view deep/stacked_dae/utils.py @ 190:70a9df1cd20e

initial commit for autoencoder training
author youssouf
date Tue, 02 Mar 2010 09:52:27 -0500
parents 1f5937e9e530
children 3632e6258642
line wrap: on
line source

#!/usr/bin/python

from jobman import DD

# from pylearn codebase
def update_locals(obj, dct):
    if 'self' in dct:
        del dct['self']
    obj.__dict__.update(dct)

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