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# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
from omegaconf import OmegaConf
from utils.io import write_json
def compute_recall(errors):
num_elements = len(errors)
sort_idx = np.argsort(errors)
errors = np.array(errors.copy())[sort_idx]
recall = (np.arange(num_elements) + 1) / num_elements
recall = np.r_[0, recall]
errors = np.r_[0, errors]
return errors, recall
def compute_auc(errors, recall, thresholds):
aucs = []
for t in thresholds:
last_index = np.searchsorted(errors, t, side="right")
r = np.r_[recall[:last_index], recall[last_index - 1]]
e = np.r_[errors[:last_index], t]
auc = np.trapz(r, x=e) / t
aucs.append(auc * 100)
return aucs
def write_dump(output_dir, experiment, cfg, results, metrics):
dump = {
"experiment": experiment,
"cfg": OmegaConf.to_container(cfg),
"results": results,
"errors": {},
}
for k, m in metrics.items():
if hasattr(m, "get_errors"):
dump["errors"][k] = m.get_errors().numpy()
write_json(output_dir / "log.json", dump)
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