While evaluating using pretrained models (https://github.com/garyzhao/SemGCN#evaluating-our-pretrained-models)

[v1093]

for e.g., with SemGCN with non-local blocks

RuntimeError: Error(s) in loading state_dict for SemGCN:
	size mismatch for gconv_input.0.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.0.gconv1.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.0.gconv2.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.2.gconv1.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.2.gconv2.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.4.gconv1.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.4.gconv2.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.6.gconv1.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_layers.6.gconv2.gconv.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).
	size mismatch for gconv_output.e: copying a param with shape torch.Size([1, 46]) from checkpoint, the shape in current model is torch.Size([1, 49]).

Similar issues with other models.

[garyzhao]

@v1093 Thanks for your feedback.

It seems that you did not use the most recent code to evaluate the pretrained models. Please try the following steps.

1. Delete all *.npz files in "data".
2. Run "git pull" or download the newest version of our code.
3. Follow "data/README.md" to re-generate ground truth data and 2D detections.
4. Evaluate the pretrained models again.

Please let me know if it still does not work.

Best,
Long

[v1093]

Oops, I missed your last changes. It works now. Thanks for the quick response. 👍