class_docstr: Packed representation of compressed tensors.
  
  This class can pack and unpack several tensor values into a single string. It
  can also optionally store a model identifier.
  
  The tensors currently must be rank 1 (vectors) and either have integer or
  string type.
docstr: Unpacks values from this object based on dtypes.
code: def unpack(self, dtypes):
      """Unpacks values from this object based on dtypes."""
      tensors = []
      for i, dtype in enumerate(dtypes):
          dtype = tf.as_dtype(dtype)
          feature = self._example.features.feature[chr(i + 1)]
          if dtype.is_integer:
              tensors.append(
                  tf.constant(feature.int64_list.value, dtype=dtype)
              )
          elif dtype.is_floating:
              tensors.append(
                  tf.constant(feature.float_list.value, dtype=dtype)
              )
          elif dtype == tf.string:
              tensors.append(
                  tf.constant(feature.bytes_list.value, dtype=dtype)
              )
          else:
              raise RuntimeError(f"Unexpected dtype: '{dtype}'.")
      return tensors
  
file_path: compression/tensorflow_compression/python/util/packed_tensors.py
imports: import tensorflow
label_desc: Use image node_id 8 for calling the PackedTensors obj's underlying member method code with example usage: obj.unpack(dtypes) and returns: tensors