from deephyper.problem import NaProblem
from deepspace.tabular import OneLayerFactory
def create_search_space(input_shape, output_shape, **kwargs):
return OneLayerFactory()(input_shape, output_shape, **kwargs)
Problem = NaProblem(seed=2019)
Problem.load_data(load_data)
Problem.search_space(create_search_space)
Problem.hyperparameters(batch_size=100,
learning_rate=0.1,
optimizer="adam",
num_epochs=1)
Problem.loss("mse")
Problem.metrics(["r2"])
Problem.objective("val_r2")
# Just to print your problem, to test its definition and imports in the current python environment.
if __name__ == "__main__":
print(Problem)
model = Problem.get_keras_model([4 for _ in range(20)])
from deephyper.benchmark.nas.linearReg.load_data import load_data
from deephyper.problem import NaProblem
from deepspace.tabular import OneLayerSpace
Problem = NaProblem()
Problem.load_data(load_data)
Problem.search_space(OneLayerSpace)
Problem.hyperparameters(batch_size=100, learning_rate=0.1, optimizer="adam", num_epochs=1)
Problem.loss("mse")
Problem.metrics(["r2"])
Problem.objective("val_r2")
# Just to print your problem, to test its definition and imports in the current python environment.
if __name__ == "__main__":
print(Problem)
model = Problem.get_keras_model([1])
