Params: -- activation: num_samples x dim_feat Returns: -- mu: dim_feat -- sigma: dim_feat x dim_feat
(activations)
| 58 | |
| 59 | |
| 60 | def calculate_activation_statistics(activations): |
| 61 | """ |
| 62 | Params: |
| 63 | -- activation: num_samples x dim_feat |
| 64 | Returns: |
| 65 | -- mu: dim_feat |
| 66 | -- sigma: dim_feat x dim_feat |
| 67 | """ |
| 68 | mu = np.mean(activations, axis=0) |
| 69 | cov = np.cov(activations, rowvar=False) |
| 70 | return mu, cov |
| 71 | |
| 72 | |
| 73 | def calculate_diversity(activation, diversity_times): |