Mercurial > ift6266
view deep/convolutional_dae/salah_exp/utils.py @ 647:47af8a002530 tip
changed Theano to ift6266 and remove numpy as we do not use code from numpy in this repository
author | Razvan Pascanu <r.pascanu@gmail.com> |
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date | Wed, 17 Oct 2012 09:26:14 -0400 |
parents | 31641a84e0ae |
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])