def test_accuracy(ddp, ddp_sync_on_step, preds, target, sk_metric):
compute_batch(preds,
target,
Accuracy,
sk_metric,
ddp_sync_on_step,
ddp,
metric_args={"threshold": threshold})
def test_explained_variance(ddp, dist_sync_on_step, multioutput, preds, target,
sk_metric):
compute_batch(
preds,
target,
ExplainedVariance,
partial(sk_metric,
sk_fn=partial(explained_variance_score,
multioutput=multioutput)),
dist_sync_on_step,
ddp,
metric_args=dict(multioutput=multioutput),
)
def test_precision_recall(ddp, dist_sync_on_step, preds, target, sk_metric,
metric_class, sk_fn, num_classes, multilabel,
average):
compute_batch(
preds,
target,
metric_class,
partial(sk_metric, sk_fn=sk_fn, average=average),
dist_sync_on_step,
ddp,
metric_args={
"num_classes": num_classes,
"average": average,
"multilabel": multilabel,
"threshold": THRESHOLD
},
check_dist_sync_on_step=False if average == 'macro' else True,
check_batch=False if average == 'macro' else True,
)
def test_fbeta(ddp, dist_sync_on_step, preds, target, sk_metric, metric_class,
beta, num_classes, multilabel, average):
compute_batch(
preds,
target,
metric_class,
partial(sk_metric, average=average, beta=beta),
dist_sync_on_step,
ddp,
metric_args={
"beta": beta,
"num_classes": num_classes,
"average": average,
"multilabel": multilabel,
"threshold": THRESHOLD
},
check_dist_sync_on_step=False,
check_batch=False,
)
def test_explained_variance(ddp, ddp_sync_on_step, preds, target, sk_metric):
compute_batch(preds, target, ExplainedVariance, sk_metric,
ddp_sync_on_step, ddp)
def test_mean_error(ddp, dist_sync_on_step, preds, target, sk_metric,
metric_class, sk_fn):
compute_batch(preds, target, metric_class, partial(sk_metric, sk_fn=sk_fn),
dist_sync_on_step, ddp)