TFL_OperandHasRank<0, 4>,
    TFL_OperandHasRank<1, 1>,
    SameOperandsAndResultsScale]> {
  let summary = "ResizeBilinear Op";

  let description = [{
    Resize `images` to `size` using bilinear interpolation.
  }];

  let arguments = (ins
    TFL_TensorOf<[F32, TFL_Quint8, QUI8, QI8, QI16]>:$input,
    TFL_I32Tensor:$size,
    BoolAttr:$align_corners,

  let hasVerifier = 1;

  let hasCanonicalizer = 1;
  let hasFolder = 1;
}

def TF_ResizeBilinearOp : TF_Op<"ResizeBilinear", [Pure]> {
  let summary = "Resize `images` to `size` using bilinear interpolation.";

  let description = [{
Input images can be of different types but output images are always float.
  }];

  let arguments = (ins

        how many times the function is called, and independent of global seed
        settings.
    *   Adds deterministic `tf.image.resize` backprop CUDA kernels for
        `method=ResizeMethod.BILINEAR` (the default method). Enable by setting
        the environment variable `TF_DETERMINISTIC_OPS` to `"true"` or `"1"`.
*   `tf.print`:
    *   Bug fix in `tf.print()` with `OrderedDict` where if an `OrderedDict`

nk:[255,182,193],lightsalmon:[255,160,122],lightseagreen:[32,178,170],lightskyblue:[135,206,250],lightslategray:[119,136,153],lightslategrey:[119,136,153],lightsteelblue:[176,196,222],lightyellow:[255,255,224],lime:[0,255,0],limegreen:[50,205,50],linen:[250,240,230],magenta:[255,0,255],maroon:[128,0,0],mediumaquamarine:[102,205,170],mediumblue:[0,0,205],mediumorchid:[186,85,211],mediumpurple:[147,112,219],mediumseagreen:[60,179,113],mediumslateblue:[123,104,238],mediumspringgreen:[0,250,154],med...