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Skips adding noise when noise_multiplier is 0 for fast clipping.

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PiperOrigin-RevId: 522396275
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Shuang Song 2023-04-06 11:54:16 -07:00 committed by A. Unique TensorFlower
parent de9836883d
commit c4628d5dbc
1 changed files with 11 additions and 8 deletions
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19
tensorflow_privacy/privacy/keras_models/dp_keras_model.py
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@ -231,16 +231,19 @@ def make_dp_model_class(cls):
self._num_microbatches, self._num_microbatches,
) )
) )
grads = gradient_clipping_utils.add_aggregate_noise( if self._noise_multiplier > 0:
self, grads = gradient_clipping_utils.add_aggregate_noise(
clipped_grads, self,
eff_num_microbatches, clipped_grads,
self._l2_norm_clip, eff_num_microbatches,
self._noise_multiplier, self._l2_norm_clip,
) self._noise_multiplier,
)
else:
grads = clipped_grads
output_metrics[privatized_loss_name] = weighted_loss output_metrics[privatized_loss_name] = weighted_loss
else: else:
logging.info('Computing gradients using microbatching.') logging.info('Computing gradients using original clipping algorithm.')
# Computes per-example clipped gradients directly. This is called # Computes per-example clipped gradients directly. This is called
# if at least one of the layers cannot use the "fast" gradient clipping # if at least one of the layers cannot use the "fast" gradient clipping
# algorithm. # algorithm.