message: Update comment on quantize operator to highlight the usage that the op can
  quantize float to int8/uint8
  requantize int8/uint8 to int8/uint8
diff: @@ -92,6 +92,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  switch (input->type) {
  case kTfLiteFloat32: {
  + // Float to int8, uint8.
  tflite::QuantizationParams op_params;
  op_params.zero_point = output->params.zero_point;
  op_params.scale = output->params.scale;
  @@ -112,6 +113,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  }
  } break;
  case kTfLiteInt8: {
  + // int8 to int8, uint8.
  const int32_t size =
  MatchingFlatSize(GetTensorShape(input), GetTensorShape(output));
  if (output->type == kTfLiteInt8) {
  @@ -133,6 +135,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  }
  } break;
  case kTfLiteUInt8: {
  + // uint8 to int8, uint8.
  const int32_t size =
  MatchingFlatSize(GetTensorShape(input), GetTensorShape(output));
  if (output->type == kTfLiteInt8) {
  @@ -166,6 +169,13 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  } // namespace quantize
  +// This Op (QUANTIZE) quantizes the input and produces quantized output.
  +// The input can be either float or quantized. If the input is float,
  +// AffineQuantize takes scale and zero point and quantize the float value to
  +// quantized output, in int8 or uint8 format. If the input is quantized value,
  +// the op requantize the input (of a certain type, with a given scale and zero
  +// point) to the output of the same or different type with a same or different
  +// scale and zero point.
  TfLiteRegistration* Register_QUANTIZE_OPT() {
  static TfLiteRegistration r = {quantize::Init, quantize::Free,
  quantize::Prepare, quantize::Eval};
  