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TensorFlow Privacy library.
Modules
restart_query module: Implements DPQuery interface for restarting the states of another query.
tree_aggregation module: Tree aggregation algorithm.
v1 module: TensorFlow Privacy library v1 imports.
Classes
class DNNClassifier: DP version of tf.estimator.DNNClassifier.
class DPModel: DP subclass of tf.keras.Model.
class DPQuery: Interface for differentially private query mechanisms.
class DPSequential: DP subclass of tf.keras.Sequential.
class DiscreteGaussianSumQuery: Implements DPQuery for discrete Gaussian sum queries.
class DistributedDiscreteGaussianSumQuery: Implements DPQuery for discrete distributed Gaussian sum queries.
class DistributedSkellamSumQuery: Implements DPQuery interface for discrete distributed sum queries.
class GaussianSumQuery: Implements DPQuery interface for Gaussian sum queries.
class GenericDPAdagradOptimizer: Differentially private subclass of class tf.keras.optimizers.legacyAdagrad.
class GenericDPAdamOptimizer: Differentially private subclass of class tf.keras.optimizers.legacyAdam.
class GenericDPSGDOptimizer: Differentially private subclass of class tf.keras.optimizers.legacySGD.
class NestedQuery: Implements DPQuery interface for structured queries.
class NoPrivacyAverageQuery: Implements DPQuery interface for an average query with no privacy.
class NoPrivacyQuantileEstimatorQuery: Iterative process to estimate target quantile of a univariate distribution.
class NoPrivacySumQuery: Implements DPQuery interface for a sum query with no privacy.
class NormalizedQuery: DPQuery for queries with a DPQuery numerator and fixed denominator.
class QAdaClipTreeResSumQuery: DPQuery for tree aggregation queries with adaptive clipping.
class QuantileAdaptiveClipSumQuery: DPQuery for Gaussian sum queries with adaptive clipping.
class QuantileEstimatorQuery: DPQuery to estimate target quantile of a univariate distribution.
class RestartQuery: DPQuery for SumAggregationDPQuery with a reset_state function.
class SumAggregationDPQuery: Base class for DPQueries that aggregate via sum.
class TreeCumulativeSumQuery: Returns private cumulative sums by clipping and adding correlated noise.
class TreeRangeSumQuery: Implements dp_query for accurate range queries using tree aggregation.
class TreeResidualSumQuery: Implements DPQuery for adding correlated noise through tree structure.
class VectorizedDPKerasAdagradOptimizer: Vectorized differentially private subclass of given class tf.keras.optimizers.Adagrad.
class VectorizedDPKerasAdamOptimizer: Vectorized differentially private subclass of given class tf.keras.optimizers.Adam.
class VectorizedDPKerasSGDOptimizer: Vectorized differentially private subclass of given class tf.keras.optimizers.SGD.
Functions
DPFTRLTreeAggregationOptimizer(...): Returns a DPOptimizerClass cls using the TreeAggregationQuery.
DPKerasAdagradOptimizer(...): Returns a DPOptimizerClass cls using the GaussianSumQuery.
DPKerasAdamOptimizer(...): Returns a DPOptimizerClass cls using the GaussianSumQuery.
DPKerasSGDOptimizer(...): Returns a DPOptimizerClass cls using the GaussianSumQuery.
compute_dp_sgd_privacy(...): Compute epsilon based on the given hyperparameters.
compute_dp_sgd_privacy_statement(...): Produces a privacy report summarizing the DP guarantee.
compute_rdp_single_tree(...): Computes RDP of the Tree Aggregation Protocol for a single tree.
compute_rdp_tree_restart(...): Computes RDP of the Tree Aggregation Protocol for Gaussian Mechanism.
compute_zcdp_single_tree(...): Computes zCDP of the Tree Aggregation Protocol for a single tree.
linearly_separable_labeled_examples(...): Generates num_examples labeled examples using separator given by weights.
logistic_dpsgd(...): Trains and validates private logistic regression model via DP-SGD.
logistic_objective_perturbation(...): Trains and validates differentially private logistic regression model.
make_dp_model_class(...): Given a subclass of tf.keras.Model, returns a DP-SGD version of it.
make_gaussian_query_optimizer_class(...): Returns a differentially private optimizer using the GaussianSumQuery.
make_keras_generic_optimizer_class(...): Returns a differentially private (DP) subclass of cls.
make_keras_optimizer_class(...): Returns a differentially private optimizer using the GaussianSumQuery.
make_vectorized_keras_optimizer_class(...): Given a subclass of tf.keras.optimizers.Optimizer, returns a vectorized DP-SGD subclass of it.
single_layer_softmax_classifier(...): Trains a single layer neural network classifier with softmax activation.
synthetic_linearly_separable_data(...): Generates synthetic train and test data for logistic regression.
Other Members | |
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| version |
'0.9.0'
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