Comments (5)
and another question is :
in "/VL-BERT/data/conceptual-captions/ReatMe.txt" introduction, where is the Specific directory location of sub project bottom-up-attention ?
the directory location is in "/VL-BERT/data/conceptual-captions/bottom-up-attention" or in root directory "/VL-BERT/bottom-up-attention"
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@campper You should use same cuda version in pytorch installation and apex compiling. The error message shows that you install pytorch binary compiled by cuda9.0 but you use cuda10.2 to compile apex.
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And the bottom-up-attention is just for pre-processing pre-training data, it doesn't matter what location you put it into.
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thx.
is the cuda tookit 9.0 suppored ubuntu 18.04? I follow the "CUDA Toolkit 9.0 Downloads" online document, the "CUDA Toolkit 9.0" supported version are 17.04 and 16.04. Is it works in 18.04?
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I don't know whether cuda9.0 is compatible with ubuntu18.04 since I worked on ubuntu16.04. But you can use cuda10.0 and also install pytorch binary compiled by cuda10.0, like following:
conda install pytorch=1.1.0 cudatoolkit=10.0 -c pytorch
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Related Issues (20)
- The problem of multitasking parallel processing HOT 4
- ./scripts/init.sh HOT 4
- fine-tune HOT 1
- visualize attention for custom images
- CUDA Illegal Memory Access In FastRCNN with ROIAlign
- what is text_visual_embeddings
- How to pretrain on my own data? HOT 2
- An example for image feature HOT 3
- Does the pre-trained BERT come from vl-bert ? HOT 1
- Why the preprocessing method differs from the official method of pytorch
- Is there an option to upload the the val_frcnn features?
- Caffe feature extraction for conceptual-captions - where do I make pycaffe?
- Pretrained VL-BERT model on bert_based_multilingual_uncased needed to apply zero shot learning for German language
- CUDA error: no kernel image is available for execution on the device
- Can I get the object label ?
- Improper RefCOCO evaluation
- How to freeze the Fast RCNN?
- Is the nvcc necessary?
- google drive
- script for downloading GCC images
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