diff deep/convolutional_dae/salah_exp/utils.py @ 358:31641a84e0ae

Initial commit for the experimental setup of the denoising convolutional network
author humel
date Thu, 22 Apr 2010 00:49:42 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/deep/convolutional_dae/salah_exp/utils.py	Thu Apr 22 00:49:42 2010 -0400
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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])
+