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Pass kwargs from make_private to _prepare_optimizer #648

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Pass kwargs from make_private to _prepare_optimizer #648

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63c803a
fix: pass kwargs from make_private to _prepare_optimizer
eigengravy May 1, 2024
a479f46
Merge branch 'main' into issue-559
HuanyuZhang Jun 11, 2024
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9 changes: 7 additions & 2 deletions opacus/privacy_engine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,8 +100,8 @@ def __init__(self, *, accountant: str = "prv", secure_mode: bool = False):

def _prepare_optimizer(
self,
optimizer: optim.Optimizer,
*,
optimizer: optim.Optimizer,
noise_multiplier: float,
max_grad_norm: Union[float, List[float]],
expected_batch_size: int,
Expand All @@ -110,6 +110,7 @@ def _prepare_optimizer(
clipping: str = "flat",
noise_generator=None,
grad_sample_mode="hooks",
**kwargs,
) -> DPOptimizer:
if isinstance(optimizer, DPOptimizer):
optimizer = optimizer.original_optimizer
Expand All @@ -134,6 +135,7 @@ def _prepare_optimizer(
loss_reduction=loss_reduction,
generator=generator,
secure_mode=self.secure_mode,
**kwargs,
)

def _prepare_data_loader(
Expand Down Expand Up @@ -274,6 +276,7 @@ def make_private(
clipping: str = "flat",
noise_generator=None,
grad_sample_mode: str = "hooks",
**kwargs,
) -> Tuple[GradSampleModule, DPOptimizer, DataLoader]:
"""
Add privacy-related responsibilities to the main PyTorch training objects:
Expand Down Expand Up @@ -371,7 +374,7 @@ def make_private(
expected_batch_size /= world_size

optimizer = self._prepare_optimizer(
optimizer,
optimizer=optimizer,
noise_multiplier=noise_multiplier,
max_grad_norm=max_grad_norm,
expected_batch_size=expected_batch_size,
Expand All @@ -380,6 +383,7 @@ def make_private(
distributed=distributed,
clipping=clipping,
grad_sample_mode=grad_sample_mode,
**kwargs,
)

optimizer.attach_step_hook(
Expand Down Expand Up @@ -487,6 +491,7 @@ def make_private_with_epsilon(
grad_sample_mode=grad_sample_mode,
poisson_sampling=poisson_sampling,
clipping=clipping,
**kwargs,
)

def get_epsilon(self, delta):
Expand Down