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Code and data to support the paper "PAQ 65 Million Probably-Asked Questions andWhat You Can Do With Them"

License: Other

Python 99.40% Shell 0.60%

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lebon369 hubayirp ml-lab iaxat exr0n seopbo yuxiang-wu dixing0908 piegu hnt4499 dashstander kunlun-zhu pooruss wjdghks950 nowkim jyk13579

paq's Issues

Amazing work! When can we have pre-trained models

No module named 'src' in filter.py

There isn't a src directory, so failed to import modules in PAQ/paq/generation/filtering/filter.py:

import src.util
import src.data
import src.evaluation
import src.model

Just want to make sure I didn't overlook anything.

Amazing work! When can we have pre-trained models?

Can we have model checkpoints for machine comprehension models?

Could you please provide a guildline or code for finetunning RePAQ or query embedding's training code, thanks!

Hi there , I am a master student at Taiwan.
I have some ideas for improving the PAQ after reading your paper, btw it's amazing!
But got some trouble in training my own query embedding code.
it would be great if you could provide a guildline or code for finetunning RePAQ or the query embedding's training code.

By the way, have always been a big fan of you. Read a lot of your papers and even saw your video on huggingface YT.
Your papers has inspired me a lot. Thank you!

Generating `retriever` index for global filtering

Thank you for open-sourcing your code. This is very interesting work!

In order to run global filtering (generator_configs/filterer_configs/global_filtering_config.json), the "retriever" expects an "index_path" and "index_id_to_db_id_path", which I assume refer to the FAISS index over the passages in the corpus.

I see that the files expected by these 2 fields are available using the Resource Key Name models.filtering.dpr_nq_passage_retriever. However, is there code in the repo that generates these files as well?

Amazing work! When can we have pre-trained models? Thanks

How can I make list question-answering pair using 'PAQ'?

I wanna use list question-answering pair. Maybe.. is PAQ able to make these pair?

Typos in the readme

Hi team,
Thanks a lot for sharing the code and the pretrained models!
It looks like there is the same typo at two lines in the readme:
python -m paq.download -v -n models.rerankers.retriever_multi_xxlarge
--> python -m paq.download -v -n models.rerankers.reranker_multi_xxlarge

Runtime Error in Question Generation

Would appreciate some help in debugging the following error encountered whilst running the question generation component:

INFO:root:Loading ae.jsonl
INFO:root:ae.jsonl Loaded, splitting into lines...
INFO:root:Parsing 6892 items from jsonl:
INFO:root:Loaded 1 Items from ae.jsonl
INFO:root:Loaded 6892 Items from ae.jsonl
INFO:__main__:Running Question Generation...
 94%|█████████▍| 101/107 [02:47<00:09,  1.59s/it]
Token indices sequence length is longer than the specified maximum sequence length for this model (2583 > 1024). Running this sequence through the model will result in indexing errors
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/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [118,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [119,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [120,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [121,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [122,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [123,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [124,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [125,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [126,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1607370141920/work/aten/src/ATen/native/cuda/Indexing.cu:658: indexSelectLargeIndex: block: [119,0,0], thread: [127,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
 94%|█████████▍| 101/107 [02:47<00:09,  1.66s/it]
Traceback (most recent call last):
  File "/ext3/miniconda3/envs/paq/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/scratch/ss11404/capstone/PAQ/paq/generation/question_generator/generate_questions.py", line 50, in <module>
    generate_questions_and_write_to_file(config, args.passage_answer_pairs_to_generate_from, args.output_path, args.verbose)
  File "/scratch/ss11404/capstone/PAQ/paq/generation/question_generator/generate_questions.py", line 25, in generate_questions_and_write_to_file
    annotations = generate_questions(config, input_path, verbose)
  File "/scratch/ss11404/capstone/PAQ/paq/generation/question_generator/generate_questions.py", line 20, in generate_questions
    annotations = question_generator.generate_questions_from_passage_answer_pairs(passage_answer_pairs, disable_tqdm=not verbose)
  File "/scratch/ss11404/capstone/PAQ/paq/generation/question_generator/generator.py", line 148, in generate_questions_from_passage_answer_pairs
    batch_questions, batch_scores = self.generate_question(list(batch_inputs))
  File "/scratch/ss11404/capstone/PAQ/paq/generation/question_generator/generator.py", line 120, in generate_question
    **self.kwargs
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/transformers/pipelines.py", line 2644, in __call__
    **generate_kwargs,
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
    return func(*args, **kwargs)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/transformers/generation_utils.py", line 503, in generate
    model_kwargs = self._prepare_encoder_decoder_kwargs_for_generation(input_ids, model_kwargs)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/transformers/generation_utils.py", line 86, in _prepare_encoder_decoder_kwargs_for_generation
    model_kwargs["encoder_outputs"]: ModelOutput = encoder(input_ids, return_dict=True, **encoder_kwargs)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/transformers/models/bart/modeling_bart.py", line 775, in forward
    hidden_states, attn = encoder_layer(hidden_states, attention_mask, output_attentions=output_attentions)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/transformers/models/bart/modeling_bart.py", line 357, in forward
    hidden_states=hidden_states, attention_mask=attention_mask, output_attentions=output_attentions
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/ext3/miniconda3/envs/paq/lib/python3.7/site-packages/transformers/models/bart/modeling_bart.py", line 291, in forward
    attn_weights = attn_weights.view(bsz, self.num_heads, tgt_len, src_len) + attention_mask
RuntimeError: CUDA error: device-side assert triggered

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