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[RTDETR]fix "Grad strides do not match bucket view strides" when training with DDP (#3255)

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Laughing 2023-06-19 22:09:06 +08:00 committed by GitHub
parent 58bccb1a9f
commit eda7758521
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2 changed files with 1 additions and 4 deletions
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2
ultralytics/nn/modules/transformer.py
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@ -77,7 +77,7 @@ class AIFI(TransformerEncoderLayer):
pos_embed = self.build_2d_sincos_position_embedding(w, h, c) pos_embed = self.build_2d_sincos_position_embedding(w, h, c)
# flatten [B, C, H, W] to [B, HxW, C] # flatten [B, C, H, W] to [B, HxW, C]
x = super().forward(x.flatten(2).permute(0, 2, 1), pos=pos_embed.to(device=x.device, dtype=x.dtype)) x = super().forward(x.flatten(2).permute(0, 2, 1), pos=pos_embed.to(device=x.device, dtype=x.dtype))
return x.permute((0, 2, 1)).view([-1, c, h, w]) return x.permute(0, 2, 1).view([-1, c, h, w]).contiguous()
@staticmethod @staticmethod
def build_2d_sincos_position_embedding(w, h, embed_dim=256, temperature=10000.): def build_2d_sincos_position_embedding(w, h, embed_dim=256, temperature=10000.):

3
ultralytics/vit/utils/ops.py
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@ -31,9 +31,6 @@ class HungarianMatcher(nn.Module):
_cost_mask(bs, num_gts, masks=None, gt_mask=None): Computes the mask cost and dice cost if masks are predicted. _cost_mask(bs, num_gts, masks=None, gt_mask=None): Computes the mask cost and dice cost if masks are predicted.
""" """
class HungarianMatcher(nn.Module):
...
def __init__(self, cost_gain=None, use_fl=True, with_mask=False, num_sample_points=12544, alpha=0.25, gamma=2.0): def __init__(self, cost_gain=None, use_fl=True, with_mask=False, num_sample_points=12544, alpha=0.25, gamma=2.0):
super().__init__() super().__init__()
if cost_gain is None: if cost_gain is None: