uta-smile / TCL

code for TCL: Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022

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No module named 'refTools'

PeterDykas opened this issue · comments

Hi I am trying to reproduce the results from inside a docker container. After installing the dependencies I hit the following error:

  File "Pretrain.py", line 30, in <module>
    from dataset import create_dataset, create_sampler, create_loader
  File "/workspace/dataset/__init__.py", line 6, in <module>
    from dataset.caption_dataset import re_train_dataset, re_eval_dataset, pretrain_dataset
  File "/workspace/dataset/caption_dataset.py", line 12, in <module>
    from dataset.utils import pre_caption
  File "/workspace/dataset/utils.py", line 45, in <module>
    from refTools.evaluation.refEvaluation import RefEvaluation
ModuleNotFoundError: No module named 'refTools'

every time when running:

python -m torch.distributed.launch --nproc_per_node=8 \ --use_env Pretrain.py \ --config ./configs/Pretrain.yaml \ --output_dir output/pretrain

I have tried pip3 install reftools but it does not solve the issue. Have you run into this issue before?

commented

Hi, thanks for your interest of our work. Let me double check this issue on my machine, will let you know ASAP.

commented

Hi, please download refTools , then unzip it, then put it under your TCL folder. Please let me know if you might need any further information.

That seems to have fixed the issue thank you. If I want to run on only a subset of the pretraining data is commenting out unused datasets in the config sufficient?

commented

Yes, just modify train_file in Pretrain.yaml.

Awesome thanks, I see that you listed MSCOCO 2014 as a dataset but I am going to assume it means the MSCOCO 2015 where the captioning competition was.

commented

Please only download MSCOCO 2014 datasets from these links.
2014 Train images [83K/13GB]
2014 Val images [41K/6GB]
2014 Test images [41K/6GB]