NASLib is a Neural Architecture Search (NAS) library for facilitating NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces and optimizers.
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Why does the zero-cost predictor not integrate with model search space module #129
In file NASLib/tree/Develop/naslib/predictors/zerocost_v1.py, it use the search space defined in NASLib/tree/Develop/naslib/predictors/utils/models. It basically defines some architectures of nasbench101 and nasbench201.
However, there is already a module called search_space. including many search spaces, and they are well-structured,
Why the zerocost_v1 don't use the model defined in search_space?
In file
NASLib/tree/Develop/naslib/predictors/zerocost_v1.py, it use the search space defined inNASLib/tree/Develop/naslib/predictors/utils/models. It basically defines some architectures of nasbench101 and nasbench201.However, there is already a module called
search_space.including many search spaces, and they are well-structured, Why thezerocost_v1don't use the model defined insearch_space?