Its a common occurrence for various neural network architectures in NLP and problems in the vision language to relate the weights of the source interstitial layer to the output type softmax. Usually this leads to an increase in the quality of the generation of offers. (see example here )
It is typical for Keras to embed word embedding layers using the Embedding class, however, there seems to be no easy way to associate the weights of this layer with the output softmax. Will anyone know how this can be implemented?
As you can read here , you should just set the flag trainableto False. For instance.
trainable
False
aux_output = Embedding(..., trainable=False)(input) .... output = Dense(nb_of_classes, .. ,activation='softmax', trainable=False)
Source: https://habr.com/ru/post/1688680/More articles:Using parent component template in Angular2 - angularSocket.io how to list sockets in a room by nickname - javascriptHow to authenticate one application using another application when both applications use the same backend server - angularShift all zeros in a 2d matrix - javaExport multiple images using plugin - javascriptgetByName configuration does not work in gradle when publishing POM file in Artifactory - androidDecreasing the number of arguments in a function in Python? - functionRecursive wildcards in Firestore security rules not working properly - firebase#temp_table vs user. # temp_table sybase_iq - sqlDrop bot to human using BotFramework (NodeJS) - node.jsAll Articles