Exercise

# Link between the trained and inference model

Here you will be transferring the trained weights from the trained model to the inference model. In the encoder decoder model, there are three layers with parameters. They are,

- The encoder
`GRU`

layer - The decoder
`GRU`

layer - The decoder
`Dense`

layer

The other layers, such as `TimeDistributed`

do not have any parameters, thus don't require the copying of weights.

For this exercise, you have been provided with the trained encoder `GRU`

layer (`tr_en_gru`

), trained decoder `GRU`

(`tr_de_gru`

) and the trained `Dense`

layer (`tr_de_dense`

). You also have access to all the layers of the inference model (including the encoder) such as the encoder `GRU`

layer (`en_gru`

), decoder `GRU`

(`de_gru`

) and the `Dense`

layer (`de_dense`

).

Instructions

**100 XP**

- Load the weights of the trained encoder
`GRU`

layer. - Set the weights of the encoder
`GRU`

layer of the inference model. - Load the weights for the decoder
`GRU`

layer (trained) and set the weights in the inference model. - Load the weights of the decoder
`Dense`

layer (trained) and set the weights in the inference model.