code: def resize3d(
      data,
      roi,
      size,
      layout="NCDHW",
      method="linear",
      coordinate_transformation_mode="half_pixel",
      rounding_method="",
      bicubic_alpha=-0.5,
      bicubic_exclude=0,
      extrapolation_value=0.0,
      out_dtype=None,
      output_shape=None,
  ):
      """Perform resize operation on the data.
  
      Parameters
      ----------
      data : tvm.te.Tensor
          inputs is a 5-D tensor with shape
          [batch, channel, in_depth, in_height, in_width]
          or  [batch, in_depth, in_height, in_width, channel]
  
      roi: Tuple of Float or Expr
          The region of interest for cropping the input image. Expected to be of
          size 6, and format [start_d, start_h, start_w, end_d, end_h, end_w].
          Only used if coordinate_transformation_mode is tf_crop_and_resize.
  
      size: Tuple
          Output resolution scale to
  
      layout: string, optional
          "NCDHW", "NDHWC", or "NCDHWc".
  
      method: string, optional
          method of interpolation ("nearest", "linear", "bicubic")
  
      coordinate_transformation_mode : string, optional
          Describes how to transform the coordinate in the resized tensor
          to the coordinate in the original tensor.
          [half_pixel, align_corners, asymmetric, pytorch_half_pixel,
          tf_half_pixel_for_nn, and tf_crop_and_resize].
  
      rounding_method:
          Method for rounding coordinate locations
  
      bicubic_alpha: float, optional
          Bicubic spline coefficient
  
      bicubic_exclude: bool, optional:
          Exclude values outside the image fdor bicubic interpolation
  
      extrapolation_value: float, optional
          Value used for extrapolation, when applicable.
  
      out_dtype: string, optional
          Type to return. If left None will be same as input type.
  
      output_shape: tvm.tir.container.Array, optional
          Shape to return. If left None will be inferred
          (If shape is determined dynamically, pass out_dtype.shape as output_shape)
  
      Returns
      -------
      output : tvm.te.Tensor
          4-D with shape [batch, channel, in_depth*scale, in_height*scale, in_width*scale]
          or [batch, in_depth*scale, in_height*scale, in_width*scale, channel]
          or 5-D with shape
          [batch, channel-major, in_depth*scale, in_height*scale, in_width*scale, channel-minor]
      """
  
      method = method.lower()
      if layout == "NDHWC":
          in_n, in_d, in_h, in_w, in_c = data.shape
          output_shape = [in_n, size[0], size[1], size[2], in_c]
      elif layout == "NCDHW":
          in_n, in_c, in_d, in_h, in_w = data.shape
          output_shape = [in_n, in_c, size[0], size[1], size[2]]
      # Otherwise layout must be NCHWxc
      else:
          in_n, in_c, in_d, in_h, in_w, in_cc = data.shape
          output_shape = [in_n, in_c, size[0], size[1], size[2], in_cc]
  
      if isinstance(size, tuple):
          size = list(size)
  
      for i in range(3):
          if isinstance(size[i], int):
              size[i] = tvm.tir.IntImm("int32", size[i])
  
      def compute_func(*indices):
          return _resize_3d(
              indices,
              data,
              roi,
              in_d,
              in_h,
              in_w,
              size[0],
              size[1],
              size[2],
              method=method,
              layout=layout,
              coordinate_transformation_mode=coordinate_transformation_mode,
              rounding_method=rounding_method,
              alpha=bicubic_alpha,
              exclude_outside=bicubic_exclude,
              extrapolation_value=extrapolation_value,
              out_dtype=out_dtype,
          )
  
      return te.compute(
          output_shape, compute_func, name="resize", tag=tag.INJECTIVE
      )
  
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 19 for calling a global function with example usage: resize3d(data, roi, size, layout, method, coordinate_transformation_mode, rounding_method, bicubic_alpha, bicubic_exclude, extrapolation_value, out_dtype, output_shape) and returns: te, _resize_3d