# Description: # Package for TensorFlow. load("//tensorflow/python/tools/api/generator:api_gen.bzl", "gen_api_init_files") load("//tensorflow/python/tools/api/generator:api_init_files.bzl", "KERAS_API_INIT_FILES") load("//tensorflow/python/tools/api/generator:api_init_files_v1.bzl", "KERAS_API_INIT_FILES_V1") package( default_visibility = [ "//tensorflow:tensorflow_py", ], licenses = ["notice"], ) keras_packages = [ "tensorflow.python", "tensorflow.python.keras", "tensorflow.python.keras.activations", "tensorflow.python.keras.applications.densenet", "tensorflow.python.keras.applications.efficientnet", "tensorflow.python.keras.applications.imagenet_utils", "tensorflow.python.keras.applications.inception_resnet_v2", "tensorflow.python.keras.applications.inception_v3", "tensorflow.python.keras.applications.mobilenet", "tensorflow.python.keras.applications.mobilenet_v2", "tensorflow.python.keras.applications.mobilenet_v3", "tensorflow.python.keras.applications.nasnet", "tensorflow.python.keras.applications.resnet", "tensorflow.python.keras.applications.resnet_v2", "tensorflow.python.keras.applications.vgg16", "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", "tensorflow.python.keras.datasets.boston_housing", "tensorflow.python.keras.datasets.cifar10", "tensorflow.python.keras.datasets.cifar100", "tensorflow.python.keras.datasets.fashion_mnist", "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.data_adapter", "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.feature_column.sequence_feature_column", # Placeholder for internal API "tensorflow.python.keras.initializers", "tensorflow.python.keras.initializers.initializers_v1", "tensorflow.python.keras.initializers.initializers_v2", "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.legacy_rnn.rnn_cell_impl", "tensorflow.python.keras.layers.local", "tensorflow.python.keras.layers.merge", "tensorflow.python.keras.layers.noise", "tensorflow.python.keras.layers.normalization.batch_normalization", "tensorflow.python.keras.layers.normalization.batch_normalization_v1", "tensorflow.python.keras.layers.normalization.layer_normalization", "tensorflow.python.keras.layers.preprocessing", "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.legacy_tf_layers.base", "tensorflow.python.keras.legacy_tf_layers.convolutional", "tensorflow.python.keras.legacy_tf_layers.core", "tensorflow.python.keras.legacy_tf_layers.normalization", "tensorflow.python.keras.legacy_tf_layers.pooling", "tensorflow.python.keras.losses", "tensorflow.python.keras.metrics", "tensorflow.python.keras.mixed_precision.get_layer_policy", "tensorflow.python.keras.mixed_precision.loss_scale_optimizer", "tensorflow.python.keras.mixed_precision.policy", "tensorflow.python.keras.models", "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", "tensorflow.python.keras.preprocessing.image", "tensorflow.python.keras.preprocessing.sequence", "tensorflow.python.keras.preprocessing.text", "tensorflow.python.keras.regularizers", "tensorflow.python.keras.saving.model_config", "tensorflow.python.keras.saving.save", "tensorflow.python.keras.saving.saved_model_experimental", "tensorflow.python.keras.utils.data_utils", "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.tf_utils", "tensorflow.python.keras.utils.vis_utils", "tensorflow.python.keras.wrappers.scikit_learn", ] gen_api_init_files( name = "keras_python_api_gen", api_name = "keras", api_version = 1, output_files = KERAS_API_INIT_FILES_V1, output_package = "tensorflow.python.keras.api", package_deps = [ "//tensorflow/python/keras", "//tensorflow/python:no_contrib", ], packages = keras_packages, ) gen_api_init_files( name = "keras_python_api_gen_compat_v1", api_name = "keras", api_version = 1, output_dir = "_v1/", output_files = KERAS_API_INIT_FILES_V1, output_package = "tensorflow.python.keras.api._v1", package_deps = [ "//tensorflow/python/keras", "//tensorflow/python:no_contrib", ], packages = keras_packages, ) gen_api_init_files( name = "keras_python_api_gen_compat_v2", api_name = "keras", api_version = 2, output_dir = "_v2/", output_files = KERAS_API_INIT_FILES, output_package = "tensorflow.python.keras.api._v2", package_deps = [ "//tensorflow/python/keras", "//tensorflow/python:no_contrib", ], packages = keras_packages, )