def __init__(self,
name_scope,
hidden_size,
param_attr=None,
bias_attr=None,
gate_activation=None,
activation=None,
forget_bias=1.0,
dtype='float32'):
super(BasicLSTMUnit, self).__init__(name_scope, dtype)
# reserve old school _full_name and _helper for static graph save load
self._full_name = unique_name.generate(name_scope + "/" +
self.__class__.__name__)
self._helper = LayerObjectHelper(self._full_name)
self._name = name_scope
self._hiden_size = hidden_size
self._param_attr = param_attr
self._bias_attr = bias_attr
self._gate_activation = gate_activation or layers.sigmoid
self._activation = activation or layers.tanh
self._forget_bias = layers.fill_constant([1],
dtype=dtype,
value=forget_bias)
self._forget_bias.stop_gradient = False
self._dtype = dtype
def func_append_activation_in_dygraph3(self):
a_np = np.random.random(size=(10, 20, 30)).astype(np.float32)
helper = LayerObjectHelper(fluid.unique_name.generate("test"))
func = helper.append_activation
with fluid.dygraph.guard():
a = paddle.to_tensor(a_np)
res1 = func(a, act="sigmoid", use_cudnn=True)
res2 = fluid.layers.sigmoid(a)
self.assertTrue(np.array_equal(res1.numpy(), res2.numpy()))