view deep/stacked_dae/v_sylvain/utils.py @ 273:7800be7bce66

changes in ttf2jpg and pycaptcha to load a file list with cPickle (instead of doing a listdir()) in order to have always the same list order from different machine (to reproduce generation)
author Xavier Glorot <glorotxa@iro.umontreal.ca>
date Sun, 21 Mar 2010 16:45:48 -0400
parents 8a94a5c808cd
children
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#!/usr/bin/python
# coding: utf-8

from __future__ import with_statement

from jobman import DD

# from pylearn codebase
# useful in __init__(param1, param2, etc.) to save
# values in self.param1, self.param2... just call
# update_locals(self, locals())
def update_locals(obj, dct):
    if 'self' in dct:
        del dct['self']
    obj.__dict__.update(dct)

# from a dictionary of possible values for hyperparameters, e.g.
# hp_values = {'learning_rate':[0.1, 0.01], 'num_layers': [1,2]}
# create a list of other dictionaries representing all the possible
# combinations, thus in this example creating:
# [{'learning_rate': 0.1, 'num_layers': 1}, ...]
# (similarly for combinations (0.1, 2), (0.01, 1), (0.01, 2))
def produit_cartesien_jobs(val_dict):
    job_list = [DD()]
    all_keys = val_dict.keys()

    for key in all_keys:
        possible_values = val_dict[key]
        new_job_list = []
        for val in possible_values:
            for job in job_list:
                to_insert = job.copy()
                to_insert.update({key: val})
                new_job_list.append(to_insert)
        job_list = new_job_list

    return job_list

def test_produit_cartesien_jobs():
    vals = {'a': [1,2], 'b': [3,4,5]}
    print produit_cartesien_jobs(vals)


# taken from http://stackoverflow.com/questions/276052/how-to-get-current-cpu-and-ram-usage-in-python
"""Simple module for getting amount of memory used by a specified user's
processes on a UNIX system.
It uses UNIX ps utility to get the memory usage for a specified username and
pipe it to awk for summing up per application memory usage and return the total.
Python's Popen() from subprocess module is used for spawning ps and awk.

"""

import subprocess

class MemoryMonitor(object):

    def __init__(self, username):
        """Create new MemoryMonitor instance."""
        self.username = username

    def usage(self):
        """Return int containing memory used by user's processes."""
        self.process = subprocess.Popen("ps -u %s -o rss | awk '{sum+=$1} END {print sum}'" % self.username,
                                        shell=True,
                                        stdout=subprocess.PIPE,
                                        )
        self.stdout_list = self.process.communicate()[0].split('\n')
        return int(self.stdout_list[0])