> For the complete documentation index, see [llms.txt](https://deeplearning4j.konduit.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/model-import-api.md). # API Reference ### Keras Model Import API Reference `KerasModelImport` is the main entry point for importing Keras models into DL4J. It reads stored Keras configurations and weights from: * A single HDF5 archive storing model architecture, training configuration, and weights (produced by `model.save()`) * A JSON file containing the model configuration combined with a separate HDF5 file containing weights (produced by `model.to_json()` and `model.save_weights()`) [Source](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/KerasModelImport.java) *** ### Importing Functional API (ComputationGraph) Models These methods import Keras Functional API models (`keras.models.Model`) as DL4J `ComputationGraph`. *** #### importKerasModelAndWeights (InputStream) ```java public static ComputationGraph importKerasModelAndWeights( InputStream modelHdf5Stream, boolean enforceTrainingConfig) throws IOException, UnsupportedKerasConfigurationException, InvalidKerasConfigurationException ``` Load a Keras Functional API model saved using `model.save(...)` from an `InputStream`. **Parameters:** * `modelHdf5Stream` — `InputStream` containing the HDF5 archive * `enforceTrainingConfig` — whether to enforce training configuration options; set to `false` if the model was not compiled **Returns:** `ComputationGraph` *** ```java public static ComputationGraph importKerasModelAndWeights(InputStream modelHdf5Stream) throws IOException, UnsupportedKerasConfigurationException, InvalidKerasConfigurationException ``` Load a Keras Functional API model from an `InputStream` with training configuration enforced by default. **Parameters:** * `modelHdf5Stream` — `InputStream` containing the HDF5 archive **Returns:** `ComputationGraph` *** #### importKerasModelAndWeights (file path) ```java public static ComputationGraph importKerasModelAndWeights( String modelHdf5Filename, int[] inputShape, boolean enforceTrainingConfig) throws IOException, UnsupportedKerasConfigurationException, InvalidKerasConfigurationException ``` Load a Keras Functional API model saved using `model.save(...)` from a file path. Use this overload for models that do not include input shape information (e.g., `include_top=False` models). **Parameters:** * `modelHdf5Filename` — path to the HDF5 archive * `inputShape` — optional input shape; pass `null` if the model already contains shape information * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `ComputationGraph` *** ```java public static ComputationGraph importKerasModelAndWeights( String modelHdf5Filename, boolean enforceTrainingConfig) throws IOException, UnsupportedKerasConfigurationException, InvalidKerasConfigurationException ``` **Parameters:** * `modelHdf5Filename` — path to the HDF5 archive * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `ComputationGraph` *** ```java public static ComputationGraph importKerasModelAndWeights(String modelHdf5Filename) throws IOException, UnsupportedKerasConfigurationException, InvalidKerasConfigurationException ``` Load a Keras Functional API model from a file path with training configuration enforced by default. **Parameters:** * `modelHdf5Filename` — path to the HDF5 archive **Returns:** `ComputationGraph` *** #### importKerasModelAndWeights (JSON config + weights) ```java public static ComputationGraph importKerasModelAndWeights( String modelJsonFilename, String weightsHdf5Filename, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` Load a Keras Functional API model for which the configuration and weights were saved separately using `model.to_json()` and `model.save_weights(...)`. **Parameters:** * `modelJsonFilename` — path to the JSON file storing the model configuration * `weightsHdf5Filename` — path to the HDF5 archive storing model weights * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `ComputationGraph` *** ```java public static ComputationGraph importKerasModelAndWeights( String modelJsonFilename, String weightsHdf5Filename) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelJsonFilename` — path to the JSON file * `weightsHdf5Filename` — path to the HDF5 weights file **Returns:** `ComputationGraph` *** #### importKerasModelConfiguration ```java public static ComputationGraphConfiguration importKerasModelConfiguration( String modelJsonFilename, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` Load only the model configuration (no weights) for a Keras Functional API model. **Parameters:** * `modelJsonFilename` — path to the JSON file * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `ComputationGraphConfiguration` *** ```java public static ComputationGraphConfiguration importKerasModelConfiguration(String modelJsonFilename) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelJsonFilename` — path to the JSON file **Returns:** `ComputationGraphConfiguration` *** ### Importing Sequential (MultiLayerNetwork) Models These methods import Keras `Sequential` models as DL4J `MultiLayerNetwork`. *** #### importKerasSequentialModelAndWeights (InputStream) ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights( InputStream modelHdf5Stream, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` Load a Keras Sequential model saved using `model.save(...)` from an `InputStream`. **Parameters:** * `modelHdf5Stream` — `InputStream` containing the HDF5 archive * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `MultiLayerNetwork` *** ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights(InputStream modelHdf5Stream) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelHdf5Stream` — `InputStream` containing the HDF5 archive **Returns:** `MultiLayerNetwork` *** #### importKerasSequentialModelAndWeights (file path) ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights( String modelHdf5Filename, int[] inputShape, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` Load a Keras Sequential model from a file path. Supply `inputShape` for models that omit input shape in their configuration. **Parameters:** * `modelHdf5Filename` — path to the HDF5 archive * `inputShape` — optional input shape array; pass `null` if not needed * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `MultiLayerNetwork` *** ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights( String modelHdf5Filename, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelHdf5Filename` — path to the HDF5 archive * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `MultiLayerNetwork` *** ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights(String modelHdf5Filename) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelHdf5Filename` — path to the HDF5 archive **Returns:** `MultiLayerNetwork` *** #### importKerasSequentialModelAndWeights (JSON config + weights) ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights( String modelJsonFilename, String weightsHdf5Filename, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` Load a Keras Sequential model for which the configuration and weights were saved separately. **Parameters:** * `modelJsonFilename` — path to the JSON configuration file * `weightsHdf5Filename` — path to the HDF5 weights file * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `MultiLayerNetwork` *** ```java public static MultiLayerNetwork importKerasSequentialModelAndWeights( String modelJsonFilename, String weightsHdf5Filename) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelJsonFilename` — path to the JSON configuration file * `weightsHdf5Filename` — path to the HDF5 weights file **Returns:** `MultiLayerNetwork` *** #### importKerasSequentialConfiguration ```java public static MultiLayerConfiguration importKerasSequentialConfiguration( String modelJsonFilename, boolean enforceTrainingConfig) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` Load only the model configuration for a Keras Sequential model. No weights are loaded. **Parameters:** * `modelJsonFilename` — path to the JSON configuration file * `enforceTrainingConfig` — whether to enforce training configuration options **Returns:** `MultiLayerConfiguration` *** ```java public static MultiLayerConfiguration importKerasSequentialConfiguration(String modelJsonFilename) throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException ``` **Parameters:** * `modelJsonFilename` — path to the JSON configuration file **Returns:** `MultiLayerConfiguration` *** ### Exception Types | Exception | Meaning | | ---------------------------------------- | -------------------------------------------------------------------------------------------- | | `InvalidKerasConfigurationException` | The Keras configuration contains elements that are recognized but cannot be parsed or mapped | | `UnsupportedKerasConfigurationException` | The Keras configuration contains features that are not supported by the importer | | `IOException` | File not found or unreadable | *** ### enforceTrainingConfig Flag The `enforceTrainingConfig` parameter controls how training-related configuration in the HDF5 is handled: * `true` (default): an exception is thrown if any training configuration element cannot be parsed or mapped. Use this when you intend to continue training the model in DL4J. * `false`: training configuration parsing errors are logged as warnings but do not stop import. Use this for inference-only workflows or when the Keras model was not compiled before saving. *** ### Method Selection Guide | Situation | Method to use | | ------------------------------------------- | ------------------------------------------------------ | | Sequential model, single .h5 file | `importKerasSequentialModelAndWeights(String)` | | Sequential model, config + weights separate | `importKerasSequentialModelAndWeights(String, String)` | | Sequential model, config only | `importKerasSequentialConfiguration(String)` | | Sequential model, from InputStream | `importKerasSequentialModelAndWeights(InputStream)` | | Functional model, single .h5 file | `importKerasModelAndWeights(String)` | | Functional model, config + weights separate | `importKerasModelAndWeights(String, String)` | | Functional model, config only | `importKerasModelConfiguration(String)` | | Functional model, from InputStream | `importKerasModelAndWeights(InputStream)` | | Model missing input shape | Use the overload with `int[] inputShape` parameter | | Model not compiled in Keras | Pass `enforceTrainingConfig=false` | --- # Agent Instructions This documentation is published with GitBook. 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