INNER CODE UNIT · Python
metric_scores
linzhiqiu/t2v_metrics · dataset.py:158
metric_scores = metric_scores.reshape(1, -1)
else:
# Group by item (last dim is number of system)
pass
# Calculate metric using KendallTau (including Pairwise Accuracy)
if variant == "pairwise_acc_with_tie_optimization":
import tau_optimization
result = tau_optimization.tau_optimization(metric_scores, gold_scores, tau_optimization.TauSufficientStats.acc_23, sample_rate=sample_rate)
return result.best_tau, result.best_threshold
elif variant == "pairwise_acc_ignore_tie":
import tau_optimization
result = tau_optimization.tau_optimization(metric_scores, gold_scores, tau_optimization.TauSufficientStats.acc_ignore_tie, sample_rate=sample_rate)
return result.taus[0], result.thresholds[0]
elif variant == 'tau_with_tie_optimization':
import tau_optimization
result = tau_optimization.tau_optimization(metric_scores, gold_scores, tau_optimization.TauSufficientStats.tau_23, sample_rate=sample_rate)
return result.best_tau, result.best_threshold