##These functions allow us to delete layers from a model,
## Or if not possible, replace with an identity function,
## So that it has no trainable parameters/effect.
from torch import nn
import copy

def deleteEncodingLayers(model, num_layers_to_keep):  # must pass in the full bert model
    oldModuleList = model.bert.encoder.layer
    newModuleList = nn.ModuleList()

    # Now iterate over all layers, only keepign only the relevant layers.
    for i in range(0, num_layers_to_keep):
        newModuleList.append(oldModuleList[i])

    # create a copy of the model, modify it with the new list, and return
    copyOfModel = copy.deepcopy(model)
    copyOfModel.bert.encoder.layer = newModuleList

    return copyOfModel