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Refactor Augmentation Space calls to speed up #5402

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merged 1 commit into from
Feb 10, 2022
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Refactor Augmentation Space calls to speed up #5402

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4 changes: 2 additions & 2 deletions torchvision/transforms/autoaugment.py
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Original file line number Diff line number Diff line change
Expand Up @@ -268,9 +268,9 @@ def forward(self, img: Tensor) -> Tensor:

transform_id, probs, signs = self.get_params(len(self.policies))

op_meta = self._augmentation_space(10, F.get_image_size(img))
for i, (op_name, p, magnitude_id) in enumerate(self.policies[transform_id]):
if probs[i] <= p:
op_meta = self._augmentation_space(10, F.get_image_size(img))
magnitudes, signed = op_meta[op_name]
magnitude = float(magnitudes[magnitude_id].item()) if magnitude_id is not None else 0.0
if signed and signs[i] == 0:
Expand Down Expand Up @@ -350,8 +350,8 @@ def forward(self, img: Tensor) -> Tensor:
elif fill is not None:
fill = [float(f) for f in fill]

op_meta = self._augmentation_space(self.num_magnitude_bins, F.get_image_size(img))
for _ in range(self.num_ops):
op_meta = self._augmentation_space(self.num_magnitude_bins, F.get_image_size(img))
op_index = int(torch.randint(len(op_meta), (1,)).item())
op_name = list(op_meta.keys())[op_index]
magnitudes, signed = op_meta[op_name]
Expand Down