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Currently it is somewhat confusing how the parameters of DenseBlock can be used with Choice and the defaults are odd.
For layers it is hyperparameters.Choice("num_layers", [1, 2, 3], default=2), could there be linear sampling with more layers? If so then would this be turned into an Int sampling instead?
For units it is hyperparameters.Choice("num_units", [16, 32, 64, 128, 256, 512, 1024], default=32), this look exactly like logarithmic sampling with a step of 2. But would allowing units of sizes smaller than 16 or larger than 1024 be useful?
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Currently it is somewhat confusing how the parameters of
DenseBlock
can be used withChoice
and the defaults are odd.For layers it is
hyperparameters.Choice("num_layers", [1, 2, 3], default=2)
, could there be linear sampling with more layers? If so then would this be turned into anInt
sampling instead?For units it is
hyperparameters.Choice("num_units", [16, 32, 64, 128, 256, 512, 1024], default=32)
, this look exactly like logarithmic sampling with a step of 2. But would allowing units of sizes smaller than 16 or larger than 1024 be useful?Reference https://github.com/keras-team/autokeras/blob/master/autokeras/blocks/basic.py
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