| import torch | |
| import numpy as np | |
| torch.set_printoptions(precision=6) | |
| times = 6 | |
| def mean_relative_error(y_true, y_pred): | |
| eps = 1e-5 | |
| relative_error = np.average(np.abs(y_true - y_pred) / (y_true + eps), axis=0) | |
| return relative_error | |
| import torch | |
| import numpy as np | |
| torch.set_printoptions(precision=6) | |
| times = 6 | |
| def mean_relative_error(y_true, y_pred): | |
| eps = 1e-5 | |
| relative_error = np.average(np.abs(y_true - y_pred) / (y_true + eps), axis=0) | |
| return relative_error | |