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[RTDETR]fix "Grad strides do not match bucket view strides" when training with DDP (#3255)
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@ -77,7 +77,7 @@ class AIFI(TransformerEncoderLayer):
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pos_embed = self.build_2d_sincos_position_embedding(w, h, c)
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# flatten [B, C, H, W] to [B, HxW, C]
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x = super().forward(x.flatten(2).permute(0, 2, 1), pos=pos_embed.to(device=x.device, dtype=x.dtype))
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return x.permute((0, 2, 1)).view([-1, c, h, w])
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return x.permute(0, 2, 1).view([-1, c, h, w]).contiguous()
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@staticmethod
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def build_2d_sincos_position_embedding(w, h, embed_dim=256, temperature=10000.):
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@ -31,9 +31,6 @@ class HungarianMatcher(nn.Module):
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_cost_mask(bs, num_gts, masks=None, gt_mask=None): Computes the mask cost and dice cost if masks are predicted.
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"""
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class HungarianMatcher(nn.Module):
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...
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def __init__(self, cost_gain=None, use_fl=True, with_mask=False, num_sample_points=12544, alpha=0.25, gamma=2.0):
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super().__init__()
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if cost_gain is None:
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