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Fix torch `long` to `float` tensor on HUB macOS (#8067)

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Glenn Jocher 2022-06-01 17:34:46 +02:00 committed by GitHub
parent a80dd66efe
commit 7cef03dddd
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1 changed files with 3 additions and 3 deletions
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6
utils/loss.py
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@ -195,8 +195,8 @@ class ComputeLoss:
device=self.device).float() * g # offsets
for i in range(self.nl):
anchors = self.anchors[i]
gain[2:6] = torch.tensor(p[i].shape)[[3, 2, 3, 2]] # xyxy gain
anchors, shape = self.anchors[i], p[i].shape
gain[2:6] = torch.tensor(shape)[[3, 2, 3, 2]] # xyxy gain
# Match targets to anchors
t = targets * gain # shape(3,n,7)
@ -226,7 +226,7 @@ class ComputeLoss:
gi, gj = gij.T # grid indices
# Append
indices.append((b, a, gj.clamp_(0, gain[3] - 1), gi.clamp_(0, gain[2] - 1))) # image, anchor, grid indices
indices.append((b, a, gj.clamp_(0, shape[2] - 1), gi.clamp_(0, shape[3] - 1))) # image, anchor, grid
tbox.append(torch.cat((gxy - gij, gwh), 1)) # box
anch.append(anchors[a]) # anchors
tcls.append(c) # class