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Fix type mis-match during mixed-precision training with extract_patches_from_pyramid #84

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Fix type mis-match during mixed-precision training with extract_patches_from_pyramid #84

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5 changes: 3 additions & 2 deletions kornia/feature/laf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -438,11 +438,12 @@ def extract_patches_from_pyramid(
scale_mask = (pyr_idx[i] == cur_pyr_level).squeeze()
if (scale_mask.float().sum().item()) == 0:
continue
scale_mask = (scale_mask > 0).view(-1)
scale_mask = (scale_mask > 0).view(-1).to(nlaf.dtype).to(nlaf.device)
grid = generate_patch_grid_from_normalized_LAF(cur_img[i : i + 1], nlaf[i : i + 1, scale_mask, :, :], PS)
patches = F.grid_sample(
cur_img[i : i + 1].expand(grid.shape[0], ch, h, w), grid, padding_mode="border", align_corners=False
)
).to(nlaf.dtype).to(nlaf.device)

out[i].masked_scatter_(scale_mask.view(-1, 1, 1, 1), patches)
we_are_in_business = min(cur_img.size(2), cur_img.size(3)) >= PS
if not we_are_in_business:
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