def test_wrong_metric(self):
with pytest.raises(ValueError):
compute_metrics.evaluate(metric='wrong_metric',
log_dir=self.log_dir,
netG=self.netG,
dataset_name=self.dataset_name,
evaluate_step=self.evaluate_step,
device=self.device)
def test_arguments(self):
for metric in ['fid', 'kid', 'inception_score']:
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset_name=self.dataset_name,
evaluate_step=self.evaluate_step,
device=self.device)
def test_evaluate_is(self):
kwargs = {
'metric': 'inception_score',
'log_dir': self.log_dir,
'netG': self.netG,
'num_samples': 10,
'num_runs': 3,
'evaluate_step': self.evaluate_step,
'device': self.device,
'start_seed': self.start_seed,
}
scores = compute_metrics.evaluate(**kwargs)[self.evaluate_step]
assert type(scores) == list
assert all(map(lambda x: type(x) == float, scores))
def test_evaluate_kid(self):
kwargs = {
'metric': 'kid',
'log_dir': self.log_dir,
'evaluate_step': self.evaluate_step,
'num_subsets': 10,
'subset_size': 10,
'netG': self.netG,
'device': self.device,
'start_seed': self.start_seed,
'dataset_name': self.dataset_name
}
scores = compute_metrics.evaluate(**kwargs)[self.evaluate_step]
assert type(scores) == list
assert all(map(lambda x: type(x) == float, scores))
def test_evaluate_fid(self):
kwargs = {
'metric': 'fid',
'log_dir': self.log_dir,
'netG': self.netG,
'dataset': self.dataset,
'num_real_samples': 10,
'num_fake_samples': 10,
'evaluate_step': self.evaluate_step,
'start_seed': self.start_seed,
'device': self.device
}
scores = compute_metrics.evaluate(**kwargs)[self.evaluate_step]
assert type(scores) == list
assert all(map(lambda x: type(x) == float, scores))
def test_arguments(self):
for metric in ['fid', 'kid', 'inception_score']:
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset=self.dataset,
evaluate_step=self.evaluate_step,
device=self.device)
# Both evaluate step and evaluate range defined
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset=self.dataset,
evaluate_range=(1000, 100000, 1000),
evaluate_step=self.evaluate_step,
device=self.device)
# Faulty evaluate range
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset=self.dataset,
evaluate_range=(1000),
device=self.device)
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset=self.dataset,
evaluate_range=('a', 'b', 'c'),
device=self.device)
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset=self.dataset,
evaluate_range=(100, 100, 100, 100),
device=self.device)
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir=self.log_dir,
netG=self.netG,
dataset=self.dataset,
evaluate_range=None,
device=self.device)
# Invalid ckpt dir
with pytest.raises(ValueError):
compute_metrics.evaluate(metric=metric,
log_dir='does_not_exist',
netG=self.netG,
dataset=self.dataset,
evaluate_step=self.evaluate_step,
device=self.device)
