Ankle/yolov5_ZWgra
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Init tensor directly on device (#6068)

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Slightly more efficient than .to(device)
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Deep Patel authored and GitHub committed 2021-12-23 13:49:00 +01:00
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commit c72270c076
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models/yolo.py
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@@ -72,9 +72,9 @@ class Detect(nn.Module):
def _make_grid(self, nx=20, ny=20, i=0): def _make_grid(self, nx=20, ny=20, i=0):
d = self.anchors[i].device d = self.anchors[i].device
if check_version(torch.__version__, '1.10.0'): # torch>=1.10.0 meshgrid workaround for torch>=0.7 compatibility if check_version(torch.__version__, '1.10.0'): # torch>=1.10.0 meshgrid workaround for torch>=0.7 compatibility
yv, xv = torch.meshgrid([torch.arange(ny).to(d), torch.arange(nx).to(d)], indexing='ij') yv, xv = torch.meshgrid([torch.arange(ny, device=d), torch.arange(nx, device=d)], indexing='ij')
else: else:
yv, xv = torch.meshgrid([torch.arange(ny).to(d), torch.arange(nx).to(d)]) yv, xv = torch.meshgrid([torch.arange(ny, device=d), torch.arange(nx, device=d)])
grid = torch.stack((xv, yv), 2).expand((1, self.na, ny, nx, 2)).float() grid = torch.stack((xv, yv), 2).expand((1, self.na, ny, nx, 2)).float()
anchor_grid = (self.anchors[i].clone() * self.stride[i]) \ anchor_grid = (self.anchors[i].clone() * self.stride[i]) \
.view((1, self.na, 1, 1, 2)).expand((1, self.na, ny, nx, 2)).float() .view((1, self.na, 1, 1, 2)).expand((1, self.na, ny, nx, 2)).float()