class_docstr: Represents a handle for a live tensor in a session.
class_docstr_tok: ["Represents","a","handle","for","a","live","tensor","in","a","session","."]
docstr: Convert a TensorHandle object to a feedable numpy value.
  
  Returns:
    A numpy array of a custom struct type that can be used as a feed value
    to run().
docstr_tok: ["Convert","a","TensorHandle","object","to","a","feedable","numpy","value",".","Returns",":","A","numpy","array","of","a","custom","struct","type","that","can","be","used","as","a","feed","value","to","run","(",")","."]
code: def to_numpy_array(self):
      """Convert a TensorHandle object to a feedable numpy value.
  
      Returns:
        A numpy array of a custom struct type that can be used as a feed value
        to run().
      """
      return encode_resource_handle(self._get_resource_handle())
  
imports: import numpy
  from tensorflow.core.framework import resource_handle_pb2
  from tensorflow.python.client import pywrap_tf_session
  from tensorflow.python.framework import device
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_data_flow_ops
  from tensorflow.python.util import compat
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 5 for calling the TensorHandle obj's underlying member method code with example usage: obj.to_numpy_array() and returns: encode_resource_handle