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: train_TSP_demo_mini_clip.m
    path of file: ./repos/deeplearningsourceseparation/codes/TSP
    
    the code of the file until where you have to start completion: function train_TSP_demo_mini_clip(context_win, hidden_units, num_layers, isdropout, isRNN, iscleanonly,...
    circular_step , isinputL1, MFCCorlogMelorSpectrum, framerate, pos_neg_r, outputnonlinear, opt, act, ...
    train_mode, const, const2, isGPU, batchsize, MaxIter, bfgs_iter, clip, lambda,...
    data_mode)
% 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
%
%%
rand('state',0)
randn('state',0)
%%
%% setup paths for code. assumed this script runs in its own directory
baseDir= '../../';
codeDir = [baseDir,'codes', filesep];
minFuncDir = [baseDir, 'tools', filesep, 'minFunc_2012', filesep];

saveDir = [codeDir,filesep,'TSP',...
           filesep,'discrim_joint_offset_all_results'];

addpath([baseDir, filesep,'tools', filesep,'labrosa']);
addpath([baseDir, filesep,'tools', filesep,'bss_eval']);

addpath(baseDir);
addpath(genpath(minFuncDir));
addpath([baseDir,filesep,'codes',filesep,'TSP', filesep,'Data']);

    
function train_TSP_demo_mini_clip(context_win, hidden_units, num_layers, isdropout, isRNN, iscleanonly,...
    circular_step , isinputL1, MFCCorlogMelorSpectrum, framerate, pos_neg_r, outputnonlinear, opt, act, ...
    train_mode, const, const2, isGPU, batchsize, MaxIter, bfgs_iter, clip, lambda,...
    data_mode)
% 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
%
%%
rand('state',0)
randn('state',0)
%%
%% setup paths for code. assumed this script runs in its own directory
baseDir= '../../';
codeDir = [baseDir,'codes', filesep];
minFuncDir = [baseDir, 'tools', filesep, 'minFunc_2012', filesep];

saveDir = [codeDir,filesep,'TSP',...
           filesep,'discrim_joint_offset_all_results'];

addpath([baseDir, filesep,'tools', filesep,'labrosa']);
addpath([baseDir, filesep,'tools', filesep,'bss_eval']);

addpath(baseDir);
addpath(genpath(minFuncDir));
addpath([baseDir,filesep,'codes',filesep,'TSP', filesep,'Data']);
addpath(codeDir);
addpath([codeDir,'TSP']);

CFGPath=[baseDir,'tools',filesep,'htk_features', filesep];
addpath(CFGPath);

%% setup network architecture
eI = [];
% 0- mfcc, 1- logmel, 2- spectrum
eI.MFCCorlogMelorSpectrum=MFCCorlogMelorSpectrum; 
eI.CFGPath=CFGPath;
eI.seqLen = [1 10 25 50 100];
eI.DataPath = [baseDir,filesep,'codes',filesep,'TSP', filesep,'Data'];
% eI.seqLen = [1];

eI.framerate=framerate;
if eI.framerate==64
    eI.winsize = 1024;    eI.nFFT = 1024;    eI.hop =eI.winsize/2;    eI.scf=1;%scf = 2/3;
else %32
    eI.winsize = 512;    eI.nFFT = 512;    eI.hop = eI.winsize/2;    eI.scf=1;%scf = 2/3;
end
winsize=eI.winsize; nFFT= eI.nFFT; hop= eI.hop; scf=eI.scf;
windows=sin(0:pi/winsize:pi-pi/winsize);

% single target or multiple targets
eI.cleanonly=iscleanonly;

% context window size of the input.
eI.num_contextwin = context_win;

% dimension of each input frame
if eI.MFCCorlogMelorSpectrum==0 %0 for mfcc 1 for logmel
    eI.featDim =39;
elseif eI.MFCCorlogMelorSpectrum==1 %0 for mfcc 1 for logmel
    eI.featDim =123;
else
    eI.featDim = (eI.nFFT/2+1);
end