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)