Ankle/yolov5_birdproject
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Update Detect() grid init for loop (#9494)

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May resolve threaded inference issue in https://github.com/ultralytics/yolov5/pull/9425#issuecomment-1250802928 by avoiding memory sharing on init.


Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher authored and GitHub committed 2022-09-19 13:31:24 +02:00
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models/yolo.py
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@@ -47,8 +47,8 @@ class Detect(nn.Module):
self.no = nc + 5 # number of outputs per anchor self.no = nc + 5 # number of outputs per anchor
self.nl = len(anchors) # number of detection layers self.nl = len(anchors) # number of detection layers
self.na = len(anchors[0]) // 2 # number of anchors self.na = len(anchors[0]) // 2 # number of anchors
self.grid = [torch.empty(1)] * self.nl # init grid self.grid = [torch.empty(0) for _ in range(self.nl)] # init grid
self.anchor_grid = [torch.empty(1)] * self.nl # init anchor grid self.anchor_grid = [torch.empty(0) for _ in range(self.nl)] # init anchor grid
self.register_buffer('anchors', torch.tensor(anchors).float().view(self.nl, -1, 2)) # shape(nl,na,2) self.register_buffer('anchors', torch.tensor(anchors).float().view(self.nl, -1, 2)) # shape(nl,na,2)
self.m = nn.ModuleList(nn.Conv2d(x, self.no * self.na, 1) for x in ch) # output conv self.m = nn.ModuleList(nn.Conv2d(x, self.no * self.na, 1) for x in ch) # output conv
self.inplace = inplace # use inplace ops (e.g. slice assignment) self.inplace = inplace # use inplace ops (e.g. slice assignment)