You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: initialize_weights.m
    path of file: ./repos/deeplearningsourceseparation/codes
    
    the code of the file until where you have to start completion: function [ stack, W_t ] = initialize_weights( eI )
% Copyright (c) 2014-present University of Illinois at Urbana-Champaign
% All rights reserved.

    
function [ stack, W_t ] = initialize_weights( eI )
% Copyright (c) 2014-present University of Illinois at Urbana-Champaign
% All rights reserved.
% 		
% Developed by:     Po-Sen Huang, Paris Smaragdis
%                   Department of Electrical and Computer Engineering
%                   Department of Computer Science
%
%INITIALIZE_WEIGHTS Random weight structures for a network architecture
%   eI describes an RNN via the fields layerSizes, inputDim and
%   temporalLayer
%
%   This uses Xavier's weight initialization tricks for better backprop
%   See: X. Glorot, Y. Bengio. Understanding the difficulty of training
%        deep feedforward neural networks. AISTATS 2010.

%% initialize hidden layers
stack = cell(1, numel(eI.layerSizes));
for l = 1 : numel(eI.layerSizes)
    if l > 1
        prevSize = eI.layerSizes(l-1);
    else
        prevSize = eI.inputDim;
    end