class_docstr: Handles a SavedModel exported using TF 1.x APIs in TF 2.x.
class_docstr_tok: ["Handles","a","SavedModel","exported","using","TF","1.x","APIs","in","TF","2.x","."]
docstr: Applies a transform graph to dictionary of (Composite)Tensors.
  
  Args:
    logical_input_map: a dict of logical name to Tensor.  The logical names
      must be a subset of those in the input signature of the transform graph,
      and the corresponding Tensors must have the expected types and shapes.
  
  Returns:
    A dict of logical name to Tensor, as provided by the output signature of
    the transform graph.
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code: def apply_transform_model(
      self, logical_input_map: Mapping[str, common_types.TensorType]
  ) -> Dict[str, common_types.TensorType]:
      """Applies a transform graph to dictionary of (Composite)Tensors.
  
      Args:
        logical_input_map: a dict of logical name to Tensor.  The logical names
          must be a subset of those in the input signature of the transform graph,
          and the corresponding Tensors must have the expected types and shapes.
  
      Returns:
        A dict of logical name to Tensor, as provided by the output signature of
        the transform graph.
      """
      unexpected_inputs = set(logical_input_map.keys()) - set(
          self._structured_inputs.keys()
      )
      if unexpected_inputs:
          raise ValueError(
              "Unexpected inputs to transform: {}".format(
                  unexpected_inputs
              )
          )
  
      if self.load_v2_in_compat:
          return self._apply_v1_transform_model_in_v2(logical_input_map)
      elif self._is_finalized:
          return self._apply_v2_transform_model_finalized(
              logical_input_map
          )
      else:
          return self._apply_v2_transform_model(logical_input_map)
  
imports: from typing import Any, Dict, Iterable, Mapping, Tuple, Union
  import tensorflow
  from tensorflow_transform import annotators
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_tools
  from tensorflow_transform import tf2_utils
  from tensorflow_transform import tf_utils
  from tensorflow_transform.py_func import pyfunc_helper
  from tensorflow_transform.saved import constants
  from tensorflow_transform.saved import saved_model_loader
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow.python.eager import function
  from tensorflow.python.eager import wrap_function
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.ops import lookup_ops
  from tensorflow.python.util import object_identity
label_desc: Use image node_id 14 for calling the SavedModelLoader obj's underlying member method code with example usage: obj.apply_transform_model(logical_input_map) and returns: self, self, self