code: def testNoDataDependentInitialization(self, model_type):
      init_kernel = np.ones((self.data_dim, self.num_hidden))
      init_norm = tf.reshape(
          tf.norm(
              tf.reshape(init_kernel, [-1, self.num_hidden]), axis=0
          ),
          (self.num_hidden,),
      )
  
      model = self._define_model(
          model_type, self.data_dim, self.num_hidden, data_init=False
      )
      model.build(self.random_input.shape)
      self.evaluate([v.initializer for v in model.weights])
      norm_layer = self._get_maybe_norm_layer(model)
      self.evaluate(model(self.random_input))
  
      self.assertAllClose(init_norm, self.evaluate(norm_layer.g))
  
imports: import tempfile
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.layers import weight_norm
label_desc: Use image node_id 12 for calling the WeightNormTest obj's underlying member method code with example usage: obj.testNoDataDependentInitialization(model_type) without return types