Package org.jetbrains.kotlinx.dl.api.inference.keras

Types

LayerBatchNormPaths

class LayerBatchNormPaths(layerName: String, gammaPath: String, betaPath: String, movingMeanPath: String, movingVariancePath: String) : LayerPaths

LayerConvOrDensePaths

Contains layerName, kernelPath, biasPath for specific layer, found in hdf5 file via

LayerPaths

open class LayerPaths(layerName: String)

Parent class for specific paths to layers in h5 file. Contains only layerName field

LayerPReLUPaths

Contains layerName, alphaPath for PReLU layer, found in hdf5 file via

LayerSeparableConv2DPaths

class LayerSeparableConv2DPaths(layerName: String, depthwiseKernelPath: String, pointwiseKernelPath: String, biasPath: String) : LayerPaths

MissedWeightsStrategy

This strategy defines the behaviour during weights' loading if the weights are not found in the h5 file by the standard Keras paths.

loadWeights

Loads weights from hdf5 file created in Keras TensorFlow framework.

Loads weights from hdf5 file created in Keras TensorFlow framework for pre-defined list of layers.

loadWeightsByPaths

fun GraphTrainableModel.loadWeightsByPaths(hdfFile: HdfFile, layerList: List<Layer>, kernelDataPathTemplate: String = KERNEL_DATA_PATH_TEMPLATE, biasDataPathTemplate: String = BIAS_DATA_PATH_TEMPLATE)

Loads weights from hdf5 file created in Keras TensorFlow framework for pre-defined list of layers.

fun GraphTrainableModel.loadWeightsByPaths(hdfFile: HdfFile, weightPaths: List<LayerPaths>, missedWeights: MissedWeightsStrategy = MissedWeightsStrategy.INITIALIZE, forFrozenLayersOnly: Boolean = false)

Loads weights from hdf5 file created in Keras TensorFlow framework.

loadWeightsByPathTemplates

fun GraphTrainableModel.loadWeightsByPathTemplates(hdfFile: HdfFile, kernelDataPathTemplate: String = KERNEL_DATA_PATH_TEMPLATE, biasDataPathTemplate: String = BIAS_DATA_PATH_TEMPLATE)

Loads weights from hdf5 file created in Keras TensorFlow framework.

fun GraphTrainableModel.loadWeightsByPathTemplates(hdfFile: HdfFile, layerList: List<Layer>, kernelDataPathTemplate: String = KERNEL_DATA_PATH_TEMPLATE, biasDataPathTemplate: String = BIAS_DATA_PATH_TEMPLATE)

Loads weights from hdf5 file created in Keras TensorFlow framework for pre-defined list of layers.

loadWeightsForFrozenLayers

Loads weights from hdf5 file created in Keras TensorFlow framework for non-trainable (or frozen) layers only.

loadWeightsForFrozenLayersByPathTemplates

fun GraphTrainableModel.loadWeightsForFrozenLayersByPathTemplates(hdfFile: HdfFile, kernelDataPathTemplate: String = KERNEL_DATA_PATH_TEMPLATE, biasDataPathTemplate: String = BIAS_DATA_PATH_TEMPLATE)

Loads weights from hdf5 file created in Keras TensorFlow framework for non-trainable (or frozen) layers only.

recursivePrintGroupInHDF5File

fun recursivePrintGroupInHDF5File(hdfFile: HdfFile, group: Group)

Helper function to print out file in hdf5 format for debugging purposes.

saveModelConfiguration

fun GraphTrainableModel.saveModelConfiguration(jsonConfigFile: File, isKerasFullyCompatible: Boolean = false)

Saves model description as json configuration file fully compatible with the Keras TensorFlow framework.