Mercurial > ift6266
view deep/crbm/utils.py @ 599:587674030c5a
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author | boulanni <nicolas_boulanger@hotmail.com> |
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date | Fri, 15 Oct 2010 14:14:06 -0400 |
parents | 64fa85d68923 |
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#!/usr/bin/python # coding: utf-8 from __future__ import with_statement import jobman from jobman import DD from pylearn.io.seriestables import * import tables # 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 jobs_from_reinsert_list(cols, job_vals): job_list = [] for vals in job_vals: job = DD() for i, col in enumerate(cols): job[col] = vals[i] job_list.append(job) return job_list def save_params(all_params, filename): import pickle with open(filename, 'wb') as f: values = [p.value for p in all_params] # -1 for HIGHEST_PROTOCOL pickle.dump(values, f, -1) # Perform insertion into the Postgre DB based on combination # of hyperparameter values above # (see comment for produit_cartesien_jobs() to know how it works) def jobman_insert_job_vals(job_db, experiment_path, job_vals): jobs = produit_cartesien_jobs(job_vals) db = jobman.sql.db(job_db) for job in jobs: job.update({jobman.sql.EXPERIMENT: experiment_path}) jobman.sql.insert_dict(job, db) def jobman_insert_specific_jobs(job_db, experiment_path, insert_cols, insert_vals): jobs = jobs_from_reinsert_list(insert_cols, insert_vals) db = jobman.sql.db(job_db) for job in jobs: job.update({jobman.sql.EXPERIMENT: experiment_path}) jobman.sql.insert_dict(job, db) # Just a shortcut for a common case where we need a few # related Error (float) series def get_accumulator_series_array( \ hdf5_file, group_name, series_names, reduce_every, index_names=('epoch','minibatch'), stdout_too=True, skip_hdf5_append=False): all_series = [] new_group = hdf5_file.createGroup('/', group_name) other_targets = [] if stdout_too: other_targets = [StdoutAppendTarget()] for sn in series_names: series_base = \ ErrorSeries(error_name=sn, table_name=sn, hdf5_file=hdf5_file, hdf5_group=new_group._v_pathname, index_names=index_names, other_targets=other_targets, skip_hdf5_append=skip_hdf5_append) all_series.append( \ AccumulatorSeriesWrapper( \ base_series=series_base, reduce_every=reduce_every)) ret_wrapper = SeriesArrayWrapper(all_series) return ret_wrapper