Layers in Polyaxon inherits from the
BaseLayer (which is
This property allows the layers to share the common behaviors.
All layers must defined there behavior in the
And they should take into account the current mode of the estimator. (
import polyaxon as plx layer = plx.layers.FullyConnected(mode=plx.Modes.TRAIN, n_units=64, activation='tanh')
Once the layer is created, it can be called as many time as needed with different inputs.
The layer itself knows how to validate the incoming values.
A layer can build other layers inside its
import tensorflow as tf import polyaxon as plx rnn_lstm = plx.layers.LSTM(plx.Modes.TRAIN, num_units=3, activation='tanh', inner_activation=tf.nn.sigmoid, dropout=0.3, num_layers=4)
Note that for activations, initializers, and regularizers you can use a string (should be one of the supported values), you can provide a function, or a tensor/value.