minimal_talos_example.py

import talos from keras.models import Sequential from keras.layers import Dense

def minimal():

x, y = talos.templates.datasets.iris()

p = {'activation':['relu', 'elu'],
     'optimizer': ['Nadam', 'Adam'],
     'losses': ['categorical_crossentropy'],
     'batch_size': [20,30,40],
     'epochs': [10,20]}

def iris_model(x_train, y_train, x_val, y_val, params):

    model = Sequential()
    model.add(Dense(32, input_dim=4, activation=params['activation']))
    model.add(Dense(3, activation='softmax'))
    model.compile(optimizer=params['optimizer'], loss=params['losses'])

    out = model.fit(x_train, y_train,
                     batch_size=params['batch_size'],
                     epochs=params['epochs'],
                     validation_data=(x_val, y_val),
                     verbose=0)

    return out, model

scan_object = talos.Scan(x, y, model=iris_model, params=p, experiment_name='iris', fraction_limit=0.1)

return scan_object