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@ronammar
Forked from mikkokotila/minimal_talos_example.py
Last active August 28, 2019 17:46
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import talos as ta
from keras.models import Sequential
from keras.layers import Dense
def minimal():
x, y = ta.templates.datasets.iris()
p = {'activation':['relu', 'elu'],
'optimizer': ['Nadam', 'Adam'],
'losses': ['logcosh'],
'hidden_layers':[0, 1, 2],
'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, params=p, model=iris_model, experiment_name="minimal_iris", fraction_limit=0.1)
return scan_object
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