when train vcoco, "RuntimeError: mat1 dim 1 must match mat2 dim 0"

[ChchunY]

File "HOICLIP/models/models_hoiclip/hoiclip.py", line 210, in forward
outputs_verb_class = logit_scale * self.verb_projection(verb_hs) @ self.verb2hoi_proj
RuntimeError: mat1 dim 1 must match mat2 dim 0

[Artanic30]

Hi, could you provide the scripts you used and print the torch tensor shape for verb_hs and self.verb2hoi_proj. I need more information to solve the issue.

[ChchunY]

Hi, could you provide the scripts you used and print the torch tensor shape for verb_hs and self.verb2hoi_proj. I need more information to solve the issue.
I use the following script: python main.py
--output_dir hico/hoiclip
--dataset_file vcoco
--hoi_path data/v-coco
--num_obj_classes 81
--num_verb_classes 29
--backbone resnet50
--num_queries 64
--dec_layers 3
--epochs 90
--lr_drop 60
--use_nms_filter
--fix_clip
--batch_size 8
--pretrained params/detr-r50-pre-2branch-vcoco.pth
--with_clip_label
--with_obj_clip_label
--gradient_accumulation_steps 1
--num_workers 8
--opt_sched "multiStep"
--dataset_root GEN
--model_name HOICLIP
--zero_shot_type default
--resume hico/hoiclip/checkpoint_last.pth
--verb_pth ./tmp/verb.pth
--verb_weight 0.1
--training_free_enhancement_path
./training_free_ehnahcement/

verb_hs shape: torch.Size([3, 8, 64, 117])
verb2hoi_proj shape: torch.Size([29, 263])

[RuoyuG]

Hi, could you provide the scripts you used and print the torch tensor shape for verb_hs and self.verb2hoi_proj. I need more information to solve the issue.
I use the following script: python main.py
--output_dir hico/hoiclip
--dataset_file vcoco
--hoi_path data/v-coco
--num_obj_classes 81
--num_verb_classes 29
--backbone resnet50
--num_queries 64
--dec_layers 3
--epochs 90
--lr_drop 60
--use_nms_filter
--fix_clip
--batch_size 8
--pretrained params/detr-r50-pre-2branch-vcoco.pth
--with_clip_label
--with_obj_clip_label
--gradient_accumulation_steps 1
--num_workers 8
--opt_sched "multiStep"
--dataset_root GEN
--model_name HOICLIP
--zero_shot_type default
--resume hico/hoiclip/checkpoint_last.pth
--verb_pth ./tmp/verb.pth
--verb_weight 0.1
--training_free_enhancement_path
./training_free_ehnahcement/

verb_hs shape: torch.Size([3, 8, 64, 117]) verb2hoi_proj shape: torch.Size([29, 263])

i meet same problem, how do u fix it?

[guoguo5421]

Hi, could you provide the scripts you used and print the torch tensor shape for verb_hs and self.verb2hoi_proj. I need more information to solve the issue.
I use the following script: python main.py
--output_dir hico/hoiclip
--dataset_file vcoco
--hoi_path data/v-coco
--num_obj_classes 81
--num_verb_classes 29
--backbone resnet50
--num_queries 64
--dec_layers 3
--epochs 90
--lr_drop 60
--use_nms_filter
--fix_clip
--batch_size 8
--pretrained params/detr-r50-pre-2branch-vcoco.pth
--with_clip_label
--with_obj_clip_label
--gradient_accumulation_steps 1
--num_workers 8
--opt_sched "multiStep"
--dataset_root GEN
--model_name HOICLIP
--zero_shot_type default
--resume hico/hoiclip/checkpoint_last.pth
--verb_pth ./tmp/verb.pth
--verb_weight 0.1
--training_free_enhancement_path
./training_free_ehnahcement/

verb_hs shape: torch.Size([3, 8, 64, 117]) verb2hoi_proj shape: torch.Size([29, 263])
i meet the same problem, how do u fix it?