Reputation: 1284
Say you create your own custom word embeddings in the process of some arbitrary task, say text classification. How do you get a dictionary like structure of {word: vector}
back from Keras?
embeddings_layer.get_weights()
gives you the raw embeddings...but it's unclear which word corresponds to what vector element.
Upvotes: 1
Views: 307
Reputation: 6387
This dictionary is not a part of keras model. It should be kept separately as a normal python dictionary. It should be in your code - you use it to convert text to integer indices (to feed them to Embedding layer).
Upvotes: 1