(activation, diversity_times)
| 71 | |
| 72 | |
| 73 | def calculate_diversity(activation, diversity_times): |
| 74 | assert len(activation.shape) == 2 |
| 75 | assert activation.shape[0] > diversity_times |
| 76 | num_samples = activation.shape[0] |
| 77 | |
| 78 | first_indices = np.random.choice(num_samples, diversity_times, replace=False) |
| 79 | second_indices = np.random.choice(num_samples, diversity_times, replace=False) |
| 80 | dist = linalg.norm(activation[first_indices] - activation[second_indices], axis=1) |
| 81 | return dist.mean() |
| 82 | |
| 83 | |
| 84 | def calculate_multimodality(activation, multimodality_times): |
no outgoing calls
no test coverage detected