class_docstr: Creates TreeEnsemble resource.
code: def __init__(
      self, name, stamp_token=0, is_local=False, serialized_proto=""
  ):
      self._stamp_token = stamp_token
      self._serialized_proto = serialized_proto
      self._is_local = is_local
      with ops.name_scope(name, "TreeEnsemble") as name:
          self._name = name
          self.resource_handle = self._create_resource()
          self._init_op = self._initialize()
          is_initialized_op = self.is_initialized()
          # Adds the variable to the savable list.
          if not is_local:
              ops.add_to_collection(
                  ops.GraphKeys.SAVEABLE_OBJECTS,
                  _TreeEnsembleSavable(
                      self.resource_handle,
                      self.initializer,
                      self.resource_handle.name,
                  ),
              )
          resources.register_resource(
              self.resource_handle,
              self.initializer,
              is_initialized_op,
              is_shared=not is_local,
          )
  
imports: from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_boosted_trees_ops
  from tensorflow.python.ops import resources
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_aggregate_stats
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_bucketize
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_calculate_best_feature_split
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_calculate_best_feature_split_v2
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_calculate_best_gains_per_feature
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_center_bias
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_create_quantile_stream_resource
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_example_debug_outputs
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_make_quantile_summaries
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_make_stats_summary
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_predict
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_quantile_stream_resource_add_summaries
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_quantile_stream_resource_deserialize
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_quantile_stream_resource_flush
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_quantile_stream_resource_get_bucket_boundaries
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_quantile_stream_resource_handle_op
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_sparse_aggregate_stats
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_sparse_calculate_best_feature_split
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_training_predict
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_update_ensemble
  from tensorflow.python.ops.gen_boosted_trees_ops import boosted_trees_update_ensemble_v2
  from tensorflow.python.ops.gen_boosted_trees_ops import is_boosted_trees_quantile_stream_resource_initialized
  from tensorflow.python.training import saver
label_desc: Use image node_id 1 to create a new TreeEnsemble object  with example: obj = TreeEnsemble(name, stamp_token, is_local, serialized_proto)