class_docstr: The LookUp module maps (embeds) input ids into *fixed* representations. The representations are     not be updated during training. The module outputs a tensor with shape     **shape(ids) + [embedding dimensionality]**.
  
  Parameters
  ----------
  embed: numpy array
      Fixed embedding matrix.
  ids: Tensorflow tensor, optional
      List of ids to retrieve embeddings. If *None*, the whole embedding matrix is returned.
  scope: str, optional
      Scope for module variables.
  reuse: bool, optional
      Whether or not to reuse module variables.
code: def _build_shared_graph(self):
      with tf.variable_scope(self._scope, reuse=self._reuse):
          self.embedding = tf.Variable(
              self._embed,
              trainable=False,
              name="embedding",
              dtype=tf.float32,
          )
          if self._ids is not None:
              self._outputs.append(
                  tf.nn.embedding_lookup(self.embedding, self._ids)
              )
          else:
              self._outputs.append(self.embedding)
  
file_path: openrec/openrec/tf1/legacy/modules/extractions/look_up.py
imports: from __future__ import print_function
  import tensorflow
  from termcolor import colored
  from openrec.tf1.legacy.modules.extractions import Extraction
label_desc: Use image node_id 2 for calling the LookUp obj's underlying member method code with example usage: obj._build_shared_graph() without return types