code: def mlp(input_tensor, layers, activ_fn=tf.nn.relu, layer_norm=False):
      """
      Create a multi-layer fully connected neural network.
  
      :param input_tensor: (tf.placeholder)
      :param layers: ([int]) Network architecture
      :param activ_fn: (tf.function) Activation function
      :param layer_norm: (bool) Whether to apply layer normalization or not
      :return: (tf.Tensor)
      """
      output = input_tensor
      for i, layer_size in enumerate(layers):
          output = tf.layers.dense(
              output, layer_size, name="fc" + str(i)
          )
          if layer_norm:
              output = tf.contrib.layers.layer_norm(
                  output, center=True, scale=True
              )
          output = activ_fn(output)
      return output
  
file_path: stable-baselines/stable_baselines/common/tf_layers.py
imports: import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: mlp(input_tensor, layers, activ_fn, layer_norm) and returns: output