def test_he_normal(self):
   tensor_shape = (5, 6, 4, 2)
   with self.test_session():
     fan_in, _ = init_ops._compute_fans(tensor_shape)
     scale = np.sqrt(2. / fan_in)
     self._runner(keras.initializers.he_normal(seed=123), tensor_shape,
                  target_mean=0., target_std=None, target_max=2 * scale)

 def test_he_uniform(self):
   tensor_shape = (5, 6, 4, 2)
   with self.test_session():
     fan_in, _ = init_ops._compute_fans(tensor_shape)
     scale = np.sqrt(6. / fan_in)
     self._runner(keras.initializers.he_uniform(seed=123), tensor_shape,
                  target_mean=0., target_max=scale, target_min=-scale)

 def test_he_uniform(self):
   tensor_shape = (5, 6, 4, 2)
   with self.cached_session():
     fan_in, _ = init_ops._compute_fans(tensor_shape)
     std = np.sqrt(2. / fan_in)
     self._runner(keras.initializers.he_uniform(seed=123), tensor_shape,
                  target_mean=0., target_std=std)

 def test_glorot_normal(self):
   tensor_shape = (5, 6, 4, 2)
   with self.cached_session():
     fan_in, fan_out = init_ops._compute_fans(tensor_shape)
     std = np.sqrt(2. / (fan_in + fan_out))
     self._runner(keras.initializers.glorot_normal(seed=123), tensor_shape,
                  target_mean=0., target_std=std)

 def test_lecun_normal(self):
   tensor_shape = (5, 6, 4, 2)
   with self.test_session():
     fan_in, _ = init_ops._compute_fans(tensor_shape)
     std = np.sqrt(1. / fan_in)
     self._runner(keras.initializers.lecun_normal(seed=123), tensor_shape,
                  target_mean=0., target_std=std)

 def test_lecun_uniform(self):
   tensor_shape = (5, 6, 4, 2)
   with self.cached_session():
     fan_in, _ = init_ops._compute_fans(tensor_shape)
     std = np.sqrt(1. / fan_in)
     self._runner(
         init_ops.lecun_uniform(seed=123),
         tensor_shape,
         target_mean=0.,
         target_std=std)

 def test_he_normal(self):
   tensor_shape = (5, 6, 4, 2)
   with self.test_session():
     fan_in, _ = init_ops._compute_fans(tensor_shape)
     std = np.sqrt(2. / fan_in)
     self._runner(
         init_ops.he_normal(seed=123),
         tensor_shape,
         target_mean=0.,
         target_std=std)