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
