|
- #!/usr/bin/env python
- # -*- coding: utf-8 -*-
-
- import os
- import unittest
-
- os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
-
- import numpy as np
-
- import tensorflow as tf
- import tensorlayer as tl
-
- from tests.utils import CustomTestCase
-
-
- class Util_Predict_Test(CustomTestCase):
-
- @classmethod
- def setUpClass(cls):
- cls.x1 = tf.placeholder(tf.float32, [None, 5, 5, 3])
- cls.x2 = tf.placeholder(tf.float32, [8, 5, 5, 3])
- cls.X1 = np.ones([127, 5, 5, 3])
- cls.X2 = np.ones([7, 5, 5, 3])
- cls.batch_size = 8
-
- @classmethod
- def tearDownClass(cls):
- tf.reset_default_graph()
-
- def test_case1(self):
- with self.assertNotRaises(Exception):
- with tf.Session() as sess:
- n = tl.layers.InputLayer(self.x1)
- y = n.outputs
- y_op = tf.nn.softmax(y)
- tl.utils.predict(sess, n, self.X1, self.x1, y_op, batch_size=self.batch_size)
- sess.close()
-
- def test_case2(self):
- with self.assertRaises(Exception):
- with tf.Session() as sess:
- n = tl.layers.InputLayer(self.x2)
- y = n.outputs
- y_op = tf.nn.softmax(y)
- tl.utils.predict(sess, n, self.X2, self.x2, y_op, batch_size=self.batch_size)
- sess.close()
-
-
- if __name__ == '__main__':
-
- tf.logging.set_verbosity(tf.logging.DEBUG)
- tl.logging.set_verbosity(tl.logging.DEBUG)
-
- unittest.main()
|