code: def emb(
      uid,
      iid,
      num_users,
      num_items,
      emb_size,
      reg_user,
      reg_item,
      seed=None,
      scope="emb",
  ):
      with tf.variable_scope(scope):
          user_emb = tf.get_variable(
              "user_emb",
              shape=[num_users, emb_size],
              dtype=tf.float32,
              initializer=tf.random_normal_initializer(
                  stddev=0.01, seed=seed
              ),
              regularizer=tf.keras.regularizers.L2(reg_user),
          )
          item_emb = tf.get_variable(
              "item_emb",
              shape=[num_items, emb_size],
              dtype=tf.float32,
              initializer=tf.random_normal_initializer(
                  stddev=0.01, seed=seed
              ),
              regularizer=tf.keras.regularizers.L2(reg_item),
          )
  
      return tf.nn.embedding_lookup(
          user_emb, uid
      ), tf.nn.embedding_lookup(item_emb, iid)
  
imports: import warnings
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: emb(uid, iid, num_users, num_items, emb_size, reg_user, reg_item, seed, scope) and returns: tf,  tf