code: def get_print_tensor_argparser(description):
      """Get an ArgumentParser for a command that prints tensor values.
  
      Examples of such commands include print_tensor and print_feed.
  
      Args:
        description: Description of the ArgumentParser.
  
      Returns:
        An instance of argparse.ArgumentParser.
      """
  
      ap = argparse.ArgumentParser(
          description=description, usage=argparse.SUPPRESS
      )
      ap.add_argument(
          "tensor_name",
          type=str,
          help="Name of the tensor, followed by any slicing indices, "
          "e.g., hidden1/Wx_plus_b/MatMul:0, "
          "hidden1/Wx_plus_b/MatMul:0[1, :]",
      )
      ap.add_argument(
          "-n",
          "--number",
          dest="number",
          type=int,
          default=-1,
          help="0-based dump number for the specified tensor. "
          "Required for tensor with multiple dumps.",
      )
      ap.add_argument(
          "-r",
          "--ranges",
          dest="ranges",
          type=str,
          default="",
          help="Numerical ranges to highlight tensor elements in. "
          "Examples: -r 0,1e-8, -r [-0.1,0.1], "
          '-r "[[-inf, -0.1], [0.1, inf]]"',
      )
      ap.add_argument(
          "-a",
          "--all",
          dest="print_all",
          action="store_true",
          help="Print the tensor in its entirety, i.e., do not use ellipses.",
      )
      ap.add_argument(
          "-s",
          "--numeric_summary",
          action="store_true",
          help="Include summary for non-empty tensors of numeric (int*, float*, "
          "complex*) and Boolean types.",
      )
      ap.add_argument(
          "-w",
          "--write_path",
          type=str,
          default="",
          help="Path of the numpy file to write the tensor data to, using "
          "numpy.save().",
      )
      return ap
  
imports: import argparse
  import ast
  import re
  import sys
label_desc: Use image node_id 14 for calling a global function with example usage: get_print_tensor_argparser(description) and returns: ap