def test_ragged_last(self):
source = tf.ragged.constant([['1', 'z'], [' ', '\n', '💥', '❤️']])
expected = tf.constant([['Nd', 'Ll', '', ''], ['Zs', 'Cc', 'Cs',
'Mn']])
result = char_category(source, first=False).to_tensor(default_value='')
expected, result = self.evaluate([expected, result])
self.assertAllEqual(expected, result)
def test_inference_shape(self):
source = [
['1', 'z', ' '],
['❤️', 'я', '-'],
]
result = char_category(source)
self.assertAllEqual([2, 3], result.shape.as_list())
def test_actual_shape(self):
source = [
['1', 'z', ' '],
['❤️', 'я', '-'],
]
result = char_category(source)
result = tf.shape(result)
result = self.evaluate(result)
self.assertAllEqual([2, 3], result.tolist())
def test_skip(self):
result = char_category([['X', '-Y-', 'z']], skip=['-Y-'])
result = self.evaluate(result)
self.assertAllEqual([[b'Lu', b'-Y-', b'Ll']], result)
def test_2d(self):
result = char_category([['X']])
result = self.evaluate(result)
self.assertAllEqual([[b'Lu']], result)
def test_0d(self):
result = char_category('X')
result = self.evaluate(result)
self.assertAllEqual(b'Lu', result)
def test_empty(self):
result = char_category('')
result = self.evaluate(result)
self.assertAllEqual(b'Cn', result)