Comments (1)
I'm not sure why I didn't respond to this earlier, but in general deep-learning frameworks aren't super multi-processing friendly. They already batch parallelize much of the computation on the back-end, so there is very little reason to ever explicitly open multiple threads when doing deep learning.
For example, in your code, it would be much better to simply write:
attributions = explainer.attributions(x_test)
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Related Issues (12)
- output_indices not passed through for torch interactions HOT 2
- Can you help update a version with pytorch example? HOT 2
- cannot import name 'EmbeddingExplainerTF' HOT 8
- Mismatch num_samples for Torch and Tensorflow implementation IG HOT 7
- Extend torch interactions to higher dimensions HOT 3
- No convergence for IH for larger input strings HOT 2
- Whether the feature attribution method can be applied on training data?
- can't find bert_explainer
- Using Longformer
- .npy files
- EmbeddingExplainerTorch not available in pip package
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