class_docstr: A wrapper around the output of the tf.Transform.
docstr: Takes a dict of tensors representing raw features and transforms them.
docstr_tok: ["Takes","a","dict","of","tensors","representing","raw","features","and","transforms","them","."]
code: def _transform_raw_features_compat_v1(
      self,
      raw_features: Mapping[str, common_types.TensorType],
      drop_unused_features: bool,
  ) -> Dict[str, common_types.TensorType]:
      """Takes a dict of tensors representing raw features and transforms them."""
      (
          unbounded_raw_features,
          transformed_features,
      ) = saved_transform_io.partially_apply_saved_transform_internal(
          self.transform_savedmodel_dir, raw_features
      )
      if drop_unused_features:
          graph = tf.compat.v1.get_default_graph()
          graph_analyzer = graph_tools.InitializableGraphAnalyzer(
              graph,
              raw_features,
              [(t, False) for t in unbounded_raw_features.values()],
          )
          return {
              name: feature
              for name, feature in transformed_features.items()
              if graph_analyzer.ready_to_run(feature)
          }
      else:
          return transformed_features
  
imports: import json
  import os
  from typing import Any, Dict, List, Mapping, Optional
  import numpy
  import tensorflow
  from tensorflow_transform import common
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_tools
  from tensorflow_transform.analyzers import sanitized_vocab_filename
  from tensorflow_transform.keras_lib import tf_keras
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tensorflow_transform.tf_metadata import metadata_io
  from tensorflow_transform.tf_metadata import schema_utils
  from tensorflow.python.framework import ops
  from tensorflow.tools.docs import doc_controls
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 15 for calling the TFTransformOutput obj's underlying member method code with example usage: obj._transform_raw_features_compat_v1(raw_features, drop_unused_features) and returns: unknown, transformed_features