如何用多个输入训练 Keras model？

Question

I want to train a Keras model with multiple inputs. I want to use the first input for training the model, but the second and the third inputs are variables which must be used during the training of the first input. I could not use the tf.Variable for using the second and the third inputs which are fixed during the training because it showed the error: You must feed a placeholder . So, I want to feed them using tf.keras . I changed the shape of the second and the third inputs to be similar to the first one. Then, I concatenate them using:

inputs = tf.keras.layers.concatenate([data, masks_rep, ind_rep], axis=2)

Then, for retrieving them in the model, I wrote:

Inputs_t = tf.keras.Input(shape=(max_length, 3*charset_length))
x, m_k_expand, ind_k_expand = tf.split(Inputs_t, num_or_size_splits=3,  axis=1)

But it changes the dimensions of the layers from charset_length to 3*charset_length . How can I solve this problem?

Answer 1

We can use the subclasses to use additional variables by using tf.Variable . tf.Variable easily leads bugs when it is used with tf.keras.layers . But using subclasses prevents bugs. More examples are provided here: enter link description here