# --- get settings --- # # parse command line arguments, or use defaults parser = utils.rgan_options_parser() settings = vars(parser.parse_args()) # if a settings file is specified, it overrides command line arguments/defaults if settings['settings_file']: settings = utils.load_settings_from_file(settings) if TIMEGAN: settings['hidden_units_g'] = 4 * 5 settings['hidden_units_d'] = 4 * 5 # --- get data, split --- # samples, pdf, labels = data_utils.get_samples_and_labels(settings, STOCK_FLAG) # --- save settings, data --- # print('Ready to run with settings:') for (k, v) in settings.items(): print(v, '\t', k) # add the settings to local environment # WARNING: at this point a lot of variables appear locals().update(settings) json.dump(settings, open('./experiments/settings/' + identifier + '.txt', 'w'), indent=0) if not data == 'load': data_path = './experiments/data/' + identifier + '.data.npy' np.save(data_path, {'samples': samples, 'pdf': pdf, 'labels': labels}) print('Saved training data to', data_path)
import data_utils import plotting import model import utils from time import time from math import floor from mmd import rbf_mmd2, median_pairwise_distance, mix_rbf_mmd2_and_ratio tf.logging.set_verbosity(tf.logging.ERROR) with tf.device('/gpu:0'): identifier = 'mnistfull' settings = utils.load_settings_from_file(identifier) samples, pdf, labels = data_utils.get_samples_and_labels(settings) locals().update(settings) # json.dump(settings, open('./experiments/settings/' + identifier + '.txt', 'w'), indent=0) data_path = './experiments/data/' + identifier + '.data.npy' np.save(data_path, {'samples': samples, 'pdf': pdf, 'labels': labels}) print('Saved training data to', data_path) # --- build model --- # Z, X, CG, CD, CS = model.create_placeholders(batch_size, seq_length, latent_dim, num_signals, cond_dim) discriminator_vars = [
from math import floor from mmd import rbf_mmd2, median_pairwise_distance, mix_rbf_mmd2_and_ratio tf.logging.set_verbosity(tf.logging.ERROR) # --- get settings --- # # parse command line arguments, or use defaults parser = utils.rgan_options_parser() settings = vars(parser.parse_args()) # if a settings file is specified, it overrides command line arguments/defaults if settings['settings_file']: settings = utils.load_settings_from_file(settings) # --- get data, split --- # if not settings['data'] == "load": samples_new, cond_data, pdf, labels = data_utils.get_samples_and_labels( settings) samples = {} if cond_data is not None: cond_samples = {} samples['train'] = np.expand_dims(samples_new['train'][:, :, 0], -1) cond_samples['train'] = np.expand_dims(samples_new['train'][:, :, 1], -1) samples['vali'] = np.expand_dims(samples_new['vali'][:, :, 0], -1) cond_samples['vali'] = np.expand_dims(samples_new['vali'][:, :, 1], -1) samples['test'] = np.expand_dims(samples_new['test'][:, :, 0], -1) cond_samples['test'] = np.expand_dims(samples_new['test'][:, :, 1], -1) cond_samples_train = cond_samples['train'] else: cond_samples_train = None samples = samples_new