def build(self, input_shape):
freeze_layers = self.params.get("freeze_layers")
if freeze_layers:
if not isinstance(freeze_layers, list):
freeze_layers = [freeze_layers]
for layer_path in freeze_layers:
layer = misc.index_structure(self, layer_path)
layer.trainable = False
misc.set_dropout(layer, 0) # Disable dropout in frozen layers.
self.examples_inputter.build(input_shape)
self.built = True
def initialize(self, data_config, params=None):
"""Initializes the model from the data configuration.
Args:
data_config: A dictionary containing the data configuration set
by the user (e.g. vocabularies, tokenization, pretrained embeddings,
etc.).
params: A dictionary of hyperparameters.
"""
if params is None:
params = {}
self.params.update(params)
dropout = self.params.get("dropout")
if dropout is not None:
misc.set_dropout(self, dropout)
self.examples_inputter.initialize(data_config)
def testSetDropout(self):
class Layer(tf.keras.layers.Layer):
def __init__(self):
super().__init__()
self.dropout = 0.3
self.x = tf.keras.layers.Dropout(0.2)
class Model(tf.keras.layers.Layer):
def __init__(self):
super().__init__()
self.output_dropout = 0.1
self.layer = Layer()
self.layers = [Layer(), Layer()]
model = Model()
misc.set_dropout(model, 0.5)
self.assertEqual(model.output_dropout, 0.5)
self.assertEqual(model.layer.dropout, 0.5)
self.assertEqual(model.layer.x.rate, 0.5)
self.assertEqual(model.layers[1].dropout, 0.5)
self.assertEqual(model.layers[1].x.rate, 0.5)
