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Fix assert for list of layers #2179

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Fix assert for list of layers #2179

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19 changes: 11 additions & 8 deletions tensorflow_addons/optimizers/discriminative_layer_training.py
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Original file line number Diff line number Diff line change
Expand Up @@ -88,8 +88,8 @@ def __init__(

if optimizer_specs is None and optimizers_and_layers is not None:
self.optimizer_specs = [
self.create_optimizer_spec(opt, layer)
for opt, layer in optimizers_and_layers
self.create_optimizer_spec(opt, layers)
for opt, layers in optimizers_and_layers
]

elif optimizer_specs is not None and optimizers_and_layers is None:
Expand Down Expand Up @@ -131,20 +131,23 @@ def get_config(self):
return config

@classmethod
def create_optimizer_spec(cls, optimizer_instance, layer):
def create_optimizer_spec(cls, optimizer_instance, layers):

assert isinstance(
optimizer_instance, tf.keras.optimizers.Optimizer
), "Object passed is not an instance of tf.keras.optimizers.Optimizer"

assert isinstance(layer, tf.keras.layers.Layer) or isinstance(
layer, tf.keras.Model
assert isinstance(layers, (tf.keras.layers.Layer, tf.keras.Model)) or (
isinstance(layers, list)
and all(isinstance(layer, tf.keras.layers.Layer) for layer in layers)
), "Object passed is not an instance of tf.keras.layers.Layer nor tf.keras.Model"

if type(layer) == list:
weights = [var.name for sublayer in layer for var in sublayer.weights]
if type(layers) == list:
weights = [
var.name for sublayer in layers for var in sublayer.trainable_weights
]
else:
weights = [var.name for var in layer.weights]
weights = [var.name for var in layers.trainable_weights]

return {
"optimizer": optimizer_instance,
Expand Down