I wouldn't the discount the performance impact on real world benchmarks for these functions. Just to name a couple of examples:
* 7x speed up of np.exp and np.log results in a 2x speed up of training neural networks like logistic regression [1]. I would expect np.tanh will show similar results for neural networks. * Vectorizing even simple functions like np.maximum results in a 1.3x speed up of sklearn's Kmeans algorithm [2] Raghuveer [1] https://github.com/numpy/numpy/pull/13134 [2] https://github.com/numpy/numpy/pull/14867
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