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)