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data, the differentially private (DP) optimizer, such as DPKerasSGDOptimizer, applies the following steps to each sample: Clipping: Each sample’s gradient is computed to understand how much the model’s weights need to be adjusted based on that sample. The gradient is clipped to a certain maximum