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comparison deep/crbm/utils.py @ 339:ffbf0e41bcee

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Aded code to run experiment on cluster, separate configuration from other machinery. Not tested yet.
author fsavard
date Sat, 17 Apr 2010 20:29:18 -0400
parents
children 82dae7c46046
comparison
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338:fca22114bb23 339:ffbf0e41bcee
1 #!/usr/bin/python
2 # coding: utf-8
3
4 from __future__ import with_statement
5
6 from jobman import DD
7
8 from pylearn.io.seriestables import *
9 import tables
10
11
12
13 # from pylearn codebase
14 # useful in __init__(param1, param2, etc.) to save
15 # values in self.param1, self.param2... just call
16 # update_locals(self, locals())
17 def update_locals(obj, dct):
18 if 'self' in dct:
19 del dct['self']
20 obj.__dict__.update(dct)
21
22 # from a dictionary of possible values for hyperparameters, e.g.
23 # hp_values = {'learning_rate':[0.1, 0.01], 'num_layers': [1,2]}
24 # create a list of other dictionaries representing all the possible
25 # combinations, thus in this example creating:
26 # [{'learning_rate': 0.1, 'num_layers': 1}, ...]
27 # (similarly for combinations (0.1, 2), (0.01, 1), (0.01, 2))
28 def produit_cartesien_jobs(val_dict):
29 job_list = [DD()]
30 all_keys = val_dict.keys()
31
32 for key in all_keys:
33 possible_values = val_dict[key]
34 new_job_list = []
35 for val in possible_values:
36 for job in job_list:
37 to_insert = job.copy()
38 to_insert.update({key: val})
39 new_job_list.append(to_insert)
40 job_list = new_job_list
41
42 return job_list
43
44 def jobs_from_reinsert_list(cols, job_vals):
45 job_list = []
46 for vals in job_vals:
47 job = DD()
48 for i, col in enumerate(cols):
49 job[col] = vals[i]
50 job_list.append(job)
51
52 return job_list
53
54 def save_params(all_params, filename):
55 import pickle
56 with open(filename, 'wb') as f:
57 values = [p.value for p in all_params]
58
59 # -1 for HIGHEST_PROTOCOL
60 pickle.dump(values, f, -1)
61
62 # Perform insertion into the Postgre DB based on combination
63 # of hyperparameter values above
64 # (see comment for produit_cartesien_jobs() to know how it works)
65 def jobman_insert_job_vals(job_db, experiment_path, job_vals):
66 jobs = produit_cartesien_jobs(job_vals)
67
68 db = jobman.sql.db(job_db)
69 for job in jobs:
70 job.update({jobman.sql.EXPERIMENT: experiment_path})
71 jobman.sql.insert_dict(job, db)
72
73 def jobman_insert_specific_jobs(job_db, experiment_path,
74 insert_cols, insert_vals):
75 jobs = jobs_from_reinsert_list(insert_cols, insert_vals)
76
77 db = jobman.sql.db(job_db)
78 for job in jobs:
79 job.update({jobman.sql.EXPERIMENT: experiment_path})
80 jobman.sql.insert_dict(job, db)
81
82 # Just a shortcut for a common case where we need a few
83 # related Error (float) series
84 def get_accumulator_series_array( \
85 hdf5_file, group_name, series_names,
86 reduce_every,
87 index_names=('epoch','minibatch'),
88 stdout_too=True,
89 skip_hdf5_append=False):
90 all_series = []
91
92 new_group = hdf5_file.createGroup('/', group_name)
93
94 other_targets = []
95 if stdout_too:
96 other_targets = [StdoutAppendTarget()]
97
98 for sn in series_names:
99 series_base = \
100 ErrorSeries(error_name=sn,
101 table_name=sn,
102 hdf5_file=hdf5_file,
103 hdf5_group=new_group._v_pathname,
104 index_names=index_names,
105 other_targets=other_targets,
106 skip_hdf5_append=skip_hdf5_append)
107
108 all_series.append( \
109 AccumulatorSeriesWrapper( \
110 base_series=series_base,
111 reduce_every=reduce_every))
112
113 ret_wrapper = SeriesArrayWrapper(all_series)
114
115 return ret_wrapper
116
117