def testOneHotEncoding(self): with self.test_session(): labels = tf.constant([0, 1, 2]) one_hot_labels = tf.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]]) output = ops.one_hot_encoding(labels, num_classes=3) self.assertAllClose(output.eval(), one_hot_labels.eval())
def testOneHotEncodingCreate(self): with self.test_session(): labels = tf.constant([0, 1, 2]) output = ops.one_hot_encoding(labels, num_classes=3) self.assertEquals(output.op.name, 'OneHotEncoding/SparseToDense') self.assertListEqual(output.get_shape().as_list(), [3, 3])
def testOneHotEncodingCreate(self): with self.test_session(): labels = tf.constant([0, 1, 2]) output = ops.one_hot_encoding(labels, num_classes=3) self.assertEqual(output.op.name, 'OneHotEncoding/SparseToDense') self.assertListEqual(output.get_shape().as_list(), [3, 3])