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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 |
Hi,
Small doubt You had initialized hidden_layers but didn't Used it.
Can you please Help me where to use it
@mikkokotila How do i use this with the keras image data generator?
Hey, what about the x_val, y_val here?
What happens if you don't pass x_val and y_val (Like in this example),
does it split it automatically?
Thanks
I think the call ta.datasets.iris()
changed to ta.templates.datasets.iris()
and should be updated.
Updated the script to work as of today. @mikkokotila, please pull or modify accordingly - thanks!
https://gist.github.com/ronammar/a62fe679ef156135faf5b171c39cd47e
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.
That's right, there was an error in the code. It's now fixed. Both the input and output dimensions were wrong.