AttributeError: 'NoneType' object has no attribute 'size'
#4
by
Archeane
- opened
Hi all, getting the below error when using ragatouille to run the sample code
Process Process-3:
Traceback (most recent call last):
File "/home/jenny/.pyenv/versions/3.10.14/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
self.run()
File "/home/jenny/.pyenv/versions/3.10.14/lib/python3.10/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/home/jenny/Desktop/projects/sp-python/.venv/lib/python3.10/site-packages/colbert/infra/launcher.py", line 134, in setup_new_process
return_val = callee(config, *args)
File "/home/jenny/Desktop/projects/sp-python/.venv/lib/python3.10/site-packages/colbert/indexing/collection_indexer.py", line 33, in encode
encoder.run(shared_lists)
File "/home/jenny/Desktop/projects/sp-python/.venv/lib/python3.10/site-packages/colbert/indexing/collection_indexer.py", line 63, in run
self.setup() # Computes and saves plan for whole collection
File "/home/jenny/Desktop/projects/sp-python/.venv/lib/python3.10/site-packages/colbert/indexing/collection_indexer.py", line 101, in setup
avg_doclen_est = self._sample_embeddings(sampled_pids)
File "/home/jenny/Desktop/projects/sp-python/.venv/lib/python3.10/site-packages/colbert/indexing/collection_indexer.py", line 141, in _sample_embeddings
self.num_sample_embs = torch.tensor([local_sample_embs.size(0)]).cuda()
AttributeError: 'NoneType' object has no attribute 'size'
[Aug 17, 21:13:42] [1] #> Encoding 0 passages..
Have ran:
pip install --upgrade ragatouille
pip install --upgrade colbert-ai
Still ran into this issue, Here's code to repro
from ragatouille import RAGPretrainedModel
RAG = RAGPretrainedModel.from_pretrained("answerdotai/answerai-colbert-small-v1")
docs = ['Hayao Miyazaki is a Japanese director and is founded ghibli studio', 'Walt Disney is an American author, director and founder of disney']
RAG.index(docs, index_name="ghibli")
query = 'Who directed spirited away?'
results = RAG.search(query)
The reranker way works fine, but I need ragatouille so I can index the docs ahead of time. Appreciate some assistance!
Hey! This is a RAGatouille-related issue, so could you open an issue on the GitHub repo?
Could you also provide information in the issue, such as:
- Operating system
- Full output of
pip freeze
- Platform information (number/type of GPU, etc...)
bclavie
changed discussion status to
closed