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when trying to run Gradient Perturbation with logistic Regression or DP-SGD, when fitting the model with model.fit there pops up an error:
AssertionError: compute_gradients() on the differentially private optimizer was not called. Which means that the training is not differentially private. It happens for example in Keras training in TensorFlow 2.0+.
The text was updated successfully, but these errors were encountered:
when trying to run Gradient Perturbation with logistic Regression or DP-SGD, when fitting the model with model.fit there pops up an error:
AssertionError: compute_gradients() on the differentially private optimizer was not called. Which means that the training is not differentially private. It happens for example in Keras training in TensorFlow 2.0+.
The text was updated successfully, but these errors were encountered: