Beispiel #1
0
# gan_model.train(result_dir, ckpt_dir, log_dir, training_iteration = 100005, G_update_num=5, D_update_num=1, Q_update_num=2)
# #gan_model.test()
# del gan_data
# del gan_model

#iteration test
result_dir = os.path.join('/home/artia/prj/results/megan_exp', 'test2', 'result')
ckpt_dir =  os.path.join('/home/artia/prj/results/megan_exp', 'test2', 'weight')
log_dir =  os.path.join('/home/artia/prj/results/megan_exp', 'test2', 'weight')
if not os.path.isdir(result_dir):
	os.makedirs(result_dir)
if not os.path.isdir(ckpt_dir):
	os.makedirs(ckpt_dir)
if not os.path.isdir(log_dir):
	os.makedirs(log_dir)
gan_data = data.Data(cat_dim, code_con_dim, total_con_dim, channel, path, name, split_name, batch_size)
gan_data.visual_prior_path = '/home/artia/prj/datasets/visual_prior_samples_multinumber'
gan_model = megan2_1.Megan(gan_data)
gan_model.train(result_dir, ckpt_dir, log_dir, training_iteration = 100005, G_update_num=5, D_update_num=1, Q_update_num=2)
#gan_model.test()
del gan_data
del gan_model


#iteration test
result_dir = os.path.join('/home/artia/prj/results/megan_exp', 'test3', 'result')
ckpt_dir =  os.path.join('/home/artia/prj/results/megan_exp', 'test3', 'weight')
log_dir =  os.path.join('/home/artia/prj/results/megan_exp', 'test3', 'weight')
if not os.path.isdir(result_dir):
	os.makedirs(result_dir)
if not os.path.isdir(ckpt_dir):
Beispiel #2
0
#!/usr/bin/env python
import os

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

import sys

import numpy as np

import model
from model import data
from model import helpers
from model import rnn

# load dataset
series = data.Data()
df = series.get_ili_data()
# configure

n_lag = 12
n_seq = 4
n_test = 10
n_epochs = 5
n_batch = 1
n_neurons = 1

n_decay = 0.1
n_dropout = 0.6

#neurons = [20, 50, 5, 1]
#shape = [seq_len, 3, 1] # window,feature, output