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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': ['binary_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 = ta.Scan(x, y, model=iris_model, params=p, experiment_name='iris', fraction_limit=0.1) | |
return scan_object |
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