fix models path bug

.gitignore

@@ -1,3 +1,9 @@
 logs/
 
 __pycache__/
+
+checkpoints
+
+output/
+
+training/

MarT/scripts/run_finetune_flava.sh

@@ -9,7 +9,7 @@ python main.py \
    --max_epochs=15  \
    --num_workers=4 \
    --model_name_or_path bert-base-uncased \
-   --visual_model_path flava-full \
+   --visual_model_path facebook/flava-full \
    --accumulate_grad_batches 1 \
    --model_class FlavaKGC \
    --batch_size 24 \

MarT/scripts/run_finetune_mkgformer.sh

@@ -9,7 +9,7 @@ python main.py \
    --max_epochs=15  \
    --num_workers=4 \
    --model_name_or_path bert-base-uncased \
-   --visual_model_path clip-vit-base-patch32 \
+   --visual_model_path openai/clip-vit-base-patch32 \
    --accumulate_grad_batches 1 \
    --model_class MKGformerKGC \
    --batch_size 32 \

MarT/scripts/run_finetune_vilt.sh

@@ -9,7 +9,7 @@ python main.py \
    --max_epochs=15  \
    --num_workers=4 \
    --model_name_or_path bert-base-uncased \
-   --visual_model_path vilt-b32-finetuned-vqa \
+   --visual_model_path dandelin/vilt-b32-finetuned-vqa \
    --accumulate_grad_batches 1 \
    --model_class ViltKGC \
    --batch_size 32 \

MarT/scripts/run_finetune_visualbert.sh

@@ -9,7 +9,7 @@ python main.py \
    --max_epochs=15  \
    --num_workers=4 \
    --model_name_or_path bert-base-uncased \
-   --visual_model_path visualbert-vqa-coco-pre \
+   --visual_model_path uclanlp/visualbert-vqa-coco-pre \
    --accumulate_grad_batches 1 \
    --model_class VisualBertKGC \
    --batch_size 64 \

MarT/scripts/run_pretrain_mkgformer.sh

@@ -3,7 +3,7 @@ python main.py \
    --max_epochs=30 \
    --num_workers=4 \
    --model_name_or_path bert-base-uncased \
-   --visual_model_path clip-vit-base-patch32 \
+   --visual_model_path openai/clip-vit-base-patch32 \
    --accumulate_grad_batches 1 \
    --model_class MKGformerKGC \
    --batch_size 64 \

MarT/scripts/run_pretrain_vlp.sh

@@ -4,7 +4,7 @@ python main.py \
    --max_epochs=15 \
    --num_workers=4 \
    --model_name_or_path bert-base-uncased \
-   --visual_model_path flava-full \
+   --visual_model_path facebook/flava-full \
    --accumulate_grad_batches 1 \
    --model_class FlavaKGC \
    --batch_size 24 \

MarT/tools/encode_images_data.py

@@ -12,7 +12,7 @@
 print(len(img_path))
 
 if processor_name == 'clip':
-    processor = CLIPProcessor.from_pretrained('clip-vit-base-patch32')
+    processor = CLIPProcessor.from_pretrained('openai/clip-vit-base-patch32')
 
     entity2visual = {}
     for entity in tqdm(img_path, total=len(img_path)):
@@ -30,7 +30,7 @@
 elif processor_name == 'vilt':
     entity2visual = []
 
-    processor = ViltProcessor.from_pretrained('vilt-b32-finetuned-vqa')
+    processor = ViltProcessor.from_pretrained('dandelin/vilt-b32-finetuned-vqa')
 
     for entity in tqdm(img_path, total=len(img_path)):
         path = os.path.join(base_path, entity)

requirements.txt

@@ -1,4 +1,4 @@
-transformers==4.16.0
+transformers==4.19.0
 torchvision==0.8.0
 scipy==1.6.2
 scikit-learn==1.0.2