uprank rank 1 inputs, so these layers can now multi-hot encode
            unbatched multi-dimensional samples.
        *   Added a new output mode `"one_hot"` for `CategoryEncoding`,
            `StringLookup`, `IntegerLookup`, which will encode each element in
            an input batch individually, and automatically append a new output

  );

  TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;

  let hasFolder = 1;
}

def TF_EncodePngOp : TF_Op<"EncodePng", [Pure]> {
  let summary = "PNG-encode an image.";

  let description = [{
`image` is a 3-D uint8 or uint16 Tensor of shape `[height, width, channels]`
where `channels` is:

*   1: for grayscale.
*   2: for grayscale + alpha.