def test_get_layer_policy(self):
layer = core.Dense(4)
self.assertEqual(
get_layer_policy.get_layer_policy(layer).name, 'float32')
p = policy.Policy('mixed_float16')
layer = core.Dense(4, dtype=p)
self.assertIs(get_layer_policy.get_layer_policy(layer), p)
layer = core.Dense(4, dtype='float64')
self.assertEqual(
get_layer_policy.get_layer_policy(layer).name, 'float64')
def _test_saving(self, model, dataset, save_format, use_regularizer):
# Save and load model, asserting variable does not change
save_path = os.path.join(self.get_temp_dir(), 'model')
model.save(save_path, save_format=save_format)
model = save.load_model(save_path)
(layer, ) = (layer for layer in model.layers
if 'MultiplyLayer' in layer.__class__.__name__)
expected = 1 - 2**-14
if use_regularizer:
expected -= 2**-14
self.assertEqual(backend.eval(layer.v), expected)
# Continue training, and assert variable is correct value
model.fit(dataset)
new_expected = expected - 2**-14
if use_regularizer:
new_expected -= 2**-14
self.assertEqual(backend.eval(layer.v), new_expected)
# Load saved model again, and assert variable is previous value
model = save.load_model(save_path)
(layer, ) = (layer for layer in model.layers
if 'MultiplyLayer' in layer.__class__.__name__)
self.assertEqual(backend.eval(layer.v), expected)
# Ensure various dtype-related aspects of the layer are correct
self.assertEqual(layer.dtype, 'float32')
self.assertEqual(
get_layer_policy.get_layer_policy(layer).name, 'mixed_float16')
self.assertEqual(layer.v.dtype, 'float32')
self.assertEqual(layer(np.ones((2, 1))).dtype, 'float16')
def test_mixed_policies_(self, strategy_fn):
for dtype in 'float16', 'bfloat16':
x = constant_op.constant([1.])
policy_name = 'mixed_' + dtype
with strategy_fn().scope(), policy.policy_scope(policy_name):
layer = mp_test_util.MultiplyLayer(assert_type=dtype)
self.assertEqual(layer.dtype, dtypes.float32)
self.assertEqual(
get_layer_policy.get_layer_policy(layer).name, policy_name)
y = layer(x)
self.assertEqual(layer.v.dtype, dtypes.float32)
self.assertEqual(y.dtype, dtype)
self.assertEqual(layer.dtype, dtypes.float32)
self.assertEqual(
get_layer_policy.get_layer_policy(layer).name, policy_name)
self.evaluate(variables.global_variables_initializer())
self.assertEqual(self.evaluate(y), 1.)
def test_error(self):
with self.assertRaisesRegexp(
ValueError,
'get_policy can only be called on a layer, but got: 1'):
get_layer_policy.get_layer_policy(1)
