def test_unknown_shape(self):
fn = lisht.get_concrete_function(
tf.TensorSpec(shape=None, dtype=tf.float32))
for shape in [(1, ), (1, 2), (1, 2, 3), (1, 2, 3, 4)]:
x = tf.ones(shape=shape, dtype=tf.float32)
self.assertAllClose(fn(x), lisht(x))
def verify_funcs_are_equivalent(self, dtype):
x_np = np.random.uniform(-10, 10, size=(4, 4)).astype(dtype)
x = tf.convert_to_tensor(x_np)
with tf.GradientTape(persistent=True) as t:
t.watch(x)
y_native = lisht(x)
y_py = _lisht_py(x)
self.assertAllCloseAccordingToType(y_native, y_py)
grad_native = t.gradient(y_native, x)
grad_py = t.gradient(y_py, x)
self.assertAllCloseAccordingToType(grad_native, grad_py)
def test_lisht(self, dtype):
x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype)
expected_result = tf.constant(
[1.9280552, 0.7615942, 0.0, 0.7615942, 1.9280552], dtype=dtype)
self.assertAllCloseAccordingToType(lisht(x), expected_result)
def test_lisht(dtype):
x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype)
expected_result = tf.constant(
[1.9280552, 0.7615942, 0.0, 0.7615942, 1.9280552], dtype=dtype
)
test_utils.assert_allclose_according_to_type(lisht(x), expected_result)
