Could you please realse a more detailed description to repeat the MVP results in NUS dataset

[PLester]

these keys have mismatched shape:
+-------------------------------+---------------------------------+---------------------------------+
| key | expected shape | loaded shape |
+-------------------------------+---------------------------------+---------------------------------+
| backbone.conv_input.0.weight | torch.Size([16, 3, 3, 3, 5]) | torch.Size([3, 3, 3, 5, 16]) |
| backbone.conv1.0.conv1.weight | torch.Size([16, 3, 3, 3, 16]) | torch.Size([3, 3, 3, 16, 16]) |
| backbone.conv1.0.conv2.weight | torch.Size([16, 3, 3, 3, 16]) | torch.Size([3, 3, 3, 16, 16]) |
| backbone.conv1.1.conv1.weight | torch.Size([16, 3, 3, 3, 16]) | torch.Size([3, 3, 3, 16, 16]) |
| backbone.conv1.1.conv2.weight | torch.Size([16, 3, 3, 3, 16]) | torch.Size([3, 3, 3, 16, 16]) |
| backbone.conv2.0.weight | torch.Size([32, 3, 3, 3, 16]) | torch.Size([3, 3, 3, 16, 32]) |
| backbone.conv2.3.conv1.weight | torch.Size([32, 3, 3, 3, 32]) | torch.Size([3, 3, 3, 32, 32]) |
| backbone.conv2.3.conv2.weight | torch.Size([32, 3, 3, 3, 32]) | torch.Size([3, 3, 3, 32, 32]) |
| backbone.conv2.4.conv1.weight | torch.Size([32, 3, 3, 3, 32]) | torch.Size([3, 3, 3, 32, 32]) |
| backbone.conv2.4.conv2.weight | torch.Size([32, 3, 3, 3, 32]) | torch.Size([3, 3, 3, 32, 32]) |
| backbone.conv3.0.weight | torch.Size([64, 3, 3, 3, 32]) | torch.Size([3, 3, 3, 32, 64]) |
| backbone.conv3.3.conv1.weight | torch.Size([64, 3, 3, 3, 64]) | torch.Size([3, 3, 3, 64, 64]) |
| backbone.conv3.3.conv2.weight | torch.Size([64, 3, 3, 3, 64]) | torch.Size([3, 3, 3, 64, 64]) |
| backbone.conv3.4.conv1.weight | torch.Size([64, 3, 3, 3, 64]) | torch.Size([3, 3, 3, 64, 64]) |
| backbone.conv3.4.conv2.weight | torch.Size([64, 3, 3, 3, 64]) | torch.Size([3, 3, 3, 64, 64]) |
| backbone.conv4.0.weight | torch.Size([128, 3, 3, 3, 64]) | torch.Size([3, 3, 3, 64, 128]) |
| backbone.conv4.3.conv1.weight | torch.Size([128, 3, 3, 3, 128]) | torch.Size([3, 3, 3, 128, 128]) |
| backbone.conv4.3.conv2.weight | torch.Size([128, 3, 3, 3, 128]) | torch.Size([3, 3, 3, 128, 128]) |
| backbone.conv4.4.conv1.weight | torch.Size([128, 3, 3, 3, 128]) | torch.Size([3, 3, 3, 128, 128]) |
| backbone.conv4.4.conv2.weight | torch.Size([128, 3, 3, 3, 128]) | torch.Size([3, 3, 3, 128, 128]) |
| backbone.extra_conv.0.weight | torch.Size([128, 3, 1, 1, 128]) | torch.Size([3, 1, 1, 128, 128]) |
+-------------------------------+---------------------------------+---------------------------------+

[tianweiy]

You are using spconv 2.x. please see their guide for how to run 1.x model in 2.x (they change weight layout in 2.x )

[tianweiy]

https://github.com/traveller59/spconv/blob/master/docs/SPCONV_2_BREAKING_CHANGEs.md

Also 2.x is not tested. So it could get bugs / different result

[PLester]

I had solved this problem by changing to spconv v1.2.1
Thanks SO MUCH!

You are using spconv 2.x. please see their guide for how to run 1.x model in 2.x (they change weight layout in 2.x )