Yzichen
加载模型张量形状不匹配
作者您好，我在复现算法时遇到以下报错2025-01-07 15:23:08,440 - mmdet - INFO - load checkpoint from local path: ckpts/bevdet-r50-cbgs.pth 2025-01-07 15:23:08,639 - mmdet - WARNING - The model and loaded state dict do not match exactly
size mismatch for img_view_transformer.depth_net.weight: copying a param with shape torch.Size([123, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([108, 256, 1, 1]). size mismatch for img_view_transformer.depth_net.bias: copying a param with shape torch.Size([123]) from checkpoint, the shape in current model is torch.Size([108]). size mismatch for img_bev_encoder_neck.conv.0.weight: copying a param with shape torch.Size([512, 640, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 640, 3, 3]). size mismatch for img_bev_encoder_neck.conv.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.3.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). size mismatch for img_bev_encoder_neck.conv.4.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.4.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.4.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.conv.4.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for img_bev_encoder_neck.up2.1.weight: copying a param with shape torch.Size([256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]). size mismatch for img_bev_encoder_neck.up2.2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for img_bev_encoder_neck.up2.2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for img_bev_encoder_neck.up2.2.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for img_bev_encoder_neck.up2.2.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for img_bev_encoder_neck.up2.4.weight: copying a param with shape torch.Size([256, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 128, 1, 1]). size mismatch for img_bev_encoder_neck.up2.4.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]). unexpected key in source state_dict: pts_bbox_head.shared_conv.conv.weight, pts_bbox_head.shared_conv.bn.weight, pts_bbox_head.shared_conv.bn.bias, pts_bbox_head.shared_conv.bn.running_mean, pts_bbox_head.shared_conv.bn.running_var, pts_bbox_head.shared_conv.bn.num_batches_tracked, pts_bbox_head.task_heads.0.reg.0.conv.weight, pts_bbox_head.task_heads.0.reg.0.bn.weight, pts_bbox_head.task_heads.0.reg.0.bn.bias, pts_bbox_head.task_heads.0.reg.0.bn.running_mean, pts_bbox_head.task_heads.0.reg.0.bn.running_var, pts_bbox_head.task_heads.0.reg.0.bn.num_batches_tracked, pts_bbox_head.task_heads.0.reg.1.weight, pts_bbox_head.task_heads.0.reg.1.bias, pts_bbox_head.task_heads.0.height.0.conv.weight, pts_bbox_head.task_heads.0.height.0.bn.weight, pts_bbox_head.task_heads.0.height.0.bn.bias, pts_bbox_head.task_heads.0.height.0.bn.running_mean, pts_bbox_head.task_heads.0.height.0.bn.running_var, pts_bbox_head.task_heads.0.height.0.bn.num_batches_tracked, pts_bbox_head.task_heads.0.height.1.weight, pts_bbox_head.task_heads.0.height.1.bias, pts_bbox_head.task_heads.0.dim.0.conv.weight, pts_bbox_head.task_heads.0.dim.0.bn.weight, pts_bbox_head.task_heads.0.dim.0.bn.bias, pts_bbox_head.task_heads.0.dim.0.bn.running_mean, pts_bbox_head.task_heads.0.dim.0.bn.running_var, pts_bbox_head.task_heads.0.dim.0.bn.num_batches_tracked, pts_bbox_head.task_heads.0.dim.1.weight, pts_bbox_head.task_heads.0.dim.1.bias, pts_bbox_head.task_heads.0.rot.0.conv.weight, pts_bbox_head.task_heads.0.rot.0.bn.weight, pts_bbox_head.task_heads.0.rot.0.bn.bias, pts_bbox_head.task_heads.0.rot.0.bn.running_mean, pts_bbox_head.task_heads.0.rot.0.bn.running_var, pts_bbox_head.task_heads.0.rot.0.bn.num_batches_tracked, pts_bbox_head.task_heads.0.rot.1.weight, pts_bbox_head.task_heads.0.rot.1.bias, pts_bbox_head.task_heads.0.vel.0.conv.weight, pts_bbox_head.task_heads.0.vel.0.bn.weight, pts_bbox_head.task_heads.0.vel.0.bn.bias, pts_bbox_head.task_heads.0.vel.0.bn.running_mean, pts_bbox_head.task_heads.0.vel.0.bn.running_var, pts_bbox_head.task_heads.0.vel.0.bn.num_batches_tracked, pts_bbox_head.task_heads.0.vel.1.weight, pts_bbox_head.task_heads.0.vel.1.bias, pts_bbox_head.task_heads.0.heatmap.0.conv.weight, pts_bbox_head.task_heads.0.heatmap.0.bn.weight, pts_bbox_head.task_heads.0.heatmap.0.bn.bias, pts_bbox_head.task_heads.0.heatmap.0.bn.running_mean, pts_bbox_head.task_heads.0.heatmap.0.bn.running_var, pts_bbox_head.task_heads.0.heatmap.0.bn.num_batches_tracked, pts_bbox_head.task_heads.0.heatmap.1.weight, pts_bbox_head.task_heads.0.heatmap.1.bias
missing keys in source state_dict: occ_head.final_conv.conv.weight, occ_head.final_conv.conv.bias, occ_head.predicter.0.weight, occ_head.predicter.0.bias, occ_head.predicter.2.weight, occ_head.predicter.2.bias
