# Description: # Contains files for loading, training and evaluating TF-Slim-based models. package(default_visibility = [ ":internal", "//domain_adaptation:__subpackages__", ]) licenses(["notice"]) # Apache 2.0 exports_files(["LICENSE"]) package_group(name = "internal") py_library( name = "dataset_utils", srcs = ["datasets/dataset_utils.py"], ) py_library( name = "download_and_convert_cifar10", srcs = ["datasets/download_and_convert_cifar10.py"], deps = [":dataset_utils"], ) py_library( name = "download_and_convert_flowers", srcs = ["datasets/download_and_convert_flowers.py"], deps = [":dataset_utils"], ) py_library( name = "download_and_convert_mnist", srcs = ["datasets/download_and_convert_mnist.py"], deps = [":dataset_utils"], ) py_binary( name = "download_and_convert_data", srcs = ["download_and_convert_data.py"], deps = [ ":download_and_convert_cifar10", ":download_and_convert_flowers", ":download_and_convert_mnist", ], ) py_binary( name = "cifar10", srcs = ["datasets/cifar10.py"], deps = [":dataset_utils"], ) py_binary( name = "flowers", srcs = ["datasets/flowers.py"], deps = [":dataset_utils"], ) py_binary( name = "imagenet", srcs = ["datasets/imagenet.py"], deps = [":dataset_utils"], ) py_binary( name = "mnist", srcs = ["datasets/mnist.py"], deps = [":dataset_utils"], ) py_library( name = "dataset_factory", srcs = ["datasets/dataset_factory.py"], deps = [ ":cifar10", ":flowers", ":imagenet", ":mnist", ], ) py_library( name = "model_deploy", srcs = ["deployment/model_deploy.py"], ) py_test( name = "model_deploy_test", srcs = ["deployment/model_deploy_test.py"], srcs_version = "PY2AND3", deps = [":model_deploy"], ) py_library( name = "cifarnet_preprocessing", srcs = ["preprocessing/cifarnet_preprocessing.py"], ) py_library( name = "inception_preprocessing", srcs = ["preprocessing/inception_preprocessing.py"], ) py_library( name = "lenet_preprocessing", srcs = ["preprocessing/lenet_preprocessing.py"], ) py_library( name = "vgg_preprocessing", srcs = ["preprocessing/vgg_preprocessing.py"], ) py_library( name = "preprocessing_factory", srcs = ["preprocessing/preprocessing_factory.py"], deps = [ ":cifarnet_preprocessing", ":inception_preprocessing", ":lenet_preprocessing", ":vgg_preprocessing", ], ) # Typical networks definitions. py_library( name = "nets", deps = [ ":alexnet", ":cifarnet", ":inception", ":lenet", ":overfeat", ":resnet_v1", ":resnet_v2", ":vgg", ], ) py_library( name = "alexnet", srcs = ["nets/alexnet.py"], srcs_version = "PY2AND3", ) py_test( name = "alexnet_test", size = "medium", srcs = ["nets/alexnet_test.py"], srcs_version = "PY2AND3", deps = [":alexnet"], ) py_library( name = "cifarnet", srcs = ["nets/cifarnet.py"], ) py_library( name = "inception", srcs = ["nets/inception.py"], srcs_version = "PY2AND3", deps = [ ":inception_resnet_v2", ":inception_v1", ":inception_v2", ":inception_v3", ":inception_v4", ], ) py_library( name = "inception_utils", srcs = ["nets/inception_utils.py"], srcs_version = "PY2AND3", ) py_library( name = "inception_v1", srcs = ["nets/inception_v1.py"], srcs_version = "PY2AND3", deps = [ ":inception_utils", ], ) py_library( name = "inception_v2", srcs = ["nets/inception_v2.py"], srcs_version = "PY2AND3", deps = [ ":inception_utils", ], ) py_library( name = "inception_v3", srcs = ["nets/inception_v3.py"], srcs_version = "PY2AND3", deps = [ ":inception_utils", ], ) py_library( name = "inception_v4", srcs = ["nets/inception_v4.py"], srcs_version = "PY2AND3", deps = [ ":inception_utils", ], ) py_library( name = "inception_resnet_v2", srcs = ["nets/inception_resnet_v2.py"], srcs_version = "PY2AND3", ) py_test( name = "inception_v1_test", size = "large", srcs = ["nets/inception_v1_test.py"], shard_count = 3, srcs_version = "PY2AND3", deps = [":inception"], ) py_test( name = "inception_v2_test", size = "large", srcs = ["nets/inception_v2_test.py"], shard_count = 3, srcs_version = "PY2AND3", deps = [":inception"], ) py_test( name = "inception_v3_test", size = "large", srcs = ["nets/inception_v3_test.py"], shard_count = 3, srcs_version = "PY2AND3", deps = [":inception"], ) py_test( name = "inception_v4_test", size = "large", srcs = ["nets/inception_v4_test.py"], shard_count = 3, srcs_version = "PY2AND3", deps = [":inception"], ) py_test( name = "inception_resnet_v2_test", size = "large", srcs = ["nets/inception_resnet_v2_test.py"], shard_count = 3, srcs_version = "PY2AND3", deps = [":inception"], ) py_library( name = "lenet", srcs = ["nets/lenet.py"], ) py_library( name = "overfeat", srcs = ["nets/overfeat.py"], srcs_version = "PY2AND3", ) py_test( name = "overfeat_test", size = "medium", srcs = ["nets/overfeat_test.py"], srcs_version = "PY2AND3", deps = [":overfeat"], ) py_library( name = "resnet_utils", srcs = ["nets/resnet_utils.py"], srcs_version = "PY2AND3", ) py_library( name = "resnet_v1", srcs = ["nets/resnet_v1.py"], srcs_version = "PY2AND3", deps = [ ":resnet_utils", ], ) py_test( name = "resnet_v1_test", size = "medium", srcs = ["nets/resnet_v1_test.py"], srcs_version = "PY2AND3", deps = [":resnet_v1"], ) py_library( name = "resnet_v2", srcs = ["nets/resnet_v2.py"], srcs_version = "PY2AND3", deps = [ ":resnet_utils", ], ) py_test( name = "resnet_v2_test", size = "medium", srcs = ["nets/resnet_v2_test.py"], srcs_version = "PY2AND3", deps = [":resnet_v2"], ) py_library( name = "vgg", srcs = ["nets/vgg.py"], srcs_version = "PY2AND3", ) py_test( name = "vgg_test", size = "medium", srcs = ["nets/vgg_test.py"], srcs_version = "PY2AND3", deps = [":vgg"], ) py_library( name = "nets_factory", srcs = ["nets/nets_factory.py"], deps = [":nets"], ) py_test( name = "nets_factory_test", size = "medium", srcs = ["nets/nets_factory_test.py"], srcs_version = "PY2AND3", deps = [":nets_factory"], ) py_binary( name = "train_image_classifier", srcs = ["train_image_classifier.py"], deps = [ ":dataset_factory", ":model_deploy", ":nets_factory", ":preprocessing_factory", ], ) py_binary( name = "eval_image_classifier", srcs = ["eval_image_classifier.py"], deps = [ ":dataset_factory", ":model_deploy", ":nets_factory", ":preprocessing_factory", ], )