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* add needed dependency * add extract_model_and_implement pipeline * add merge_file_to_model_dict_to_model_dict * implement `rdagent\app\model_implementation\eval.py` * Running benchmark * refine import --------- Co-authored-by: Young <afe.young@gmail.com>
1008 B
1008 B
Preparation
Install Pytorch
CPU CUDA will be enough for verify the implementation
Please install pytorch based on your system. Here is an example on my system
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
pip3 install torch_geometric
Tasks
Task Extraction
From paper to task.
# python rdagent/app/model_implementation/task_extraction.py
# It may based on rdagent/document_reader/document_reader.py
python rdagent/components/task_implementation/model_implementation/task_extraction.py ./PaperImpBench/raw_paper/
Complete workflow
From paper to implementation
# Similar to
# rdagent/app/factor_extraction_and_implementation/factor_extract_and_implement.py
Paper benchmark
# TODO: it does not work well now.
python rdagent/app/model_implementation/eval.py
TODO:
- Create reasonable benchmark
- with uniform input
- manually create task
- Create reasonable evaluation metrics