{
  "$schema": "https://ambiqai.github.io/helia-ui/schema/reference-model-1.json",
  "generatedFrom": {
    "sourceCommit": "f341fb11f7f5d77a4974ba8273c4cd55d67c21f0",
    "tool": "pyref",
    "version": "1.7.3"
  },
  "language": "python",
  "modules": [
    {
      "description": "Masked reconstruction with portable computation and explicit TF/Torch steps.",
      "name": "mask_autoencoder",
      "path": "helia_edge.trainers.mask_autoencoder",
      "submodules": [],
      "summary": "Masked reconstruction with portable computation and explicit TF/Torch steps.",
      "symbols": [
        {
          "description": "Masked target patches and their corresponding predicted patches.",
          "examples": [],
          "id": "helia_edge.trainers.mask_autoencoder.Reconstruction",
          "kind": "class",
          "language": "python",
          "members": [
            {
              "description": "Input patches gathered at the selected mask indices.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.Reconstruction.targets",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "targets",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "targets: Tensor",
              "source": {
                "line": 26,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L26"
              },
              "summary": ""
            },
            {
              "description": "Reconstructed patches gathered at the same indices.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.Reconstruction.predictions",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "predictions",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "predictions: Tensor",
              "source": {
                "line": 27,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L27"
              },
              "summary": ""
            }
          ],
          "name": "Reconstruction",
          "params": [],
          "raises": [],
          "returns": [],
          "signature": "Reconstruction()",
          "source": {
            "line": 18,
            "path": "helia_edge/trainers/mask_autoencoder.py",
            "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L18"
          },
          "summary": "Masked target patches and their corresponding predicted patches."
        },
        {
          "description": "Reconstruction objective together with the patches used to compute it.",
          "examples": [],
          "id": "helia_edge.trainers.mask_autoencoder.ReconstructionLoss",
          "kind": "class",
          "language": "python",
          "members": [
            {
              "description": "Loss tensor computed by the configured reconstruction objective.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.ReconstructionLoss.loss",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "loss",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "loss: Tensor",
              "source": {
                "line": 39,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L39"
              },
              "summary": ""
            },
            {
              "description": "Masked input patches.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.ReconstructionLoss.targets",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "targets",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "targets: Tensor",
              "source": {
                "line": 40,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L40"
              },
              "summary": ""
            },
            {
              "description": "Corresponding reconstructed patches.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.ReconstructionLoss.predictions",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "predictions",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "predictions: Tensor",
              "source": {
                "line": 41,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L41"
              },
              "summary": ""
            }
          ],
          "name": "ReconstructionLoss",
          "params": [],
          "raises": [],
          "returns": [],
          "signature": "ReconstructionLoss()",
          "source": {
            "line": 30,
            "path": "helia_edge/trainers/mask_autoencoder.py",
            "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L30"
          },
          "summary": "Reconstruction objective together with the patches used to compute it."
        },
        {
          "description": "Masked reconstruction with Keras fit() and independently callable objectives.\n\ncall() returns (targets, predictions). training controls layer state, not masks.\nSee https://ambiqai.github.io/helia-edge/getting-started/backends/ for serialization, native-loop\nuse and support limits.",
          "examples": [],
          "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder",
          "kind": "class",
          "language": "python",
          "members": [
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.patch_layer",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "patch_layer",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "patch_layer = patch_layer",
              "source": {
                "line": 69,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L69"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.patch_encoder",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "patch_encoder",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "patch_encoder = patch_encoder",
              "source": {
                "line": 70,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L70"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.encoder",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "encoder",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "encoder = encoder",
              "source": {
                "line": 71,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L71"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.decoder",
              "kind": "attribute",
              "language": "python",
              "members": [],
              "name": "decoder",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "decoder = decoder",
              "source": {
                "line": 72,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L72"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.call",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "call",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "call(inputs: Array, training: bool = False) -> Reconstruction",
              "source": {
                "line": 74,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L74"
              },
              "summary": ""
            },
            {
              "description": "Return masked (target_patches, predicted_patches), without an objective.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.reconstruction_targets",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "reconstruction_targets",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "reconstruction_targets(x: Array, training: bool = False) -> Reconstruction",
              "source": {
                "line": 86,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L86"
              },
              "summary": "Return masked (targetpatches, predictedpatches), without an objective."
            },
            {
              "description": "Return (compiled total loss, targets, predictions); preserve the old API.",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.calculate_loss",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "calculate_loss",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "calculate_loss(x: Array, test: bool = False) -> ReconstructionLoss",
              "source": {
                "line": 90,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L90"
              },
              "summary": "Return (compiled total loss, targets, predictions); preserve the old API."
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.compute_loss",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "compute_loss",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "compute_loss(\n    x: Any = None,\n    y: Any = None,\n    y_pred: Any = None,\n    sample_weight: Any = None,\n    training: bool = True,\n) -> Tensor",
              "source": {
                "line": 96,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L96"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.compute_metrics",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "compute_metrics",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "compute_metrics(x: Any, y: Any, y_pred: Any, sample_weight: Any = None) -> dict[str, Tensor]",
              "source": {
                "line": 104,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L104"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.train_step",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "train_step",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "train_step(data: Any) -> dict[str, Tensor]",
              "source": {
                "line": 130,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L130"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.test_step",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "test_step",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "test_step(data: Any) -> dict[str, Tensor]",
              "source": {
                "line": 137,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L137"
              },
              "summary": ""
            },
            {
              "description": "",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.get_config",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "get_config",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "get_config() -> dict[str, Any]",
              "source": {
                "line": 143,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L143"
              },
              "summary": ""
            },
            {
              "description": "`classmethod`",
              "examples": [],
              "id": "helia_edge.trainers.mask_autoencoder.MaskedAutoencoder.from_config",
              "kind": "method",
              "language": "python",
              "members": [],
              "name": "from_config",
              "params": [],
              "raises": [],
              "returns": [],
              "signature": "from_config(config: dict[str, Any], custom_objects: dict[str, Any] | None = None) -> Self",
              "source": {
                "line": 149,
                "path": "helia_edge/trainers/mask_autoencoder.py",
                "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L149"
              },
              "summary": ""
            }
          ],
          "name": "MaskedAutoencoder",
          "params": [],
          "raises": [],
          "returns": [],
          "signature": "MaskedAutoencoder(\n    patch_layer: Callable[[Array], Tensor],\n    patch_encoder: Callable[[Array], tuple[Tensor, Tensor, Tensor, Tensor, Tensor]],\n    encoder: keras.Model,\n    decoder: keras.Model,\n    **kwargs: Any = {},\n) -> None",
          "source": {
            "line": 51,
            "path": "helia_edge/trainers/mask_autoencoder.py",
            "url": "https://github.com/AmbiqAI/helia-edge/blob/f341fb11f7f5d77a4974ba8273c4cd55d67c21f0/helia_edge/trainers/mask_autoencoder.py#L51"
          },
          "summary": "Masked reconstruction with Keras fit() and independently callable objectives."
        }
      ]
    }
  ],
  "name": "helia_edge"
}
