quantization_method,
    bool enable_per_channel_quantization);

LogicalResult FillAttributesForUniformQuantizedConvolutionOp(
    PatternRewriter& rewriter, Operation* op,
    llvm::StringMap<Attribute>& identifier_to_attr,
    tensorflow::quantization::QuantizationMethod::PresetMethod
        quantization_method,
    bool enable_per_channel_quantization);

LogicalResult FillAttributesForUniformQuantizedAddOp(

  BitType bit_type = 3;

  // Defines whether quantization is done in narrow range.
  bool enable_narrow_range = 4;

  // Defines whether quantiation is done per-channel.
  bool enable_per_channel_quantization = 5;

  // Defines whether quantization is done symmetrically.
  bool enable_symmetric = 6;

  // not applied regardless of the op support. Currently, it is supported for
  // XLA opset for SRQ on weight tensors (not activation),
  // and Uniform Quantized opset .
  optional bool enable_per_channel_quantization = 10;

  // Enables two inputs of an operation to be both tensors.
  // Currently supports MatMul and BatchMatMul ops for XLA.
  // TODO(b/263528090): Check the condition when this feature is beneficial.