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comparison deep/crbm/utils.py @ 360:f37c0705649d

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Problèmes de révisions hg... tentative de merger
author fsavard
date Thu, 22 Apr 2010 10:34:26 -0400
parents
children 64fa85d68923
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359:969ad25e78cc 360:f37c0705649d
1 #!/usr/bin/python
2 # coding: utf-8
3
4 from __future__ import with_statement
5
6 import jobman
7 from jobman import DD
8
9 from pylearn.io.seriestables import *
10 import tables
11
12
13
14 # from pylearn codebase
15 # useful in __init__(param1, param2, etc.) to save
16 # values in self.param1, self.param2... just call
17 # update_locals(self, locals())
18 def update_locals(obj, dct):
19 if 'self' in dct:
20 del dct['self']
21 obj.__dict__.update(dct)
22
23 # from a dictionary of possible values for hyperparameters, e.g.
24 # hp_values = {'learning_rate':[0.1, 0.01], 'num_layers': [1,2]}
25 # create a list of other dictionaries representing all the possible
26 # combinations, thus in this example creating:
27 # [{'learning_rate': 0.1, 'num_layers': 1}, ...]
28 # (similarly for combinations (0.1, 2), (0.01, 1), (0.01, 2))
29 def produit_cartesien_jobs(val_dict):
30 job_list = [DD()]
31 all_keys = val_dict.keys()
32
33 for key in all_keys:
34 possible_values = val_dict[key]
35 new_job_list = []
36 for val in possible_values:
37 for job in job_list:
38 to_insert = job.copy()
39 to_insert.update({key: val})
40 new_job_list.append(to_insert)
41 job_list = new_job_list
42
43 return job_list
44
45 def jobs_from_reinsert_list(cols, job_vals):
46 job_list = []
47 for vals in job_vals:
48 job = DD()
49 for i, col in enumerate(cols):
50 job[col] = vals[i]
51 job_list.append(job)
52
53 return job_list
54
55 def save_params(all_params, filename):
56 import pickle
57 with open(filename, 'wb') as f:
58 values = [p.value for p in all_params]
59
60 # -1 for HIGHEST_PROTOCOL
61 pickle.dump(values, f, -1)
62
63 # Perform insertion into the Postgre DB based on combination
64 # of hyperparameter values above
65 # (see comment for produit_cartesien_jobs() to know how it works)
66 def jobman_insert_job_vals(job_db, experiment_path, job_vals):
67 jobs = produit_cartesien_jobs(job_vals)
68
69 db = jobman.sql.db(job_db)
70 for job in jobs:
71 job.update({jobman.sql.EXPERIMENT: experiment_path})
72 jobman.sql.insert_dict(job, db)
73
74 def jobman_insert_specific_jobs(job_db, experiment_path,
75 insert_cols, insert_vals):
76 jobs = jobs_from_reinsert_list(insert_cols, insert_vals)
77
78 db = jobman.sql.db(job_db)
79 for job in jobs:
80 job.update({jobman.sql.EXPERIMENT: experiment_path})
81 jobman.sql.insert_dict(job, db)
82
83 # Just a shortcut for a common case where we need a few
84 # related Error (float) series
85 def get_accumulator_series_array( \
86 hdf5_file, group_name, series_names,
87 reduce_every,
88 index_names=('epoch','minibatch'),
89 stdout_too=True,
90 skip_hdf5_append=False):
91 all_series = []
92
93 new_group = hdf5_file.createGroup('/', group_name)
94
95 other_targets = []
96 if stdout_too:
97 other_targets = [StdoutAppendTarget()]
98
99 for sn in series_names:
100 series_base = \
101 ErrorSeries(error_name=sn,
102 table_name=sn,
103 hdf5_file=hdf5_file,
104 hdf5_group=new_group._v_pathname,
105 index_names=index_names,
106 other_targets=other_targets,
107 skip_hdf5_append=skip_hdf5_append)
108
109 all_series.append( \
110 AccumulatorSeriesWrapper( \
111 base_series=series_base,
112 reduce_every=reduce_every))
113
114 ret_wrapper = SeriesArrayWrapper(all_series)
115
116 return ret_wrapper
117
118