There is a runtime error

[happyfox-dot]

Hello, thank you for your open source code.
I am using sh scripts/test_ sence. sh encountered the following problem when executing the command, which was caused by mismatched parameters.
Please tell me your sense.pth file
How did you get it? Can you share it?
Error(s) in loading state_dict for SemanticPrediction: size mismatch for input_conv.0.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.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 linear_semantics.weight: copying a param with shape torch.Size([2, 32]) from checkpoint, the shape in current model is torch.Size([10, 32]). size mismatch for linear_semantics.bias: copying a param with shape torch.Size([2]) from checkpoint, the shape in current model is torch.Size([10]).

[zuixiaosanlang]

@happyfox-xie

change 10 to 2
can solve this problem