def __init__(self,
n_units,
forget_bias=0.0,
kernel_initializer=initializers.RandomUniformInitializer(0.01),
bias_initializer=initializers.RandomNormalInitializer(1e-6)):
super().__init__(n_in=2, n_out=2)
self._n_units = n_units
self._forget_bias = forget_bias
self._kernel_initializer = kernel_initializer
self._bias_initializer = bias_initializer
def __init__(self, bases=[11, 13, 14, 15], n_digits=8, # pylint: disable=dangerous-default-value
start_from_zero_one_in=100, base_dropout_one_in=100,
mode='train', initializer=init.RandomUniformInitializer(1e-4)):
super().__init__()
self._bases = bases
self._n_digits = n_digits
self._mode = mode
self._initializer = initializer
self._start_from_zero_one_in = start_from_zero_one_in
self._base_dropout_one_in = base_dropout_one_in
def test_random_uniform(self):
initializer = initializers.RandomUniformInitializer()
input_shape = (29, 5, 7, 20)
init_value = initializer(input_shape, random.get_prng(0))
self.assertEqual(tuple(init_value.shape), input_shape)
