model = train(prob, prob_v, pa...
prob = check_data(y, Z, net_co...
rng(seed);
addpath(genpath('./cnn'), genp...param = parameter(Z, options);
cnn_train (Calls: 1, Time: 2206.167 s)
Generated 19-Jun-2021 04:39:07 using performance time.
function in file /nfs/inm_phd/07/d07944009/2021/0618-proj6/simpleNN/MATLAB/cnn_train.m
Copy to new window for comparing multiple runs
| Function Name | Function Type | Calls |
| example | function | 1 |
| Line Number | Code | Calls | Total Time | % Time | Time Plot |
| 34 | model = train(prob, prob_v, pa... | 1 | 2204.893 s | 99.9% | |
| 27 | prob = check_data(y, Z, net_co... | 1 | 0.952 s | 0.0% | |
| 18 | rng(seed); | 1 | 0.189 s | 0.0% | |
| 23 | addpath(genpath('./cnn'), genp... | 1 | 0.084 s | 0.0% | |
| 25 | param = parameter(Z, options); | 1 | 0.041 s | 0.0% | |
| All other lines | 0.007 s | 0.0% | | ||
| Totals | 2206.167 s | 100% |
| Function Name | Function Type | Calls | Total Time | % Time | Time Plot |
| train | function | 1 | 2204.827 s | 99.9% | |
| check_data | function | 1 | 0.947 s | 0.0% | |
| rng | function | 1 | 0.173 s | 0.0% | |
| addpath | function | 1 | 0.077 s | 0.0% | |
| cnn_train>parameter | subfunction | 1 | 0.040 s | 0.0% | |
| genpath | function | 2 | 0.007 s | 0.0% | |
| read_config | function | 1 | 0.007 s | 0.0% | |
| Self time (built-ins, overhead, etc.) | 0.089 s | 0.0% | | ||
| Totals | 2206.167 s | 100% |
| Line number | Message |
| 8 | RAND or RANDN with the 'seed', 'state', or 'twister' inputs is not recommended. Use RNG instead. |
| 9 | RAND or RANDN with the 'seed', 'state', or 'twister' inputs is not recommended. Use RNG instead. |
| 15 | RAND or RANDN with the 'seed', 'state', or 'twister' inputs is not recommended. Use RNG instead. |
| 16 | RAND or RANDN with the 'seed', 'state', or 'twister' inputs is not recommended. Use RNG instead. |
| Total lines in function | 34 |
| Non-code lines (comments, blank lines) | 5 |
| Code lines (lines that can run) | 29 |
| Code lines that did run | 15 |
| Code lines that did not run | 14 |
| Coverage (did run/can run) | 51.72 % |
time | Calls | line | |
|---|---|---|---|
1 | function model = cnn_train(y, Z, y_v, Z_v, config_file, options, seed) | ||
2 | |||
< 0.001 | 1 | 3 | if nargin == 5 || nargin == 6 |
4 | if nargin == 5 | ||
5 | options = ''; | ||
6 | end | ||
7 | if exist('OCTAVE_VERSION', 'builtin') | ||
8 | rand('state'); | ||
9 | randn('state'); | ||
10 | else | ||
11 | rng('shuffle'); | ||
12 | end | ||
< 0.001 | 1 | 13 | elseif nargin == 7 |
< 0.001 | 1 | 14 | if exist('OCTAVE_VERSION', 'builtin') |
15 | rand('state', seed); | ||
16 | randn('state', seed); | ||
< 0.001 | 1 | 17 | else |
0.189 | 1 | 18 | rng(seed); |
< 0.001 | 1 | 19 | end |
20 | else | ||
21 | error('The #arguments is incorrect.'); | ||
< 0.001 | 1 | 22 | end |
0.084 | 1 | 23 | addpath(genpath('./cnn'), genpath('./opt')); |
24 | |||
0.041 | 1 | 25 | param = parameter(Z, options); |
0.007 | 1 | 26 | net_config = read_config(config_file); |
0.952 | 1 | 27 | prob = check_data(y, Z, net_config); |
28 | % check if the vaildation data exists | ||
< 0.001 | 1 | 29 | prob_v = struct; |
< 0.001 | 1 | 30 | if ~isempty(y_v) && ~isempty(Z_v) |
31 | prob_v = check_data(y_v, Z_v, net_config); | ||
< 0.001 | 1 | 32 | end |
33 | |||
2204.893 | 1 | 34 | model = train(prob, prob_v, param, net_config); |
Other subfunctions in this file are not included in this listing.