com/tensorflow/tensorflow/issues/25846 ���� PR “����” “������������” https://github.com/tensorflow/tensorflow#contribution-guidelines ML GDE TensorFlow ��������� Google Developers Expert �� Google Developers Exp

child networks were smaller and more efficient than the human designed models. However, the key contribution of NASNet was the focus on predicting the components of child networks which enabled the construction

magnitude-based pruning, there are other heuristics for selecting the connections to prune based on their contribution to the loss / error. Similarly, it might be better to gradually increase the sparsity rate in