Extra key in ucf101.pt
wang-muhan opened this issue · comments
When I'm loading the pretrained ucf101 checkpoint, the error appears:
RuntimeError: Error(s) in loading state_dict for Latte:
Unexpected key(s) in state_dict: "y_embedder.embedding_table.weight".
All the other checkpoints can generate videos successfully, can you check this? Thank you
When I'm loading the pretrained ucf101 checkpoint, the error appears: RuntimeError: Error(s) in loading state_dict for Latte: Unexpected key(s) in state_dict: "y_embedder.embedding_table.weight". All the other checkpoints can generate videos successfully, can you check this? Thank you
Hi, can I confirm whether the extras parameter is 2 when you use the ucf101 pre-train model? See:
Latte/configs/ucf101/ucf101_sample.yaml
Line 14 in 9ededbe
Do you have pretrained models for unconditional generation?
Do you have pretrained models for unconditional generation?
All pre-trained models are unconditional generation except ucf101 and t2v.
Thanks. How can I control the class being sampled, is it "sample_names" in the ucf101_sample.yaml? But I didn't found where you reference this value in your code
Thanks. How can I control the class being sampled, is it "sample_names" in the ucf101_sample.yaml? But I didn't found where you reference this value in your code
You can change the class label in here,
Line 90 in 9ededbe
What's you training loss after converge? I want to reproduce but met some problem.
What's you training loss after converge? I want to reproduce but met some problem.
Training loss decreases quickly and oscillates around a value.