search

wenbowen123 / catgrasp

[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation
Apache License 2.0
298 stars 82 forks source link

size mismatch between ckpt and model #18

Closed waiyc closed 2 years ago

waiyc commented 2 years ago

Hi,

When I run python run_grasp_simulation.py I encountered the error for size mismatch when loading PointGroupPredictor from artifacts/artifacts-77.

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]).
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]).
waiyc commented 2 years ago
Full error report section 2. Click to expand **************************************************************************************************** Current model layers: input_conv.0.weight input_conv.0.bias unet.blocks.block0.conv_branch.0.weight unet.blocks.block0.conv_branch.0.bias unet.blocks.block0.conv_branch.2.weight unet.blocks.block0.conv_branch.2.bias unet.blocks.block0.conv_branch.3.weight unet.blocks.block0.conv_branch.3.bias unet.blocks.block0.conv_branch.5.weight unet.blocks.block0.conv_branch.5.bias unet.blocks.block1.conv_branch.0.weight unet.blocks.block1.conv_branch.0.bias unet.blocks.block1.conv_branch.2.weight unet.blocks.block1.conv_branch.2.bias unet.blocks.block1.conv_branch.3.weight unet.blocks.block1.conv_branch.3.bias unet.blocks.block1.conv_branch.5.weight unet.blocks.block1.conv_branch.5.bias unet.conv.0.weight unet.conv.0.bias unet.conv.2.weight unet.conv.2.bias unet.u.blocks.block0.conv_branch.0.weight unet.u.blocks.block0.conv_branch.0.bias unet.u.blocks.block0.conv_branch.2.weight unet.u.blocks.block0.conv_branch.2.bias unet.u.blocks.block0.conv_branch.3.weight unet.u.blocks.block0.conv_branch.3.bias unet.u.blocks.block0.conv_branch.5.weight unet.u.blocks.block0.conv_branch.5.bias unet.u.blocks.block1.conv_branch.0.weight unet.u.blocks.block1.conv_branch.0.bias unet.u.blocks.block1.conv_branch.2.weight unet.u.blocks.block1.conv_branch.2.bias unet.u.blocks.block1.conv_branch.3.weight unet.u.blocks.block1.conv_branch.3.bias unet.u.blocks.block1.conv_branch.5.weight unet.u.blocks.block1.conv_branch.5.bias unet.u.conv.0.weight unet.u.conv.0.bias unet.u.conv.2.weight unet.u.conv.2.bias unet.u.u.blocks.block0.conv_branch.0.weight unet.u.u.blocks.block0.conv_branch.0.bias unet.u.u.blocks.block0.conv_branch.2.weight unet.u.u.blocks.block0.conv_branch.2.bias unet.u.u.blocks.block0.conv_branch.3.weight unet.u.u.blocks.block0.conv_branch.3.bias unet.u.u.blocks.block0.conv_branch.5.weight unet.u.u.blocks.block0.conv_branch.5.bias unet.u.u.blocks.block1.conv_branch.0.weight unet.u.u.blocks.block1.conv_branch.0.bias unet.u.u.blocks.block1.conv_branch.2.weight unet.u.u.blocks.block1.conv_branch.2.bias unet.u.u.blocks.block1.conv_branch.3.weight unet.u.u.blocks.block1.conv_branch.3.bias unet.u.u.blocks.block1.conv_branch.5.weight unet.u.u.blocks.block1.conv_branch.5.bias unet.u.u.conv.0.weight unet.u.u.conv.0.bias unet.u.u.conv.2.weight unet.u.u.conv.2.bias unet.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.conv.0.weight unet.u.u.u.conv.0.bias unet.u.u.u.conv.2.weight unet.u.u.u.conv.2.bias unet.u.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.u.conv.0.weight unet.u.u.u.u.conv.0.bias unet.u.u.u.u.conv.2.weight unet.u.u.u.u.conv.2.bias unet.u.u.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.u.u.conv.0.weight unet.u.u.u.u.u.conv.0.bias unet.u.u.u.u.u.conv.2.weight unet.u.u.u.u.u.conv.2.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.u.u.deconv.0.weight unet.u.u.u.u.u.deconv.0.bias unet.u.u.u.u.u.deconv.2.weight unet.u.u.u.u.u.deconv.2.bias unet.u.u.u.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.u.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.u.u.u.deconv.0.weight unet.u.u.u.u.deconv.0.bias unet.u.u.u.u.deconv.2.weight unet.u.u.u.u.deconv.2.bias unet.u.u.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.u.u.deconv.0.weight unet.u.u.u.deconv.0.bias unet.u.u.u.deconv.2.weight unet.u.u.u.deconv.2.bias unet.u.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.u.deconv.0.weight unet.u.u.deconv.0.bias unet.u.u.deconv.2.weight unet.u.u.deconv.2.bias unet.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.deconv.0.weight unet.u.deconv.0.bias unet.u.deconv.2.weight unet.u.deconv.2.bias unet.u.blocks_tail.block0.i_branch.0.weight unet.u.blocks_tail.block0.i_branch.0.bias unet.u.blocks_tail.block0.conv_branch.0.weight unet.u.blocks_tail.block0.conv_branch.0.bias unet.u.blocks_tail.block0.conv_branch.2.weight unet.u.blocks_tail.block0.conv_branch.2.bias unet.u.blocks_tail.block0.conv_branch.3.weight unet.u.blocks_tail.block0.conv_branch.3.bias unet.u.blocks_tail.block0.conv_branch.5.weight unet.u.blocks_tail.block0.conv_branch.5.bias unet.u.blocks_tail.block1.conv_branch.0.weight unet.u.blocks_tail.block1.conv_branch.0.bias unet.u.blocks_tail.block1.conv_branch.2.weight unet.u.blocks_tail.block1.conv_branch.2.bias unet.u.blocks_tail.block1.conv_branch.3.weight unet.u.blocks_tail.block1.conv_branch.3.bias unet.u.blocks_tail.block1.conv_branch.5.weight unet.u.blocks_tail.block1.conv_branch.5.bias unet.deconv.0.weight unet.deconv.0.bias unet.deconv.2.weight unet.deconv.2.bias unet.blocks_tail.block0.i_branch.0.weight unet.blocks_tail.block0.i_branch.0.bias unet.blocks_tail.block0.conv_branch.0.weight unet.blocks_tail.block0.conv_branch.0.bias unet.blocks_tail.block0.conv_branch.2.weight unet.blocks_tail.block0.conv_branch.2.bias unet.blocks_tail.block0.conv_branch.3.weight unet.blocks_tail.block0.conv_branch.3.bias unet.blocks_tail.block0.conv_branch.5.weight unet.blocks_tail.block0.conv_branch.5.bias unet.blocks_tail.block1.conv_branch.0.weight unet.blocks_tail.block1.conv_branch.0.bias unet.blocks_tail.block1.conv_branch.2.weight unet.blocks_tail.block1.conv_branch.2.bias unet.blocks_tail.block1.conv_branch.3.weight unet.blocks_tail.block1.conv_branch.3.bias unet.blocks_tail.block1.conv_branch.5.weight unet.blocks_tail.block1.conv_branch.5.bias output_layer.0.weight output_layer.0.bias offset.0.weight offset.0.bias offset.1.weight offset.1.bias offset.3.weight offset.3.bias score_unet.blocks.block0.conv_branch.0.weight score_unet.blocks.block0.conv_branch.0.bias score_unet.blocks.block0.conv_branch.2.weight score_unet.blocks.block0.conv_branch.2.bias score_unet.blocks.block0.conv_branch.3.weight score_unet.blocks.block0.conv_branch.3.bias score_unet.blocks.block0.conv_branch.5.weight score_unet.blocks.block0.conv_branch.5.bias score_unet.blocks.block1.conv_branch.0.weight score_unet.blocks.block1.conv_branch.0.bias score_unet.blocks.block1.conv_branch.2.weight score_unet.blocks.block1.conv_branch.2.bias score_unet.blocks.block1.conv_branch.3.weight score_unet.blocks.block1.conv_branch.3.bias score_unet.blocks.block1.conv_branch.5.weight score_unet.blocks.block1.conv_branch.5.bias score_unet.conv.0.weight score_unet.conv.0.bias score_unet.conv.2.weight score_unet.conv.2.bias score_unet.u.blocks.block0.conv_branch.0.weight score_unet.u.blocks.block0.conv_branch.0.bias score_unet.u.blocks.block0.conv_branch.2.weight score_unet.u.blocks.block0.conv_branch.2.bias score_unet.u.blocks.block0.conv_branch.3.weight score_unet.u.blocks.block0.conv_branch.3.bias score_unet.u.blocks.block0.conv_branch.5.weight score_unet.u.blocks.block0.conv_branch.5.bias score_unet.u.blocks.block1.conv_branch.0.weight score_unet.u.blocks.block1.conv_branch.0.bias score_unet.u.blocks.block1.conv_branch.2.weight score_unet.u.blocks.block1.conv_branch.2.bias score_unet.u.blocks.block1.conv_branch.3.weight score_unet.u.blocks.block1.conv_branch.3.bias score_unet.u.blocks.block1.conv_branch.5.weight score_unet.u.blocks.block1.conv_branch.5.bias score_unet.deconv.0.weight score_unet.deconv.0.bias score_unet.deconv.2.weight score_unet.deconv.2.bias score_unet.blocks_tail.block0.i_branch.0.weight score_unet.blocks_tail.block0.i_branch.0.bias score_unet.blocks_tail.block0.conv_branch.0.weight score_unet.blocks_tail.block0.conv_branch.0.bias score_unet.blocks_tail.block0.conv_branch.2.weight score_unet.blocks_tail.block0.conv_branch.2.bias score_unet.blocks_tail.block0.conv_branch.3.weight score_unet.blocks_tail.block0.conv_branch.3.bias score_unet.blocks_tail.block0.conv_branch.5.weight score_unet.blocks_tail.block0.conv_branch.5.bias score_unet.blocks_tail.block1.conv_branch.0.weight score_unet.blocks_tail.block1.conv_branch.0.bias score_unet.blocks_tail.block1.conv_branch.2.weight score_unet.blocks_tail.block1.conv_branch.2.bias score_unet.blocks_tail.block1.conv_branch.3.weight score_unet.blocks_tail.block1.conv_branch.3.bias score_unet.blocks_tail.block1.conv_branch.5.weight score_unet.blocks_tail.block1.conv_branch.5.bias score_outputlayer.0.weight score_outputlayer.0.bias score_linear.weight score_linear.bias **************************************************************************************************** ckpt layers: input_conv.0.weight input_conv.0.bias unet.blocks.block0.conv_branch.0.weight unet.blocks.block0.conv_branch.0.bias unet.blocks.block0.conv_branch.0.running_mean unet.blocks.block0.conv_branch.0.running_var unet.blocks.block0.conv_branch.0.num_batches_tracked unet.blocks.block0.conv_branch.2.weight unet.blocks.block0.conv_branch.2.bias unet.blocks.block0.conv_branch.3.weight unet.blocks.block0.conv_branch.3.bias unet.blocks.block0.conv_branch.3.running_mean unet.blocks.block0.conv_branch.3.running_var unet.blocks.block0.conv_branch.3.num_batches_tracked unet.blocks.block0.conv_branch.5.weight unet.blocks.block0.conv_branch.5.bias unet.blocks.block1.conv_branch.0.weight unet.blocks.block1.conv_branch.0.bias unet.blocks.block1.conv_branch.0.running_mean unet.blocks.block1.conv_branch.0.running_var unet.blocks.block1.conv_branch.0.num_batches_tracked unet.blocks.block1.conv_branch.2.weight unet.blocks.block1.conv_branch.2.bias unet.blocks.block1.conv_branch.3.weight unet.blocks.block1.conv_branch.3.bias unet.blocks.block1.conv_branch.3.running_mean unet.blocks.block1.conv_branch.3.running_var unet.blocks.block1.conv_branch.3.num_batches_tracked unet.blocks.block1.conv_branch.5.weight unet.blocks.block1.conv_branch.5.bias unet.conv.0.weight unet.conv.0.bias unet.conv.0.running_mean unet.conv.0.running_var unet.conv.0.num_batches_tracked unet.conv.2.weight unet.conv.2.bias unet.u.blocks.block0.conv_branch.0.weight unet.u.blocks.block0.conv_branch.0.bias unet.u.blocks.block0.conv_branch.0.running_mean unet.u.blocks.block0.conv_branch.0.running_var unet.u.blocks.block0.conv_branch.0.num_batches_tracked unet.u.blocks.block0.conv_branch.2.weight unet.u.blocks.block0.conv_branch.2.bias unet.u.blocks.block0.conv_branch.3.weight unet.u.blocks.block0.conv_branch.3.bias unet.u.blocks.block0.conv_branch.3.running_mean unet.u.blocks.block0.conv_branch.3.running_var unet.u.blocks.block0.conv_branch.3.num_batches_tracked unet.u.blocks.block0.conv_branch.5.weight unet.u.blocks.block0.conv_branch.5.bias unet.u.blocks.block1.conv_branch.0.weight unet.u.blocks.block1.conv_branch.0.bias unet.u.blocks.block1.conv_branch.0.running_mean unet.u.blocks.block1.conv_branch.0.running_var unet.u.blocks.block1.conv_branch.0.num_batches_tracked unet.u.blocks.block1.conv_branch.2.weight unet.u.blocks.block1.conv_branch.2.bias unet.u.blocks.block1.conv_branch.3.weight unet.u.blocks.block1.conv_branch.3.bias unet.u.blocks.block1.conv_branch.3.running_mean unet.u.blocks.block1.conv_branch.3.running_var unet.u.blocks.block1.conv_branch.3.num_batches_tracked unet.u.blocks.block1.conv_branch.5.weight unet.u.blocks.block1.conv_branch.5.bias unet.u.conv.0.weight unet.u.conv.0.bias unet.u.conv.0.running_mean unet.u.conv.0.running_var unet.u.conv.0.num_batches_tracked unet.u.conv.2.weight unet.u.conv.2.bias unet.u.u.blocks.block0.conv_branch.0.weight unet.u.u.blocks.block0.conv_branch.0.bias unet.u.u.blocks.block0.conv_branch.0.running_mean unet.u.u.blocks.block0.conv_branch.0.running_var unet.u.u.blocks.block0.conv_branch.0.num_batches_tracked unet.u.u.blocks.block0.conv_branch.2.weight unet.u.u.blocks.block0.conv_branch.2.bias unet.u.u.blocks.block0.conv_branch.3.weight unet.u.u.blocks.block0.conv_branch.3.bias unet.u.u.blocks.block0.conv_branch.3.running_mean unet.u.u.blocks.block0.conv_branch.3.running_var unet.u.u.blocks.block0.conv_branch.3.num_batches_tracked unet.u.u.blocks.block0.conv_branch.5.weight unet.u.u.blocks.block0.conv_branch.5.bias unet.u.u.blocks.block1.conv_branch.0.weight unet.u.u.blocks.block1.conv_branch.0.bias unet.u.u.blocks.block1.conv_branch.0.running_mean unet.u.u.blocks.block1.conv_branch.0.running_var unet.u.u.blocks.block1.conv_branch.0.num_batches_tracked unet.u.u.blocks.block1.conv_branch.2.weight unet.u.u.blocks.block1.conv_branch.2.bias unet.u.u.blocks.block1.conv_branch.3.weight unet.u.u.blocks.block1.conv_branch.3.bias unet.u.u.blocks.block1.conv_branch.3.running_mean unet.u.u.blocks.block1.conv_branch.3.running_var unet.u.u.blocks.block1.conv_branch.3.num_batches_tracked unet.u.u.blocks.block1.conv_branch.5.weight unet.u.u.blocks.block1.conv_branch.5.bias unet.u.u.conv.0.weight unet.u.u.conv.0.bias unet.u.u.conv.0.running_mean unet.u.u.conv.0.running_var unet.u.u.conv.0.num_batches_tracked unet.u.u.conv.2.weight unet.u.u.conv.2.bias unet.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.blocks.block0.conv_branch.0.running_mean unet.u.u.u.blocks.block0.conv_branch.0.running_var unet.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked unet.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.blocks.block0.conv_branch.3.running_mean unet.u.u.u.blocks.block0.conv_branch.3.running_var unet.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked unet.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.blocks.block1.conv_branch.0.running_mean unet.u.u.u.blocks.block1.conv_branch.0.running_var unet.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked unet.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.blocks.block1.conv_branch.3.running_mean unet.u.u.u.blocks.block1.conv_branch.3.running_var unet.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked unet.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.conv.0.weight unet.u.u.u.conv.0.bias unet.u.u.u.conv.0.running_mean unet.u.u.u.conv.0.running_var unet.u.u.u.conv.0.num_batches_tracked unet.u.u.u.conv.2.weight unet.u.u.u.conv.2.bias unet.u.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.u.blocks.block0.conv_branch.0.running_mean unet.u.u.u.u.blocks.block0.conv_branch.0.running_var unet.u.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked unet.u.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.u.blocks.block0.conv_branch.3.running_mean unet.u.u.u.u.blocks.block0.conv_branch.3.running_var unet.u.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked unet.u.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.u.blocks.block1.conv_branch.0.running_mean unet.u.u.u.u.blocks.block1.conv_branch.0.running_var unet.u.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked unet.u.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.u.blocks.block1.conv_branch.3.running_mean unet.u.u.u.u.blocks.block1.conv_branch.3.running_var unet.u.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked unet.u.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.u.conv.0.weight unet.u.u.u.u.conv.0.bias unet.u.u.u.u.conv.0.running_mean unet.u.u.u.u.conv.0.running_var unet.u.u.u.u.conv.0.num_batches_tracked unet.u.u.u.u.conv.2.weight unet.u.u.u.u.conv.2.bias unet.u.u.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.u.u.blocks.block0.conv_branch.0.running_mean unet.u.u.u.u.u.blocks.block0.conv_branch.0.running_var unet.u.u.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked unet.u.u.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.u.u.blocks.block0.conv_branch.3.running_mean unet.u.u.u.u.u.blocks.block0.conv_branch.3.running_var unet.u.u.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked unet.u.u.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.u.u.blocks.block1.conv_branch.0.running_mean unet.u.u.u.u.u.blocks.block1.conv_branch.0.running_var unet.u.u.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked unet.u.u.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.u.u.blocks.block1.conv_branch.3.running_mean unet.u.u.u.u.u.blocks.block1.conv_branch.3.running_var unet.u.u.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked unet.u.u.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.u.u.conv.0.weight unet.u.u.u.u.u.conv.0.bias unet.u.u.u.u.u.conv.0.running_mean unet.u.u.u.u.u.conv.0.running_var unet.u.u.u.u.u.conv.0.num_batches_tracked unet.u.u.u.u.u.conv.2.weight unet.u.u.u.u.u.conv.2.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.running_mean unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.running_var unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked unet.u.u.u.u.u.u.blocks.block0.conv_branch.2.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.2.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.bias unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.running_mean unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.running_var unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked unet.u.u.u.u.u.u.blocks.block0.conv_branch.5.weight unet.u.u.u.u.u.u.blocks.block0.conv_branch.5.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.running_mean unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.running_var unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked unet.u.u.u.u.u.u.blocks.block1.conv_branch.2.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.2.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.bias unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.running_mean unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.running_var unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked unet.u.u.u.u.u.u.blocks.block1.conv_branch.5.weight unet.u.u.u.u.u.u.blocks.block1.conv_branch.5.bias unet.u.u.u.u.u.deconv.0.weight unet.u.u.u.u.u.deconv.0.bias unet.u.u.u.u.u.deconv.0.running_mean unet.u.u.u.u.u.deconv.0.running_var unet.u.u.u.u.u.deconv.0.num_batches_tracked unet.u.u.u.u.u.deconv.2.weight unet.u.u.u.u.u.deconv.2.bias unet.u.u.u.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.u.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.running_mean unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.running_var unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked unet.u.u.u.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.running_mean unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.running_var unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked unet.u.u.u.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.u.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.running_mean unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.running_var unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked unet.u.u.u.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.running_mean unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.running_var unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked unet.u.u.u.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.u.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.u.u.u.deconv.0.weight unet.u.u.u.u.deconv.0.bias unet.u.u.u.u.deconv.0.running_mean unet.u.u.u.u.deconv.0.running_var unet.u.u.u.u.deconv.0.num_batches_tracked unet.u.u.u.u.deconv.2.weight unet.u.u.u.u.deconv.2.bias unet.u.u.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.0.running_mean unet.u.u.u.u.blocks_tail.block0.conv_branch.0.running_var unet.u.u.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked unet.u.u.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.u.u.blocks_tail.block0.conv_branch.3.running_mean unet.u.u.u.u.blocks_tail.block0.conv_branch.3.running_var unet.u.u.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked unet.u.u.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.0.running_mean unet.u.u.u.u.blocks_tail.block1.conv_branch.0.running_var unet.u.u.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked unet.u.u.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.u.u.blocks_tail.block1.conv_branch.3.running_mean unet.u.u.u.u.blocks_tail.block1.conv_branch.3.running_var unet.u.u.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked unet.u.u.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.u.u.deconv.0.weight unet.u.u.u.deconv.0.bias unet.u.u.u.deconv.0.running_mean unet.u.u.u.deconv.0.running_var unet.u.u.u.deconv.0.num_batches_tracked unet.u.u.u.deconv.2.weight unet.u.u.u.deconv.2.bias unet.u.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.u.blocks_tail.block0.conv_branch.0.running_mean unet.u.u.u.blocks_tail.block0.conv_branch.0.running_var unet.u.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked unet.u.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.u.blocks_tail.block0.conv_branch.3.running_mean unet.u.u.u.blocks_tail.block0.conv_branch.3.running_var unet.u.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked unet.u.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.u.blocks_tail.block1.conv_branch.0.running_mean unet.u.u.u.blocks_tail.block1.conv_branch.0.running_var unet.u.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked unet.u.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.u.blocks_tail.block1.conv_branch.3.running_mean unet.u.u.u.blocks_tail.block1.conv_branch.3.running_var unet.u.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked unet.u.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.u.deconv.0.weight unet.u.u.deconv.0.bias unet.u.u.deconv.0.running_mean unet.u.u.deconv.0.running_var unet.u.u.deconv.0.num_batches_tracked unet.u.u.deconv.2.weight unet.u.u.deconv.2.bias unet.u.u.blocks_tail.block0.i_branch.0.weight unet.u.u.blocks_tail.block0.i_branch.0.bias unet.u.u.blocks_tail.block0.conv_branch.0.weight unet.u.u.blocks_tail.block0.conv_branch.0.bias unet.u.u.blocks_tail.block0.conv_branch.0.running_mean unet.u.u.blocks_tail.block0.conv_branch.0.running_var unet.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked unet.u.u.blocks_tail.block0.conv_branch.2.weight unet.u.u.blocks_tail.block0.conv_branch.2.bias unet.u.u.blocks_tail.block0.conv_branch.3.weight unet.u.u.blocks_tail.block0.conv_branch.3.bias unet.u.u.blocks_tail.block0.conv_branch.3.running_mean unet.u.u.blocks_tail.block0.conv_branch.3.running_var unet.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked unet.u.u.blocks_tail.block0.conv_branch.5.weight unet.u.u.blocks_tail.block0.conv_branch.5.bias unet.u.u.blocks_tail.block1.conv_branch.0.weight unet.u.u.blocks_tail.block1.conv_branch.0.bias unet.u.u.blocks_tail.block1.conv_branch.0.running_mean unet.u.u.blocks_tail.block1.conv_branch.0.running_var unet.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked unet.u.u.blocks_tail.block1.conv_branch.2.weight unet.u.u.blocks_tail.block1.conv_branch.2.bias unet.u.u.blocks_tail.block1.conv_branch.3.weight unet.u.u.blocks_tail.block1.conv_branch.3.bias unet.u.u.blocks_tail.block1.conv_branch.3.running_mean unet.u.u.blocks_tail.block1.conv_branch.3.running_var unet.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked unet.u.u.blocks_tail.block1.conv_branch.5.weight unet.u.u.blocks_tail.block1.conv_branch.5.bias unet.u.deconv.0.weight unet.u.deconv.0.bias unet.u.deconv.0.running_mean unet.u.deconv.0.running_var unet.u.deconv.0.num_batches_tracked unet.u.deconv.2.weight unet.u.deconv.2.bias unet.u.blocks_tail.block0.i_branch.0.weight unet.u.blocks_tail.block0.i_branch.0.bias unet.u.blocks_tail.block0.conv_branch.0.weight unet.u.blocks_tail.block0.conv_branch.0.bias unet.u.blocks_tail.block0.conv_branch.0.running_mean unet.u.blocks_tail.block0.conv_branch.0.running_var unet.u.blocks_tail.block0.conv_branch.0.num_batches_tracked unet.u.blocks_tail.block0.conv_branch.2.weight unet.u.blocks_tail.block0.conv_branch.2.bias unet.u.blocks_tail.block0.conv_branch.3.weight unet.u.blocks_tail.block0.conv_branch.3.bias unet.u.blocks_tail.block0.conv_branch.3.running_mean unet.u.blocks_tail.block0.conv_branch.3.running_var unet.u.blocks_tail.block0.conv_branch.3.num_batches_tracked unet.u.blocks_tail.block0.conv_branch.5.weight unet.u.blocks_tail.block0.conv_branch.5.bias unet.u.blocks_tail.block1.conv_branch.0.weight unet.u.blocks_tail.block1.conv_branch.0.bias unet.u.blocks_tail.block1.conv_branch.0.running_mean unet.u.blocks_tail.block1.conv_branch.0.running_var unet.u.blocks_tail.block1.conv_branch.0.num_batches_tracked unet.u.blocks_tail.block1.conv_branch.2.weight unet.u.blocks_tail.block1.conv_branch.2.bias unet.u.blocks_tail.block1.conv_branch.3.weight unet.u.blocks_tail.block1.conv_branch.3.bias unet.u.blocks_tail.block1.conv_branch.3.running_mean unet.u.blocks_tail.block1.conv_branch.3.running_var unet.u.blocks_tail.block1.conv_branch.3.num_batches_tracked unet.u.blocks_tail.block1.conv_branch.5.weight unet.u.blocks_tail.block1.conv_branch.5.bias unet.deconv.0.weight unet.deconv.0.bias unet.deconv.0.running_mean unet.deconv.0.running_var unet.deconv.0.num_batches_tracked unet.deconv.2.weight unet.deconv.2.bias unet.blocks_tail.block0.i_branch.0.weight unet.blocks_tail.block0.i_branch.0.bias unet.blocks_tail.block0.conv_branch.0.weight unet.blocks_tail.block0.conv_branch.0.bias unet.blocks_tail.block0.conv_branch.0.running_mean unet.blocks_tail.block0.conv_branch.0.running_var unet.blocks_tail.block0.conv_branch.0.num_batches_tracked unet.blocks_tail.block0.conv_branch.2.weight unet.blocks_tail.block0.conv_branch.2.bias unet.blocks_tail.block0.conv_branch.3.weight unet.blocks_tail.block0.conv_branch.3.bias unet.blocks_tail.block0.conv_branch.3.running_mean unet.blocks_tail.block0.conv_branch.3.running_var unet.blocks_tail.block0.conv_branch.3.num_batches_tracked unet.blocks_tail.block0.conv_branch.5.weight unet.blocks_tail.block0.conv_branch.5.bias unet.blocks_tail.block1.conv_branch.0.weight unet.blocks_tail.block1.conv_branch.0.bias unet.blocks_tail.block1.conv_branch.0.running_mean unet.blocks_tail.block1.conv_branch.0.running_var unet.blocks_tail.block1.conv_branch.0.num_batches_tracked unet.blocks_tail.block1.conv_branch.2.weight unet.blocks_tail.block1.conv_branch.2.bias unet.blocks_tail.block1.conv_branch.3.weight unet.blocks_tail.block1.conv_branch.3.bias unet.blocks_tail.block1.conv_branch.3.running_mean unet.blocks_tail.block1.conv_branch.3.running_var unet.blocks_tail.block1.conv_branch.3.num_batches_tracked unet.blocks_tail.block1.conv_branch.5.weight unet.blocks_tail.block1.conv_branch.5.bias output_layer.0.weight output_layer.0.bias output_layer.0.running_mean output_layer.0.running_var output_layer.0.num_batches_tracked offset.0.weight offset.0.bias offset.1.weight offset.1.bias offset.1.running_mean offset.1.running_var offset.1.num_batches_tracked offset.3.weight offset.3.bias score_unet.blocks.block0.conv_branch.0.weight score_unet.blocks.block0.conv_branch.0.bias score_unet.blocks.block0.conv_branch.0.running_mean score_unet.blocks.block0.conv_branch.0.running_var score_unet.blocks.block0.conv_branch.0.num_batches_tracked score_unet.blocks.block0.conv_branch.2.weight score_unet.blocks.block0.conv_branch.2.bias score_unet.blocks.block0.conv_branch.3.weight score_unet.blocks.block0.conv_branch.3.bias score_unet.blocks.block0.conv_branch.3.running_mean score_unet.blocks.block0.conv_branch.3.running_var score_unet.blocks.block0.conv_branch.3.num_batches_tracked score_unet.blocks.block0.conv_branch.5.weight score_unet.blocks.block0.conv_branch.5.bias score_unet.blocks.block1.conv_branch.0.weight score_unet.blocks.block1.conv_branch.0.bias score_unet.blocks.block1.conv_branch.0.running_mean score_unet.blocks.block1.conv_branch.0.running_var score_unet.blocks.block1.conv_branch.0.num_batches_tracked score_unet.blocks.block1.conv_branch.2.weight score_unet.blocks.block1.conv_branch.2.bias score_unet.blocks.block1.conv_branch.3.weight score_unet.blocks.block1.conv_branch.3.bias score_unet.blocks.block1.conv_branch.3.running_mean score_unet.blocks.block1.conv_branch.3.running_var score_unet.blocks.block1.conv_branch.3.num_batches_tracked score_unet.blocks.block1.conv_branch.5.weight score_unet.blocks.block1.conv_branch.5.bias score_unet.conv.0.weight score_unet.conv.0.bias score_unet.conv.0.running_mean score_unet.conv.0.running_var score_unet.conv.0.num_batches_tracked score_unet.conv.2.weight score_unet.conv.2.bias score_unet.u.blocks.block0.conv_branch.0.weight score_unet.u.blocks.block0.conv_branch.0.bias score_unet.u.blocks.block0.conv_branch.0.running_mean score_unet.u.blocks.block0.conv_branch.0.running_var score_unet.u.blocks.block0.conv_branch.0.num_batches_tracked score_unet.u.blocks.block0.conv_branch.2.weight score_unet.u.blocks.block0.conv_branch.2.bias score_unet.u.blocks.block0.conv_branch.3.weight score_unet.u.blocks.block0.conv_branch.3.bias score_unet.u.blocks.block0.conv_branch.3.running_mean score_unet.u.blocks.block0.conv_branch.3.running_var score_unet.u.blocks.block0.conv_branch.3.num_batches_tracked score_unet.u.blocks.block0.conv_branch.5.weight score_unet.u.blocks.block0.conv_branch.5.bias score_unet.u.blocks.block1.conv_branch.0.weight score_unet.u.blocks.block1.conv_branch.0.bias score_unet.u.blocks.block1.conv_branch.0.running_mean score_unet.u.blocks.block1.conv_branch.0.running_var score_unet.u.blocks.block1.conv_branch.0.num_batches_tracked score_unet.u.blocks.block1.conv_branch.2.weight score_unet.u.blocks.block1.conv_branch.2.bias score_unet.u.blocks.block1.conv_branch.3.weight score_unet.u.blocks.block1.conv_branch.3.bias score_unet.u.blocks.block1.conv_branch.3.running_mean score_unet.u.blocks.block1.conv_branch.3.running_var score_unet.u.blocks.block1.conv_branch.3.num_batches_tracked score_unet.u.blocks.block1.conv_branch.5.weight score_unet.u.blocks.block1.conv_branch.5.bias score_unet.deconv.0.weight score_unet.deconv.0.bias score_unet.deconv.0.running_mean score_unet.deconv.0.running_var score_unet.deconv.0.num_batches_tracked score_unet.deconv.2.weight score_unet.deconv.2.bias score_unet.blocks_tail.block0.i_branch.0.weight score_unet.blocks_tail.block0.i_branch.0.bias score_unet.blocks_tail.block0.conv_branch.0.weight score_unet.blocks_tail.block0.conv_branch.0.bias score_unet.blocks_tail.block0.conv_branch.0.running_mean score_unet.blocks_tail.block0.conv_branch.0.running_var score_unet.blocks_tail.block0.conv_branch.0.num_batches_tracked score_unet.blocks_tail.block0.conv_branch.2.weight score_unet.blocks_tail.block0.conv_branch.2.bias score_unet.blocks_tail.block0.conv_branch.3.weight score_unet.blocks_tail.block0.conv_branch.3.bias score_unet.blocks_tail.block0.conv_branch.3.running_mean score_unet.blocks_tail.block0.conv_branch.3.running_var score_unet.blocks_tail.block0.conv_branch.3.num_batches_tracked score_unet.blocks_tail.block0.conv_branch.5.weight score_unet.blocks_tail.block0.conv_branch.5.bias score_unet.blocks_tail.block1.conv_branch.0.weight score_unet.blocks_tail.block1.conv_branch.0.bias score_unet.blocks_tail.block1.conv_branch.0.running_mean score_unet.blocks_tail.block1.conv_branch.0.running_var score_unet.blocks_tail.block1.conv_branch.0.num_batches_tracked score_unet.blocks_tail.block1.conv_branch.2.weight score_unet.blocks_tail.block1.conv_branch.2.bias score_unet.blocks_tail.block1.conv_branch.3.weight score_unet.blocks_tail.block1.conv_branch.3.bias score_unet.blocks_tail.block1.conv_branch.3.running_mean score_unet.blocks_tail.block1.conv_branch.3.running_var score_unet.blocks_tail.block1.conv_branch.3.num_batches_tracked score_unet.blocks_tail.block1.conv_branch.5.weight score_unet.blocks_tail.block1.conv_branch.5.bias score_outputlayer.0.weight score_outputlayer.0.bias score_outputlayer.0.running_mean score_outputlayer.0.running_var score_outputlayer.0.num_batches_tracked score_linear.weight score_linear.bias **************************************************************************************************** Difference: unet.blocks.block0.conv_branch.0.running_mean not found in cur model unet.blocks.block0.conv_branch.0.running_var not found in cur model unet.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.blocks.block0.conv_branch.3.running_mean not found in cur model unet.blocks.block0.conv_branch.3.running_var not found in cur model unet.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.blocks.block1.conv_branch.0.running_mean not found in cur model unet.blocks.block1.conv_branch.0.running_var not found in cur model unet.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.blocks.block1.conv_branch.3.running_mean not found in cur model unet.blocks.block1.conv_branch.3.running_var not found in cur model unet.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.conv.0.running_mean not found in cur model unet.conv.0.running_var not found in cur model unet.conv.0.num_batches_tracked not found in cur model unet.u.blocks.block0.conv_branch.0.running_mean not found in cur model unet.u.blocks.block0.conv_branch.0.running_var not found in cur model unet.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.blocks.block0.conv_branch.3.running_mean not found in cur model unet.u.blocks.block0.conv_branch.3.running_var not found in cur model unet.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.blocks.block1.conv_branch.0.running_mean not found in cur model unet.u.blocks.block1.conv_branch.0.running_var not found in cur model unet.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.blocks.block1.conv_branch.3.running_mean not found in cur model unet.u.blocks.block1.conv_branch.3.running_var not found in cur model unet.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.conv.0.running_mean not found in cur model unet.u.conv.0.running_var not found in cur model unet.u.conv.0.num_batches_tracked not found in cur model unet.u.u.blocks.block0.conv_branch.0.running_mean not found in cur model unet.u.u.blocks.block0.conv_branch.0.running_var not found in cur model unet.u.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.blocks.block0.conv_branch.3.running_mean not found in cur model unet.u.u.blocks.block0.conv_branch.3.running_var not found in cur model unet.u.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.blocks.block1.conv_branch.0.running_mean not found in cur model unet.u.u.blocks.block1.conv_branch.0.running_var not found in cur model unet.u.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.blocks.block1.conv_branch.3.running_mean not found in cur model unet.u.u.blocks.block1.conv_branch.3.running_var not found in cur model unet.u.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.conv.0.running_mean not found in cur model unet.u.u.conv.0.running_var not found in cur model unet.u.u.conv.0.num_batches_tracked not found in cur model unet.u.u.u.blocks.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.blocks.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.blocks.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.blocks.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.blocks.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.blocks.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.blocks.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.blocks.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.conv.0.running_mean not found in cur model unet.u.u.u.conv.0.running_var not found in cur model unet.u.u.u.conv.0.num_batches_tracked not found in cur model unet.u.u.u.u.blocks.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.blocks.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.blocks.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.blocks.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.blocks.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.blocks.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.blocks.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.blocks.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.conv.0.running_mean not found in cur model unet.u.u.u.u.conv.0.running_var not found in cur model unet.u.u.u.u.conv.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.u.blocks.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.u.blocks.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.u.blocks.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.u.blocks.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.u.conv.0.running_mean not found in cur model unet.u.u.u.u.u.conv.0.running_var not found in cur model unet.u.u.u.u.u.conv.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.u.u.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.u.u.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.u.u.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.u.u.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.u.deconv.0.running_mean not found in cur model unet.u.u.u.u.u.deconv.0.running_var not found in cur model unet.u.u.u.u.u.deconv.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.deconv.0.running_mean not found in cur model unet.u.u.u.u.deconv.0.running_var not found in cur model unet.u.u.u.u.deconv.0.num_batches_tracked not found in cur model unet.u.u.u.u.blocks_tail.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.blocks_tail.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.blocks_tail.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.blocks_tail.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.u.blocks_tail.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.u.blocks_tail.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.u.blocks_tail.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.u.blocks_tail.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.deconv.0.running_mean not found in cur model unet.u.u.u.deconv.0.running_var not found in cur model unet.u.u.u.deconv.0.num_batches_tracked not found in cur model unet.u.u.u.blocks_tail.block0.conv_branch.0.running_mean not found in cur model unet.u.u.u.blocks_tail.block0.conv_branch.0.running_var not found in cur model unet.u.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.blocks_tail.block0.conv_branch.3.running_mean not found in cur model unet.u.u.u.blocks_tail.block0.conv_branch.3.running_var not found in cur model unet.u.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.u.blocks_tail.block1.conv_branch.0.running_mean not found in cur model unet.u.u.u.blocks_tail.block1.conv_branch.0.running_var not found in cur model unet.u.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.u.blocks_tail.block1.conv_branch.3.running_mean not found in cur model unet.u.u.u.blocks_tail.block1.conv_branch.3.running_var not found in cur model unet.u.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.deconv.0.running_mean not found in cur model unet.u.u.deconv.0.running_var not found in cur model unet.u.u.deconv.0.num_batches_tracked not found in cur model unet.u.u.blocks_tail.block0.conv_branch.0.running_mean not found in cur model unet.u.u.blocks_tail.block0.conv_branch.0.running_var not found in cur model unet.u.u.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.blocks_tail.block0.conv_branch.3.running_mean not found in cur model unet.u.u.blocks_tail.block0.conv_branch.3.running_var not found in cur model unet.u.u.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.u.blocks_tail.block1.conv_branch.0.running_mean not found in cur model unet.u.u.blocks_tail.block1.conv_branch.0.running_var not found in cur model unet.u.u.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.u.blocks_tail.block1.conv_branch.3.running_mean not found in cur model unet.u.u.blocks_tail.block1.conv_branch.3.running_var not found in cur model unet.u.u.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model unet.u.deconv.0.running_mean not found in cur model unet.u.deconv.0.running_var not found in cur model unet.u.deconv.0.num_batches_tracked not found in cur model unet.u.blocks_tail.block0.conv_branch.0.running_mean not found in cur model unet.u.blocks_tail.block0.conv_branch.0.running_var not found in cur model unet.u.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model unet.u.blocks_tail.block0.conv_branch.3.running_mean not found in cur model unet.u.blocks_tail.block0.conv_branch.3.running_var not found in cur model unet.u.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model unet.u.blocks_tail.block1.conv_branch.0.running_mean not found in cur model unet.u.blocks_tail.block1.conv_branch.0.running_var not found in cur model unet.u.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model unet.u.blocks_tail.block1.conv_branch.3.running_mean not found in cur model unet.u.blocks_tail.block1.conv_branch.3.running_var not found in cur model unet.u.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model unet.deconv.0.running_mean not found in cur model unet.deconv.0.running_var not found in cur model unet.deconv.0.num_batches_tracked not found in cur model unet.blocks_tail.block0.conv_branch.0.running_mean not found in cur model unet.blocks_tail.block0.conv_branch.0.running_var not found in cur model unet.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model unet.blocks_tail.block0.conv_branch.3.running_mean not found in cur model unet.blocks_tail.block0.conv_branch.3.running_var not found in cur model unet.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model unet.blocks_tail.block1.conv_branch.0.running_mean not found in cur model unet.blocks_tail.block1.conv_branch.0.running_var not found in cur model unet.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model unet.blocks_tail.block1.conv_branch.3.running_mean not found in cur model unet.blocks_tail.block1.conv_branch.3.running_var not found in cur model unet.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model output_layer.0.running_mean not found in cur model output_layer.0.running_var not found in cur model output_layer.0.num_batches_tracked not found in cur model offset.1.running_mean not found in cur model offset.1.running_var not found in cur model offset.1.num_batches_tracked not found in cur model score_unet.blocks.block0.conv_branch.0.running_mean not found in cur model score_unet.blocks.block0.conv_branch.0.running_var not found in cur model score_unet.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model score_unet.blocks.block0.conv_branch.3.running_mean not found in cur model score_unet.blocks.block0.conv_branch.3.running_var not found in cur model score_unet.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model score_unet.blocks.block1.conv_branch.0.running_mean not found in cur model score_unet.blocks.block1.conv_branch.0.running_var not found in cur model score_unet.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model score_unet.blocks.block1.conv_branch.3.running_mean not found in cur model score_unet.blocks.block1.conv_branch.3.running_var not found in cur model score_unet.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model score_unet.conv.0.running_mean not found in cur model score_unet.conv.0.running_var not found in cur model score_unet.conv.0.num_batches_tracked not found in cur model score_unet.u.blocks.block0.conv_branch.0.running_mean not found in cur model score_unet.u.blocks.block0.conv_branch.0.running_var not found in cur model score_unet.u.blocks.block0.conv_branch.0.num_batches_tracked not found in cur model score_unet.u.blocks.block0.conv_branch.3.running_mean not found in cur model score_unet.u.blocks.block0.conv_branch.3.running_var not found in cur model score_unet.u.blocks.block0.conv_branch.3.num_batches_tracked not found in cur model score_unet.u.blocks.block1.conv_branch.0.running_mean not found in cur model score_unet.u.blocks.block1.conv_branch.0.running_var not found in cur model score_unet.u.blocks.block1.conv_branch.0.num_batches_tracked not found in cur model score_unet.u.blocks.block1.conv_branch.3.running_mean not found in cur model score_unet.u.blocks.block1.conv_branch.3.running_var not found in cur model score_unet.u.blocks.block1.conv_branch.3.num_batches_tracked not found in cur model score_unet.deconv.0.running_mean not found in cur model score_unet.deconv.0.running_var not found in cur model score_unet.deconv.0.num_batches_tracked not found in cur model score_unet.blocks_tail.block0.conv_branch.0.running_mean not found in cur model score_unet.blocks_tail.block0.conv_branch.0.running_var not found in cur model score_unet.blocks_tail.block0.conv_branch.0.num_batches_tracked not found in cur model score_unet.blocks_tail.block0.conv_branch.3.running_mean not found in cur model score_unet.blocks_tail.block0.conv_branch.3.running_var not found in cur model score_unet.blocks_tail.block0.conv_branch.3.num_batches_tracked not found in cur model score_unet.blocks_tail.block1.conv_branch.0.running_mean not found in cur model score_unet.blocks_tail.block1.conv_branch.0.running_var not found in cur model score_unet.blocks_tail.block1.conv_branch.0.num_batches_tracked not found in cur model score_unet.blocks_tail.block1.conv_branch.3.running_mean not found in cur model score_unet.blocks_tail.block1.conv_branch.3.running_var not found in cur model score_unet.blocks_tail.block1.conv_branch.3.num_batches_tracked not found in cur model score_outputlayer.0.running_mean not found in cur model score_outputlayer.0.running_var not found in cur model score_outputlayer.0.num_batches_tracked not found in cur model Traceback (most recent call last): File "/home/waiyc/catkin_test_catgrasp/catgrasp/Utils.py", line 148, in load_model model.load_state_dict(state_dict) File "/home/waiyc/anaconda3/envs/catgrasp_conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1483, in load_state_dict self.__class__.__name__, "\n\t".join(error_msgs))) RuntimeError: 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]). During handling of the above exception, another exception occurred: Traceback (most recent call last): File "run_grasp_simulation.py", line 715, in seg_predicter = PointGroupPredictor(class_name) File "/home/waiyc/catkin_test_catgrasp/catgrasp/predicter.py", line 228, in __init__ self.model = load_model(self.model,ckpt_dir='{}/best_val.pth.tar'.format(artifact_dir)) File "/home/waiyc/catkin_test_catgrasp/catgrasp/Utils.py", line 172, in load_model raise RuntimeError RuntimeError
wenbowen123 commented 2 years ago

Did you run inside docker container and build as suggested in readme?

waiyc commented 2 years ago

Hi @wenbowen123 ,

Thank for the reply. I have sucessfully run the simulation after a retrain. I will close this for now.