Mercurial > ift6266

annotate deep/convolutional_dae/salah_exp/utils.py @ 618:14ba0120baff

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review response changes
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Sun, 09 Jan 2011 14:13:23 -0500
parents 31641a84e0ae
children
rev   line source
358
31641a84e0ae Initial commit for the experimental setup of the denoising convolutional network
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1 #!/usr/bin/python
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2 # coding: utf-8
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3
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4 from __future__ import with_statement
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5
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6 from jobman import DD
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7
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8 # from pylearn codebase
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9 # useful in __init__(param1, param2, etc.) to save
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10 # values in self.param1, self.param2... just call
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11 # update_locals(self, locals())
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12 def update_locals(obj, dct):
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13 if 'self' in dct:
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14 del dct['self']
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15 obj.__dict__.update(dct)
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16
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17 # from a dictionary of possible values for hyperparameters, e.g.
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18 # hp_values = {'learning_rate':[0.1, 0.01], 'num_layers': [1,2]}
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19 # create a list of other dictionaries representing all the possible
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20 # combinations, thus in this example creating:
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21 # [{'learning_rate': 0.1, 'num_layers': 1}, ...]
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22 # (similarly for combinations (0.1, 2), (0.01, 1), (0.01, 2))
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23 def produit_cartesien_jobs(val_dict):
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24 job_list = [DD()]
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25 all_keys = val_dict.keys()
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26
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27 for key in all_keys:
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28 possible_values = val_dict[key]
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29 new_job_list = []
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30 for val in possible_values:
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31 for job in job_list:
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32 to_insert = job.copy()
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33 to_insert.update({key: val})
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34 new_job_list.append(to_insert)
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35 job_list = new_job_list
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36
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37 return job_list
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38
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39 def test_produit_cartesien_jobs():
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40 vals = {'a': [1,2], 'b': [3,4,5]}
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41 print produit_cartesien_jobs(vals)
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42
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43
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44 # taken from http://stackoverflow.com/questions/276052/how-to-get-current-cpu-and-ram-usage-in-python
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45 """Simple module for getting amount of memory used by a specified user's
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46 processes on a UNIX system.
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47 It uses UNIX ps utility to get the memory usage for a specified username and
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48 pipe it to awk for summing up per application memory usage and return the total.
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49 Python's Popen() from subprocess module is used for spawning ps and awk.
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50
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51 """
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52
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53 import subprocess
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54
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55 class MemoryMonitor(object):
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56
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57 def __init__(self, username):
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58 """Create new MemoryMonitor instance."""
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59 self.username = username
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60
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61 def usage(self):
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62 """Return int containing memory used by user's processes."""
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63 self.process = subprocess.Popen("ps -u %s -o rss | awk '{sum+=$1} END {print sum}'" % self.username,
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64 shell=True,
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65 stdout=subprocess.PIPE,
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66 )
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67 self.stdout_list = self.process.communicate()[0].split('\n')
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68 return int(self.stdout_list[0])
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69