Module: tff.learning.models | TensorFlow Federated (original) (raw)
Libraries for working with models in federated learning algorithms.
Classes
class BatchOutput: A structure that holds the output of a tff.learning.models.VariableModel.
class FunctionalModel: A model that parameterizes forward pass by model weights.
class ModelWeights: A container for the trainable and non-trainable variables of a Model.
class ReconstructionModel: Represents a reconstruction model for use in Tensorflow Federated.
class VariableModel: Represents a variable-based model for use in TensorFlow Federated.
Functions
functional_model_from_keras(...): Converts a tf.keras.Model to a tff.learning.models.FunctionalModel.
load(...): Deserializes a TensorFlow SavedModel at path to a tff.learning.models.VariableModel.
load_functional_model(...): Deserializes a TensorFlow SavedModel at path to a functional model.
model_from_functional(...): Converts a FunctionalModel to a tff.learning.models.VariableModel.
save(...): Serializes model as a TensorFlow SavedModel to path.
save_functional_model(...): Serializes a FunctionalModel as a tf.SavedModel to path.
weights_type_from_model(...): Creates a tff.Type from a tff.learning.models.VariableModel or callable that constructs a model.