def test_amdim(tmpdir):
reset_seed()
model = AMDIM(data_dir=tmpdir,
batch_size=2,
online_ft=True,
encoder='resnet18')
trainer = pl.Trainer(fast_dev_run=True,
max_epochs=1,
default_root_dir=tmpdir)
trainer.fit(model)
loss = trainer.callback_metrics['loss']
assert loss > 0
def test_amdim(tmpdir):
reset_seed()
model = AMDIM(data_dir=tmpdir,
batch_size=2,
online_ft=True,
encoder='resnet18')
trainer = pl.Trainer(fast_dev_run=True,
max_epochs=1,
default_root_dir=tmpdir)
trainer.fit(model)
loss = trainer.progress_bar_dict['loss']
assert float(loss) > 0
def test_amdim(tmpdir, datadir):
model = AMDIM(data_dir=datadir, batch_size=2, online_ft=True, encoder='resnet18', num_workers=0)
trainer = pl.Trainer(fast_dev_run=True, default_root_dir=tmpdir)
trainer.fit(model)
