code: def normalized_columns_initializer(std=1.0):
      def _initializer(shape, dtype=None, partition_info=None):
          out = np.random.randn(*shape).astype(np.float32)
          out *= std / np.sqrt(
              np.square(out).sum(axis=0, keepdims=True)
          )
          return tf.constant(out)
  
      return _initializer
  
imports: import numpy
  import tensorflow
  from tensorflow.python.ops.losses.losses_impl import Reduction
  from rl_coach.architectures.tensorflow_components.layers import Dense, convert_layer_class
  from rl_coach.base_parameters import AgentParameters
  from rl_coach.spaces import SpacesDefinition
  from rl_coach.utils import force_list
  from rl_coach.architectures.tensorflow_components.utils import squeeze_tensor
label_desc: Use image node_id 1 for calling a global function with example usage: normalized_columns_initializer(std) and returns: _initializer, tf