guides_master.py

# CV_GUIDES_MASTER = {
#     "path": "keras_cv/",
#     "title": "KerasCV",
#     "toc": True,
#     "children": [
#         {
#             "path": "object_detection_keras_cv",
#             "title": "Use KerasCV to assemble object detection pipelines",
#         },
#         {
#             "path": "classification_with_keras_cv",
#             "title": "Use KerasCV to train powerful image classifiers.",
#         },
#         {
#             "path": "cut_mix_mix_up_and_rand_augment",
#             "title": "CutMix, MixUp, and RandAugment image augmentation with KerasCV",
#         },
#         {
#             "path": "generate_images_with_stable_diffusion",
#             "title": "High-performance image generation using Stable Diffusion in KerasCV",
#         },
#         {
#             "path": "custom_image_augmentations",
#             "title": "Custom Image Augmentations with BaseImageAugmentationLayer",
#         },
#         {
#             "path": "semantic_segmentation_deeplab_v3_plus",
#             "title": "Semantic Segmentation with KerasCV",
#         },
#         {
#             "path": "segment_anything_in_keras_cv",
#             "title": "Segment Anything in KerasCV",
#         },
#     ],
# }

GUIDES_MASTER = {
    "path": "guides/",
    "title": "Developer guides",
    "toc": True,
    "children": [
        {
            "path": "functional_api",
            "title": "The Functional API",
        },
        {
            "path": "sequential_model",
            "title": "The Sequential model",
        },
        {
            "path": "making_new_layers_and_models_via_subclassing",
            "title": "Making new layers & models via subclassing",
        },
        {
            "path": "training_with_built_in_methods",
            "title": "Training & evaluation with the built-in methods",
        },
        {
            "path": "custom_train_step_in_jax",
            "title": "Customizing `fit()` with JAX",
        },
        {
            "path": "custom_train_step_in_tensorflow",
            "title": "Customizing `fit()` with TensorFlow",
        },
        {
            "path": "custom_train_step_in_torch",
            "title": "Customizing `fit()` with PyTorch",
        },
        {
            "path": "writing_a_custom_training_loop_in_jax",
            "title": "Writing a custom training loop in JAX",
        },
        {
            "path": "writing_a_custom_training_loop_in_tensorflow",
            "title": "Writing a custom training loop in TensorFlow",
        },
        {
            "path": "writing_a_custom_training_loop_in_torch",
            "title": "Writing a custom training loop in PyTorch",
        },
        {
            "path": "serialization_and_saving",
            "title": "Serialization & saving",
        },
        {
            "path": "customizing_saving_and_serialization",
            "title": "Customizing saving & serialization",
        },
        {
            "path": "writing_your_own_callbacks",
            "title": "Writing your own callbacks",
        },
        {
            "path": "transfer_learning",
            "title": "Transfer learning & fine-tuning",
        },
        {
            "path": "distributed_training_with_jax",
            "title": "Distributed training with JAX",
        },
        {
            "path": "distributed_training_with_tensorflow",
            "title": "Distributed training with TensorFlow",
        },
        {
            "path": "distributed_training_with_torch",
            "title": "Distributed training with PyTorch",
        },
        {
            "path": "distribution",
            "title": "Distributed training with Keras 3",
        },
        {
            "path": "migrating_to_keras_3",
            "title": "Migrating Keras 2 code to Keras 3",
        },
        {
            "path": "keras_nnx_guide",
            "title": "How to use Keras with NNX backend",
        },
        {
            "path": "orbax_checkpoint",
            "title": "Orbax Checkpointing in Keras",
        },
        # {
        #     "path": "preprocessing_layers",
        #     "title": "Working with preprocessing layers",
        # },
        # {
        #     "path": "working_with_rnns",
        #     "title": "Working with recurrent neural networks",
        # },
        # {
        #     "path": "understanding_masking_and_padding",
        #     "title": "Understanding masking & padding",
        # },
        # {
        #     'path': 'writing_your_own_metrics',
        #     'title': 'Writing your own Metrics',
        # },
        # {
        #     'path': 'writing_your_own_losses',
        #     'title': 'Writing your own Losses',
        # },
        # {
        #     'path': 'tpu_training',
        #     'title': 'Training Keras models on TPU',
        # },
        # {
        #     'path': 'hyperparameter_optimization',
        #     'title': 'Hyperparameter optimization',
        # },
        # {
        #     'path': 'mixed_precision',
        #     'title': 'Mixed precision training',
        # },
        # CV_GUIDES_MASTER,
    ],
}