code: def get_inx(
      x,
      image_width,
      target_width,
      coordinate_transformation_mode,
      start_x=0,
      end_x=-1,
      use_int_div=False,
  ):
      """Infer input x from output x with various coordinate transformation methods"""
      scale_x = te.div(
          image_width.astype("float"), target_width.astype("float")
      )
      if coordinate_transformation_mode == "half_pixel":
          in_x = (x + 0.5) * scale_x - 0.5
      elif coordinate_transformation_mode == "align_corners":
          in_x = (
              (image_width - 1).astype("float") / (target_width - 1) * x
          )
      elif coordinate_transformation_mode == "asymmetric":
          if use_int_div:
              in_x = te.div(x, te.div(target_width, image_width))
          else:
              in_x = scale_x * x
      elif coordinate_transformation_mode == "pytorch_half_pixel":
          in_x = te.if_then_else(
              target_width > 1, (x + 0.5) * scale_x - 0.5, 0.0
          )
      elif coordinate_transformation_mode == "tf_half_pixel_for_nn":
          in_x = (x + 0.5) * scale_x
      elif coordinate_transformation_mode == "tf_crop_and_resize":
          in_x = te.if_then_else(
              target_width > 1,
              start_x * (image_width - 1)
              + x
              * (end_x - start_x)
              * (image_width - 1).astype("float")
              / (target_width - 1),
              0.5 * (start_x + end_x) * (image_width - 1),
          )
      else:
          raise ValueError(
              f"Unsupported coordinate_transformation_mode: {coordinate_transformation_mode}"
          )
      return in_x
  
imports: from __future__ import absolute_import
  import tvm
  from tvm import te
  from tvm.topi.utils import nchw_pack_layout, nchw_xc_layout
  from ..None import tag
label_desc: Use image node_id 8 for calling a global function with example usage: get_inx(x, image_width, target_width, coordinate_transformation_mode, start_x, end_x, use_int_div) and returns: in_x