What does tf.nn.embedding_lookup function do?

Question

tf.nn.embedding_lookup(params, ids, partition_strategy=\'mod\', name=None)

I cannot understand the duty of this function. Is it like a lookup table

Answer 1

When the params tensor is in high dimensions, the ids only refers to top dimension. Maybe it's obvious to most of people but I have to run the following code to understand that:

embeddings = tf.constant([[[1,1],[2,2],[3,3],[4,4]],[[11,11],[12,12],[13,13],[14,14]],
                          [[21,21],[22,22],[23,23],[24,24]]])
ids=tf.constant([0,2,1])
embed = tf.nn.embedding_lookup(embeddings, ids, partition_strategy='div')

with tf.Session() as session:
    result = session.run(embed)
    print (result)

Just trying the 'div' strategy and for one tensor, it makes no difference.

Here is the output:

[[[ 1  1]
  [ 2  2]
  [ 3  3]
  [ 4  4]]

 [[21 21]
  [22 22]
  [23 23]
  [24 24]]

 [[11 11]
  [12 12]
  [13 13]
  [14 14]]]