import argparse
from tools.utils import *
import os
from tqdm import tqdm
from glob import glob
import time
import numpy as np
from net import generator
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"


def stats_graph(graph):
    flops = tf.profiler.profile(graph, options=tf.profiler.ProfileOptionBuilder.float_operation())
    # params = tf.profiler.profile(graph, options=tf.profiler.ProfileOptionBuilder.trainable_variables_parameter())
    print('FLOPs: {}'.format(flops.total_float_ops))

g_sess = None
test_generated = None
test_real = None

def test(checkpoint_dir, style_name, test_file, if_adjust_brightness, img_size=[256,256]):
    global g_sess
    global test_generated
    global test_real

    # tf.reset_default_graph()
    result_dir = 'results/'+style_name
    check_folder(result_dir)

    if g_sess is None:
        test_real = tf.placeholder(tf.float32, [1, None, None, 3], name='test')

        with tf.variable_scope("generator", reuse=False):
            test_generated = generator.G_net(test_real).fake
        saver = tf.train.Saver()

        gpu_options = tf.GPUOptions(allow_growth=True)
        g_sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True, gpu_options=gpu_options))

        # load model
        ckpt = tf.train.get_checkpoint_state(checkpoint_dir)  # checkpoint file information
        if ckpt and ckpt.model_checkpoint_path:
            ckpt_name = os.path.basename(ckpt.model_checkpoint_path)  # first line
            saver.restore(sess, os.path.join(checkpoint_dir, ckpt_name))
            print(" [*] Success to read {}".format(os.path.join(checkpoint_dir, ckpt_name)))
        else:
            print(" [*] Failed to find a checkpoint")
            return
        # stats_graph(tf.get_default_graph())

    begin = time.time()
    # print('Processing image: ' + sample_file)
    sample_image = np.asarray(load_test_data(test_file, img_size))
    image_path = os.path.join(result_dir,'{0}'.format(os.path.basename(test_file)))
    fake_img = g_sess.run(test_generated, feed_dict = {test_real : sample_image})
    if if_adjust_brightness:
        save_images(fake_img, image_path, test_file)
    else:
        save_images(fake_img, image_path, None)

    end = time.time()
    print(f'test-time: {end-begin} s')

    return image_path