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BUG: FileNotFoundError: [Errno 2] No such file or directory: 'vision_features/name_map.json' #10

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psknlr opened this issue Feb 20, 2023 · 2 comments

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@psknlr
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psknlr commented Feb 20, 2023

Thank u for your great work and code, I have tried it, but got this error, can u help me solve it. It seems that lack of the josn files.

CUDA_VISIBLE_DEVICES=0,1 python main.py \

--model allenai/unifiedqa-t5-base \
--user_msg rationale --img_type detr \
--bs 8 --eval_bs 4 --eval_acc 10 --output_len 512 \
--final_eval --prompt_format QCM-LE

args Namespace(bs=8, caption_file='data/captions.json', data_root='data', epoch=20, eval_acc=10, eval_bs=4, eval_le=None, evaluate_dir=None, final_eval=True, img_type='detr', input_len=512, lr=5e-05, model='allenai/unifiedqa-t5-base', options=['A', 'B', 'C', 'D', 'E'], output_dir='experiments', output_len=512, prompt_format='QCM-LE', seed=42, test_le=None, test_split='test', train_split='train', use_caption=False, use_generate=False, user_msg='rationale', val_split='val')
====Input Arguments====
{
"data_root": "data",
"output_dir": "experiments",
"model": "allenai/unifiedqa-t5-base",
"options": [
"A",
"B",
"C",
"D",
"E"
],
"epoch": 20,
"lr": 5e-05,
"bs": 8,
"input_len": 512,
"output_len": 512,
"eval_bs": 4,
"eval_acc": 10,
"train_split": "train",
"val_split": "val",
"test_split": "test",
"use_generate": false,
"final_eval": true,
"user_msg": "rationale",
"img_type": "detr",
"eval_le": null,
"test_le": null,
"evaluate_dir": null,
"caption_file": "data/captions.json",
"use_caption": false,
"prompt_format": "QCM-LE",
"seed": 42
}
Traceback (most recent call last):
File "main.py", line 374, in
problems, qids, name_maps, image_features = load_data_img(args) # probelms, test question ids, shot example ids
File "/root/mm-cot/utils_data.py", line 39, in load_data_img
name_maps = json.load(open('vision_features/name_map.json'))
FileNotFoundError: [Errno 2] No such file or directory: 'vision_features/name_map.json'

@gcl916
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gcl916 commented Feb 20, 2023

this json file come from the "vison_features" dataset which link "readme" shown.

@adnanmig
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Download the extracted vision features from vision_features and unzip the files under vision_features

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