Xelawk
commented
4 months ago 问题找到了，你的ECABlock有个channel的入参是无效的，导致我在重构后错误传给了k_size
class ECABlock(nn.Module):
"""Constructs a ECA module.
Args:
channel: Number of channels of the input feature map
k_size: Adaptive selection of kernel size
"""
def __init__(self, channel, k_size=3):
super(ECABlock, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.conv = nn.Conv1d(1, 1, kernel_size=k_size, padding=(k_size - 1) // 2, bias=False)
self.sigmoid = nn.Sigmoid()
RuntimeError: Error(s) in loading state_dict for SLBR: size mismatch for shared_decoder.up_im_atts.0.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 256]). size mismatch for shared_decoder.up_mask_atts.0.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 256]). size mismatch for coarse_decoder.atts_bg.0.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 128]). size mismatch for coarse_decoder.atts_bg.1.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 64]). size mismatch for coarse_decoder.atts_bg.2.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 32]). size mismatch for coarse_decoder.atts_mask.0.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 128]). size mismatch for coarse_decoder.atts_mask.1.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 64]). size mismatch for coarse_decoder.atts_mask.2.conv.weight: copying a param with shape torch.Size([1, 1, 3]) from checkpoint, the shape in current model is torch.Size([1, 1, 32]).