class_docstr: Visitor optimizes the operation graph (see nodes.py).
  
  This operates on the translated graph which is emitted by the
  `_TranslateVisitor`, and performs optimizations.
  
  Namely, when enabled, this enables reading and writing from/to analyzer
  accumulator cache to avoid recomputing them over already seen datasets.
  This type of optimization requires also creating a partitioned view of the
  input data, according to the `is_partitionable` annotation.
code: def validate_value(self, value):
      assert isinstance(value, _OptimizationView), value
      if value.fine_grained_view:
          assert set(value.fine_grained_view.keys()) == set(
              self._sorted_dataset_keys
          ), f"{value.fine_grained_view.keys()} != {self._sorted_dataset_keys}"
  
imports: import collections
  import dataclasses
  import hashlib
  from typing import Collection, Dict, Mapping, Optional, Tuple
  from typing import OrderedDict
  import tensorflow
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_tools
  from tensorflow_transform import impl_helper
  from tensorflow_transform import nodes
  from tensorflow_transform import tf2_utils
  from tensorflow_transform import tf_utils
  from tensorflow_transform.beam import analyzer_cache
  from tensorflow_transform.beam import beam_nodes
  from tensorflow_transform.beam import combiner_packing_util
label_desc: Use image node_id 9 for calling the _OptimizeVisitor obj's underlying member method code with example usage: obj.validate_value(value) without return types