import os

import tensorflow as tf

from utils import store_to_csv

import config

from model_utils import x, evaluate_test_set, evaluate_solution

from model_factory import ModelFactory

# Construct model

factory = ModelFactory()

model = factory.get_network_model()

softmax_prediction = tf.nn.softmax(model.conv_net(x, 1.0), 

    name='softmax_prediction')

data_loader = factory.get_data_loader()

test_set = data_loader.get_exact_tests_set()

out_dir = data_loader.results_out_dir()

print(out_dir)

saver = tf.train.Saver()

with tf.Session() as sess:

    sess.run(tf.global_variables_initializer())

    if os.path.exists(os.path.join(out_dir, config.RESTORE_MODEL_CKPT + '.index')):

        saver.restore(sess, os.path.join(out_dir, config.RESTORE_MODEL_CKPT))

        evaluate_test_set(sess, 

                          test_set,

                          softmax_prediction,

                          x)

        if os.path.exists(config.SOLUTION_FILE_PATH):

            print("Evaluate generated solution...")

            evaluate_solution(config.SOLUTION_FILE_PATH)

        else:

          print("Solution file was not generated, check if test data is complete...")

    else:

        print("Checkpoint file {} does not exist in the configured directory {}.".format(

            config.RESTORE_MODEL_CKPT, out_dir))