Keras rename model and layers
Question:
1) I try to rename a model and the layers in Keras with TF backend, since I am using multiple models in one script.
Class Model seem to have the property model.name, but when changing it I get “AttributeError: can’t set attribute”.
What is the Problem here?
2) Additionally, I am using sequential API and I want to give a name to layers, which seems to be possibile with Functional API, but I found no solution for sequential API. Does anonye know how to do it for sequential API?
UPDATE TO 2): Naming the layers works, although it seems to be not documented. Just add the argument name, e.g. model.add(Dense(…,…,name=”hiddenLayer1″). Watch out, Layers with same name share weights!
Answers:
Doesn’t work any more as per tf2+
Your first problem about the model name is not reproducible on my machine.
I can set it like this. many a times these errors are caused by software versions.
model=Sequential()
model.add(Dense(2,input_shape=(....)))
model.name="NAME"
As far as naming the layers, you can do it in Sequential model like this
model=Sequential()
model.add(Dense(2,input_shape=(...),name="NAME"))
Latest solution
use _name
for 1), I think you may build another model with right name and same structure with the exist one. then set weights from layers of the exist model to layers of the new model.
The Answer from user239457 only works with Standard keras.
If you want to use the Tensorflow Keras, you can do it like this:
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
model = Sequential(name='Name')
model.add(Dense(2,input_shape=(5, 1)))
Just to cover all the options, regarding the title of the question, if you are using the Keras functional API you can define the model and the layers name by:
inputs = Input(shape=(value, value))
output_layer = Dense(2, activation = 'softmax', name = 'training_output')(dropout_new_training_layer)
model = Model(inputs= inputs, outputs=output_layer, name="my_model")
For changing names of model.layers with tf.keras you can use the following lines:
for layer in model.layers:
layer._name = layer.name + str("_2")
I needed this in a two-input model case and ran into the “AttributeError: can’t set attribute”, too. The thing is that there is an underlying hidden attribute _name, which causes the conflict.
Detailed answer is here How to rename Pre-Trained model ? ValueError 'Trained Model' is not a valid scope name
We can use model.name = "Model_Name" when are developing model and making it ready to train. We can also give name to layers. Ex:
model = Sequential()
model.name = "My_Model" #Naming model
model.add(Dense(2,input_shape=(...),name="Name") #Naming layer
To rename a keras model in TF2.2.0:
model._name = "newname"
I have no idea if this is a bad idea – they don’t seem to want you to do it, but it does work. To confirm, call model.summary() and you should see the new name.
To change only one layer name in a model you can use the following lines:
my_model.layers[0]._name = 'my_new_name_for_the_first_layer'
my_model.layers[1]._name = 'my_new_name_for_the_second_layer'
my_model.layers[-1]._name = 'my_new_name_for_the_last_layer'
In order to change the layer name of a pre-trained model on Tensorflow Keras, the solution is a bit more complex. A simple
layer.name = "new_name" or layer._name = "new_name" as proposed by other answers will not work.
This blog post offers a solution that works for that case.
1) I try to rename a model and the layers in Keras with TF backend, since I am using multiple models in one script.
Class Model seem to have the property model.name, but when changing it I get “AttributeError: can’t set attribute”.
What is the Problem here?
2) Additionally, I am using sequential API and I want to give a name to layers, which seems to be possibile with Functional API, but I found no solution for sequential API. Does anonye know how to do it for sequential API?
UPDATE TO 2): Naming the layers works, although it seems to be not documented. Just add the argument name, e.g. model.add(Dense(…,…,name=”hiddenLayer1″). Watch out, Layers with same name share weights!
Doesn’t work any more as per tf2+
Your first problem about the model name is not reproducible on my machine.
I can set it like this. many a times these errors are caused by software versions.
model=Sequential()
model.add(Dense(2,input_shape=(....)))
model.name="NAME"
As far as naming the layers, you can do it in Sequential model like this
model=Sequential()
model.add(Dense(2,input_shape=(...),name="NAME"))
Latest solution
use _name
for 1), I think you may build another model with right name and same structure with the exist one. then set weights from layers of the exist model to layers of the new model.
The Answer from user239457 only works with Standard keras.
If you want to use the Tensorflow Keras, you can do it like this:
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
model = Sequential(name='Name')
model.add(Dense(2,input_shape=(5, 1)))
Just to cover all the options, regarding the title of the question, if you are using the Keras functional API you can define the model and the layers name by:
inputs = Input(shape=(value, value))
output_layer = Dense(2, activation = 'softmax', name = 'training_output')(dropout_new_training_layer)
model = Model(inputs= inputs, outputs=output_layer, name="my_model")
For changing names of model.layers with tf.keras you can use the following lines:
for layer in model.layers:
layer._name = layer.name + str("_2")
I needed this in a two-input model case and ran into the “AttributeError: can’t set attribute”, too. The thing is that there is an underlying hidden attribute _name, which causes the conflict.
Detailed answer is here How to rename Pre-Trained model ? ValueError 'Trained Model' is not a valid scope name
We can use model.name = "Model_Name" when are developing model and making it ready to train. We can also give name to layers. Ex:
model = Sequential()
model.name = "My_Model" #Naming model
model.add(Dense(2,input_shape=(...),name="Name") #Naming layer
To rename a keras model in TF2.2.0:
model._name = "newname"
I have no idea if this is a bad idea – they don’t seem to want you to do it, but it does work. To confirm, call model.summary() and you should see the new name.
To change only one layer name in a model you can use the following lines:
my_model.layers[0]._name = 'my_new_name_for_the_first_layer'
my_model.layers[1]._name = 'my_new_name_for_the_second_layer'
my_model.layers[-1]._name = 'my_new_name_for_the_last_layer'
In order to change the layer name of a pre-trained model on Tensorflow Keras, the solution is a bit more complex. A simple
layer.name = "new_name" or layer._name = "new_name" as proposed by other answers will not work.
This blog post offers a solution that works for that case.