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annotate deep/crbm/utils.py @ 342:b25ad1670ff7

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Slight bug
author fsavard
date Sun, 18 Apr 2010 11:47:35 -0400
parents ffbf0e41bcee
children 82dae7c46046
rev   line source
339
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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.io.seriestables import *
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9 import tables
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10
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11
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12
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13 # from pylearn codebase
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14 # useful in __init__(param1, param2, etc.) to save
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15 # values in self.param1, self.param2... just call
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16 # update_locals(self, locals())
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17 def update_locals(obj, dct):
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18 if 'self' in dct:
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19 del dct['self']
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20 obj.__dict__.update(dct)
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21
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22 # from a dictionary of possible values for hyperparameters, e.g.
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23 # hp_values = {'learning_rate':[0.1, 0.01], 'num_layers': [1,2]}
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24 # create a list of other dictionaries representing all the possible
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25 # combinations, thus in this example creating:
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26 # [{'learning_rate': 0.1, 'num_layers': 1}, ...]
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27 # (similarly for combinations (0.1, 2), (0.01, 1), (0.01, 2))
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28 def produit_cartesien_jobs(val_dict):
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29 job_list = [DD()]
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30 all_keys = val_dict.keys()
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31
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32 for key in all_keys:
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33 possible_values = val_dict[key]
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34 new_job_list = []
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35 for val in possible_values:
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36 for job in job_list:
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37 to_insert = job.copy()
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38 to_insert.update({key: val})
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39 new_job_list.append(to_insert)
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40 job_list = new_job_list
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41
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42 return job_list
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43
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44 def jobs_from_reinsert_list(cols, job_vals):
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45 job_list = []
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46 for vals in job_vals:
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47 job = DD()
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48 for i, col in enumerate(cols):
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49 job[col] = vals[i]
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50 job_list.append(job)
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51
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52 return job_list
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53
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54 def save_params(all_params, filename):
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55 import pickle
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56 with open(filename, 'wb') as f:
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57 values = [p.value for p in all_params]
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58
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59 # -1 for HIGHEST_PROTOCOL
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60 pickle.dump(values, f, -1)
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61
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62 # Perform insertion into the Postgre DB based on combination
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63 # of hyperparameter values above
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64 # (see comment for produit_cartesien_jobs() to know how it works)
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65 def jobman_insert_job_vals(job_db, experiment_path, job_vals):
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66 jobs = produit_cartesien_jobs(job_vals)
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67
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68 db = jobman.sql.db(job_db)
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69 for job in jobs:
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70 job.update({jobman.sql.EXPERIMENT: experiment_path})
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71 jobman.sql.insert_dict(job, db)
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72
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73 def jobman_insert_specific_jobs(job_db, experiment_path,
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74 insert_cols, insert_vals):
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75 jobs = jobs_from_reinsert_list(insert_cols, insert_vals)
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76
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77 db = jobman.sql.db(job_db)
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78 for job in jobs:
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79 job.update({jobman.sql.EXPERIMENT: experiment_path})
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80 jobman.sql.insert_dict(job, db)
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81
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82 # Just a shortcut for a common case where we need a few
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83 # related Error (float) series
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84 def get_accumulator_series_array( \
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85 hdf5_file, group_name, series_names,
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86 reduce_every,
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87 index_names=('epoch','minibatch'),
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88 stdout_too=True,
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89 skip_hdf5_append=False):
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90 all_series = []
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91
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92 new_group = hdf5_file.createGroup('/', group_name)
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93
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94 other_targets = []
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95 if stdout_too:
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96 other_targets = [StdoutAppendTarget()]
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97
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98 for sn in series_names:
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99 series_base = \
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100 ErrorSeries(error_name=sn,
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101 table_name=sn,
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102 hdf5_file=hdf5_file,
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103 hdf5_group=new_group._v_pathname,
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104 index_names=index_names,
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105 other_targets=other_targets,
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106 skip_hdf5_append=skip_hdf5_append)
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107
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108 all_series.append( \
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109 AccumulatorSeriesWrapper( \
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110 base_series=series_base,
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111 reduce_every=reduce_every))
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112
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113 ret_wrapper = SeriesArrayWrapper(all_series)
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114
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115 return ret_wrapper
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116
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117