def main_exp(params):
"""Set up and run one random experiment.
Arguments:
params -- dictionary of parameters for experiment
Returns:
None
Side effects:
Changes params dict
If doesn't already exist, creates folder params['folder_name']
Saves files in that folder
"""
helperfns.set_defaults(params)
if not os.path.exists(params['folder_name']):
os.makedirs(params['folder_name'])
tf.set_random_seed(params['seed'])
np.random.seed(params['seed'])
# data is num_steps x num_examples x n but load flattened version (matrix instead of tensor)
data_val = np.loadtxt(('./data/%s_val_x.csv' % (params['data_name'])),
delimiter=',',
dtype=np.float64)
try_net(data_val, params)
def main_exp(params):
helperfns.set_defaults(params)
if not os.path.exists(params['folder_name']):
os.makedirs(params['folder_name'])
# data is num_steps x num_examples x n
data_val = np.genfromtxt(('./data/%s_val_x.csv' % (params['data_name'])),
delimiter=',')
try_net(data_val, params)
tf.reset_default_graph()
def main_exp(params):
"""Set up and run one random experiment.
Arguments:
params -- dictionary of parameters for experiment
Returns:
None
Side effects:
Changes params dict
If doesn't already exist, creates folder params['folder_name']
Saves files in that folder
"""
helperfns.set_defaults(params)
if not os.path.exists(params['folder_name']):
os.makedirs(params['folder_name'])
tf.compat.v1.set_random_seed(params['seed'])
np.random.seed(params['seed'])
try_net(params)