code: def conv_block_3d(
      tensor,
      num_filters,
      size,
      strides,
      normalization=None,
      dropout=False,
      alpha_lrelu=0.2,
      relu=True,
      rate=0.7,
  ):
      """3D convolution block with normalization and leaky relu."""
      tensor = tf.keras.layers.Conv3D(
          num_filters,
          size,
          strides=strides,
          padding="same",
          kernel_initializer=tf.keras.initializers.glorot_normal(),
          use_bias=False,
      )(tensor)
  
      tensor = norm_layer(tensor, normalization)
  
      if relu:
          tensor = tf.keras.layers.LeakyReLU(alpha=alpha_lrelu)(tensor)
      if dropout:
          tensor = tf.keras.layers.Dropout(rate)(tensor)
      return tensor
  
label_desc: Use image node_id 2 for calling a global function with example usage: conv_block_3d(tensor, num_filters, size, strides, normalization, dropout, alpha_lrelu, relu, rate) and returns: tensor