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Do not record gradient_tape on gradient calculation.

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PiperOrigin-RevId: 308772699
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A. Unique TensorFlower 2020-04-27 23:56:58 -07:00
parent 5bc76d2e13
commit 9259ccb3d8
1 changed files with 2 additions and 1 deletions
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tensorflow_privacy/privacy/optimizers/dp_optimizer.py
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@ -96,7 +96,8 @@ def make_optimizer_class(cls):
"""Process one microbatch (record) with privacy helper.""" """Process one microbatch (record) with privacy helper."""
microbatch_loss = tf.reduce_mean( microbatch_loss = tf.reduce_mean(
input_tensor=tf.gather(microbatches_losses, [i])) input_tensor=tf.gather(microbatches_losses, [i]))
grads = gradient_tape.gradient(microbatch_loss, var_list) with gradient_tape.stop_recording():
grads = gradient_tape.gradient(microbatch_loss, var_list)
sample_state = self._dp_sum_query.accumulate_record( sample_state = self._dp_sum_query.accumulate_record(
sample_params, sample_state, grads) sample_params, sample_state, grads)
return sample_state return sample_state