class_docstr: PartitionedFunction will translate call to cached Function call
class_docstr_tok: ["PartitionedFunction","will","translate","call","to","cached","Function","call"]
docstr: length
code: def length(self):
      """length"""
      while self._length is None:
          # resolve until length is available
          partition = self._function()
          if partition.shape[0] == 0:
              self._length = sum(e.shape[0] for e in self._partitions)
          else:
              self._partitions.append(partition)
          partitions_indices = (
              tf.cumsum([e.shape[0] for e in self._partitions])
              .numpy()
              .tolist()
          )
          self._partitions_start = list([0] + partitions_indices[:-1])
          self._partitions_stop = partitions_indices
      return self._length
  
imports: import tensorflow
label_desc: Use image node_id 3 for calling the _IOTensorIterablePartitionedFunction obj's underlying member method code with example usage: obj.length() and returns: self