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size mismatch between ckpt and model #18
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Full error report section 2. Click to expandCurrent model layers: ckpt layers: Difference: During handling of the above exception, another exception occurred: Traceback (most recent call last): |
Did you run inside docker container and build as suggested in readme? |
Hi @wenbowen123 , Thank for the reply. |
Hi,
When I run
python run_grasp_simulation.py
I encountered the error for size mismatch when loading PointGroupPredictor from artifacts/artifacts-77.Full error report section 1. Click to expand
Error(s) in loading state_dict for PointGroup:
size mismatch for input_conv.0.weight: copying a param with shape torch.Size([3, 3, 3, 6, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 6]).
size mismatch for unet.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for unet.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for unet.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for unet.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for unet.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 16, 32]) from checkpoint, the shape in current model is torch.Size([32, 2, 2, 2, 16]).
size mismatch for unet.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.u.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 32, 48]) from checkpoint, the shape in current model is torch.Size([48, 2, 2, 2, 32]).
size mismatch for unet.u.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.u.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 48, 64]) from checkpoint, the shape in current model is torch.Size([64, 2, 2, 2, 48]).
size mismatch for unet.u.u.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.u.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 64, 80]) from checkpoint, the shape in current model is torch.Size([80, 2, 2, 2, 64]).
size mismatch for unet.u.u.u.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.u.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 80, 96]) from checkpoint, the shape in current model is torch.Size([96, 2, 2, 2, 80]).
size mismatch for unet.u.u.u.u.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.u.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 96, 112]) from checkpoint, the shape in current model is torch.Size([112, 2, 2, 2, 96]).
size mismatch for unet.u.u.u.u.u.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 112, 112]) from checkpoint, the shape in current model is torch.Size([112, 3, 3, 3, 112]).
size mismatch for unet.u.u.u.u.u.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 112, 112]) from checkpoint, the shape in current model is torch.Size([112, 3, 3, 3, 112]).
size mismatch for unet.u.u.u.u.u.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 112, 112]) from checkpoint, the shape in current model is torch.Size([112, 3, 3, 3, 112]).
size mismatch for unet.u.u.u.u.u.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 112, 112]) from checkpoint, the shape in current model is torch.Size([112, 3, 3, 3, 112]).
size mismatch for unet.u.u.u.u.u.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 112, 96]) from checkpoint, the shape in current model is torch.Size([96, 2, 2, 2, 112]).
size mismatch for unet.u.u.u.u.u.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 192, 96]) from checkpoint, the shape in current model is torch.Size([96, 1, 1, 1, 192]).
size mismatch for unet.u.u.u.u.u.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 192, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 192]).
size mismatch for unet.u.u.u.u.u.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.u.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.u.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 96, 96]) from checkpoint, the shape in current model is torch.Size([96, 3, 3, 3, 96]).
size mismatch for unet.u.u.u.u.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 96, 80]) from checkpoint, the shape in current model is torch.Size([80, 2, 2, 2, 96]).
size mismatch for unet.u.u.u.u.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 160, 80]) from checkpoint, the shape in current model is torch.Size([80, 1, 1, 1, 160]).
size mismatch for unet.u.u.u.u.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 160, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 160]).
size mismatch for unet.u.u.u.u.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.u.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.u.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 80, 80]) from checkpoint, the shape in current model is torch.Size([80, 3, 3, 3, 80]).
size mismatch for unet.u.u.u.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 80, 64]) from checkpoint, the shape in current model is torch.Size([64, 2, 2, 2, 80]).
size mismatch for unet.u.u.u.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 128, 64]) from checkpoint, the shape in current model is torch.Size([64, 1, 1, 1, 128]).
size mismatch for unet.u.u.u.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 128, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 128]).
size mismatch for unet.u.u.u.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.u.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.u.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).
size mismatch for unet.u.u.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 64, 48]) from checkpoint, the shape in current model is torch.Size([48, 2, 2, 2, 64]).
size mismatch for unet.u.u.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 96, 48]) from checkpoint, the shape in current model is torch.Size([48, 1, 1, 1, 96]).
size mismatch for unet.u.u.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 96, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 96]).
size mismatch for unet.u.u.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.u.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.u.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 48, 48]) from checkpoint, the shape in current model is torch.Size([48, 3, 3, 3, 48]).
size mismatch for unet.u.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 48, 32]) from checkpoint, the shape in current model is torch.Size([32, 2, 2, 2, 48]).
size mismatch for unet.u.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 64, 32]) from checkpoint, the shape in current model is torch.Size([32, 1, 1, 1, 64]).
size mismatch for unet.u.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 64, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 64]).
size mismatch for unet.u.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.u.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.u.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for unet.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 32, 16]) from checkpoint, the shape in current model is torch.Size([16, 2, 2, 2, 32]).
size mismatch for unet.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 32, 16]) from checkpoint, the shape in current model is torch.Size([16, 1, 1, 1, 32]).
size mismatch for unet.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 32]).
size mismatch for unet.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for unet.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for unet.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.conv.2.weight: copying a param with shape torch.Size([2, 2, 2, 16, 32]) from checkpoint, the shape in current model is torch.Size([32, 2, 2, 2, 16]).
size mismatch for score_unet.u.blocks.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for score_unet.u.blocks.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for score_unet.u.blocks.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for score_unet.u.blocks.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 3, 3, 32]).
size mismatch for score_unet.deconv.2.weight: copying a param with shape torch.Size([2, 2, 2, 32, 16]) from checkpoint, the shape in current model is torch.Size([16, 2, 2, 2, 32]).
size mismatch for score_unet.blocks_tail.block0.i_branch.0.weight: copying a param with shape torch.Size([1, 1, 1, 32, 16]) from checkpoint, the shape in current model is torch.Size([16, 1, 1, 1, 32]).
size mismatch for score_unet.blocks_tail.block0.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 32, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 32]).
size mismatch for score_unet.blocks_tail.block0.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.blocks_tail.block1.conv_branch.2.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
size mismatch for score_unet.blocks_tail.block1.conv_branch.5.weight: copying a param with shape torch.Size([3, 3, 3, 16, 16]) from checkpoint, the shape in current model is torch.Size([16, 3, 3, 3, 16]).
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