code: def __init__(self):
      self.fc1 = layers.fc(100)
      self.fc2 = layers.fc(100)
      self.fc3 = layers.fc(100, bias_attr=False)
      self.fc4 = layers.fc(100, param_attr=False)
      self.fc5 = layers.fc(100, name="fc", bias_attr=False)
      self.fc6 = layers.fc(100, param_attr=fluid.initializer.Xavier())
      self.embedding = layers.embedding((100, 128))
      self.embedding_custom = layers.embedding(
          (100, 128), name="embedding_custom"
      )
      ## although here self.conv2d shares param with self.embedding,
      ## it might be invalid because the param sizes do not match
      self.conv2d = layers.conv2d(
          num_filters=64,
          filter_size=3,
          param_attr=self.embedding.attr_holder.param_attr,
          name="my_conv2d",
      )
  
      self.batch_norm = layers.batch_norm()
  
file_path: PARL/parl/core/fluid/layers/tests/param_name_test_fluid.py
imports: import parl
  from paddle import fluid
  from parl import layers
  import unittest
label_desc: Use image node_id 1 to create a new MyNetWork object from inherited base classes: parl with example: obj = MyNetWork()