def net_cls_2d(self): from skorch.toy import make_regressor return make_regressor( input_units=2, num_hidden=0, output_units=1, )
def net_cls(self): """very simple network that trains for 10 epochs""" from skorch import NeuralNetRegressor from skorch.toy import make_regressor module_cls = make_regressor( input_units=1, num_hidden=0, output_units=1, ) return partial(NeuralNetRegressor, module=module_cls, max_epochs=10, batch_size=10)
def multioutput_module_cls(self): from skorch.toy import make_regressor return make_regressor(output_units=3, dropout=0.5)
def module_cls(self): from skorch.toy import make_regressor return make_regressor(dropout=0.5)
def test_make_regressor(self): from skorch.toy import make_regressor module = make_regressor()() assert module.sequential[-1].out_features == 1