def test_save_and_load_tasnet(fb):
model1 = LSTMTasNet(n_src=2, hid_size=4, n_layers=1, n_filters=32, dropout=0.0, fb_name=fb,)
test_input = torch.randn(1, 800)
model_conf = model1.serialize()
reconstructed_model = LSTMTasNet.from_pretrained(model_conf)
assert_allclose(model1(test_input), reconstructed_model(test_input))
def test_save_and_load_tasnet(fb):
_default_test_model(
LSTMTasNet(
n_src=2,
hid_size=4,
n_layers=1,
n_filters=32,
dropout=0.0,
fb_name=fb,
))