How to run multiple experiments in one go with Nkululeko

Sometimes you will want to run several experiments without the need to manually start them one after the other, e.g. if you want to run them over night.
This post shows you one way how to do this.
The necessary Python files are part of the Nkululeko distribution.

You need three files:

The value parser

First i created a Python file that accepts nkululeko ini file values as targets, called parse_nkulu.py:

# imports
import sys
sys.path.append("../src")
import constants
import numpy as np
import experiment as exp
import configparser
from util import Util
import argparse
import os.path

def main():

# use the argparse package to parse arguments:
    parser = argparse.ArgumentParser(description='Call the nkululeko framework.')
    parser.add_argument('--data', help='The databases', nargs='*', \
        action='append')
    parser.add_argument('--label', nargs='*', help='The labels for the target', \
        action='append')
    parser.add_argument('--tuning_params', nargs='*', help='parameters to be tuned', \
        action='append')
    parser.add_argument('--model', default='xgb', help='The model type', required=True)
    parser.add_argument('--feat', default='os', help='The model type')
    parser.add_argument('--set', help='The opensmile set')
    parser.add_argument('--with_os', help='To add os features')
    parser.add_argument('--target', help='The target designation')

    args = parser.parse_args()

# Use a prepared config file with values that are stable across experiments:
    config_file = './exp.ini'
    util = Util()
    # test if config is there
    if not os.path.isfile(config_file):
        util.error(f'no such file {config_file}')

    config = configparser.ConfigParser()
    config.read(config_file)

# fill the config file
    if args.data is not None:
        databases = []
        for t in args.data:
            databases.append(t[0])
        print(f'got databases: {databases}')
        config['DATA']['databases'] = str(databases)
    if args.label is not None:
        labels = []
        for l in args.label:
            labels.append(l[0])
        print(f'got labels: {labels}')
        config['DATA']['labels'] = str(labels)
    if args.tuning_params is not None:
        tuning_params = []
        for tp in args.tuning_params:
            tuning_params.append(tp[0])
        config['MODEL']['tuning_params'] = str(tuning_params)
    if args.target is not None:
        config['DATA']['target'] = args.target
    if args.model is not None:
        config['MODEL']['type'] = args.model
    if args.feat is not None:
        config['FEATS']['type'] = args.feat
    if args.with_os is not None:
        config['FEATS']['with_os'] = args.with_os
    if args.set is not None:
        config['FEATS']['set'] = args.set
    name = config['EXP']['name']
    util = Util()
    util.debug(f'running {name}, Nkululeko version {constants.VERSION}')

# Now run the experiment
    # init the experiment
    expr = exp.Experiment(config)
    # load the data
    expr.load_datasets()
    # split into train and test
    expr.fill_train_and_tests()
    # extract features
    expr.extract_feats()
    # initialize a run manager
    expr.init_runmanager()
    # run the experiment
    reports = expr.run()
    result = reports[-1].result.test
    # report result
    util.debug(f'result for {expr.get_name()} is {result}')

if __name__ == "__main__":
    main()

The configuration file

A Nkululeko config file with the constant values for all experiments (to be adapted to your needs and pathes)

[EXP]
root = ./
name = exp
runs = 1
epochs = 1
[DATA]
root_folders = ../data_roots.ini
databases = ['mydata']
target = mytarget
labels = ['label1', 'label2']
[FEATS]
wav2vec.model = xxx/wav2vec2-large-robust-ft-swbd-300h
xbow.model = xxx/openXBOW/
trill.model = xxx/trill_model
mld.model = xxx/mld/src
scale = standard
[MODEL]
C_val = .001
loso = True

The script to specify and run all experiments

Lastly, you need a script to start and specify the experiments, here's an example that combines tweo classifiers and eight feature sets:

import os

classifiers = [
    {'--model': 'xgb'},
    {'--model': 'svm'},
]

features = [
    {'--feat': 'os'},
    {'--feat': 'os', 
    '--set': 'ComParE_2016',
    },
    {'--feat': 'mld'},
    {'--feat': 'mld',
    '--with_os': 'True',
    },
    {'--feat': 'xbow'},
    {'--feat': 'xbow',
    '--with_os': 'True',
    },
    {'--feat': 'trill'},
    {'--feat': 'wav2vec'},
]

for c in classifiers:
    for f in features:
        cmd = f'python parse_nkulu.py '
        for item in c:
            cmd += f'{item} {c[item]} '
        for item in f:
            cmd += f'{item} {f[item]} '
        print(cmd)
        os.system(cmd)

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