utils.get_source_inputs(c), [a, b])
 
       # serialization / deserialization
       json_config = model.to_json()