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@mikkokotila
Last active November 21, 2020 12:19
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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': ['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
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mikkokotila commented Sep 25, 2019

What happens if you don't pass x_val and y_val (Like in this example)

You have to pass it.

How do i use this with the keras image data generator?

Have a look at the generator example in the docs.

@blu3r4y @ronammar @dileep3004 thanks for the corrections. It's now updated to the latest API.

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