code: def embedding_lookup(lookup_table, x, use_tpu=True):
      if use_tpu:
          n_token = tf.shape(lookup_table)[0]
          one_hot_idx = tf.one_hot(x, n_token)
          if one_hot_idx.shape.ndims == 2:
              return tf.einsum("nd,in->id", lookup_table, one_hot_idx)
          else:
              return tf.einsum("nd,ibn->ibd", lookup_table, one_hot_idx)
      else:
          return tf.nn.embedding_lookup(lookup_table, x)
  
file_path: delta/gcompiler/example/python/nlp_transformer/model.py
imports: import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: embedding_lookup(lookup_table, x, use_tpu) and returns: tf, tf, tf