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retrieve_from_faiss_by_prompt
fails with pyarrow error
#14
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Thanks for the report @vpvsankar. Two questions to help us narrow this down:
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I didn't make any changes to the pipeline. I am using GPU for runnig the pipeline |
And using the local runner @vpvsankar? |
I submitted a fix to fondant at ml6team/fondant#904. You can already test it by installing the commit and using the
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Still getting some error
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I am using Vertex AI workbench. |
It looks like your machine might be too small. @mrchtr can you provide the minimum spec needed to run the component? |
That would be great, so that I can create a large machine |
Hi @vpvsankar, I revisited the components and the pipeline. Due to this behavior, your instance has used the CPU instead. Depending on the size of your machine, too little memory was assigned to a single dask worker. The current faiss index and clip model need approximately 7Gb of RAM. I've updated the component code as well, to avoid running into this when executing the component on a CPU. |
I used n1-highmem-16 machine with T4 GPU. Currently I have 6.39 GB per worker, is there a way to restrict the number of workers? Do I need to update the fondant package?
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Sorry for the back and forth. Now, a different component is failing in the pipeline due to resource limitation. I was able to reproduce your issue. The other components of the pipeline didn't use the GPU. I've updated the component code in #905. I've also enabled GPU usage in the #15. With the latest state you shouldn't run into any issues anymore when you are using a GPU. |
@mrchtr thank you for your support. I am getting this error in segment_images module.
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@vpvsankar I've taken another look into it. It seems that one of your partitions is empty. It should look like this:
By using the machine configuration you have mentioned ( |
Seems to be we have missed to enable the GPU usage in the notebook and the pipeline itself. Set the option accordingly. fix #14
Originally posted by @vpvsankar in #10 (comment)
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