# --- 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
