[tosa_mlir_translator] Refactor QuantizationAttr

changes to serialization/deserialization due to removal of
quantization attr in TOSA dialect

Signed-off-by: Tai Ly <tai.ly@arm.com>
Change-Id: I0903d2c1c62bc50822e6c08bb869ec135c986ff3

1 files changed, 66 insertions, 54 deletions

diff --git a/src/TosaSerialize.cpp b/src/TosaSerialize.cpp
index 05c7812..0f5056d 100644
--- a/src/TosaSerialize.cpp
+++ b/src/TosaSerialize.cpp
@@ -471,14 +471,16 @@ TosaSerializationOperatorBuilder::BuildPoolOpFromMlirOp(mlir::Operation &op,
   std::string input_name = GetTensorName(op.getOperand(0));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info = op.getAttrOfType<mlir::tosa::UnaryOpQuantizationAttr>(
-      "quantization_info");
-
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t output_zp = quant_info ? quant_info.getOutputZp() : 0;
+  int32_t input_zp =
+      op.hasAttr("input_zp")
+          ? input_zp = op.getAttr("input_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t output_zp =
+      op.hasAttr("output_zp")
+          ? output_zp =
+                op.getAttr("output_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
-  mlir::RankedTensorType tensor =
-      op.getOperand(0).getType().cast<mlir::RankedTensorType>();
   TosaPoolAttribute attribute(pad, kernel, stride, input_zp, output_zp,
                               accum_dtype);
 
@@ -717,13 +719,14 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::Conv2DOp>(
   std::string input2_name = GetTensorName(op.getOperand(2));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info =
-      op.getAttrOfType<mlir::tosa::ConvOpQuantizationAttr>("quantization_info");
-
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t weight_zp = quant_info ? quant_info.getWeightZp() : 0;
-  mlir::RankedTensorType tensor =
-      op.getOperand(0).getType().cast<mlir::RankedTensorType>();
+  int32_t input_zp =
+      op.hasAttr("input_zp")
+          ? op.getAttr("input_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t weight_zp =
+      op.hasAttr("weight_zp")
+          ? op.getAttr("weight_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
   bool local_bound =
       op.hasAttr("local_bound")
@@ -759,13 +762,14 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::Conv3DOp>(
   std::string input2_name = GetTensorName(op.getOperand(2));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info =
-      op.getAttrOfType<mlir::tosa::ConvOpQuantizationAttr>("quantization_info");
-
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t weight_zp = quant_info ? quant_info.getWeightZp() : 0;
-  mlir::RankedTensorType tensor =
-      op.getOperand(0).getType().cast<mlir::RankedTensorType>();
+  int32_t input_zp =
+      op.hasAttr("input_zp")
+          ? op.getAttr("input_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t weight_zp =
+      op.hasAttr("weight_zp")
+          ? op.getAttr("weight_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
   bool local_bound =
       op.hasAttr("local_bound")
@@ -801,13 +805,14 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::DepthwiseConv2DOp>(
   std::string input2_name = GetTensorName(op.getOperand(2));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info =
-      op.getAttrOfType<mlir::tosa::ConvOpQuantizationAttr>("quantization_info");
-
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t weight_zp = quant_info ? quant_info.getWeightZp() : 0;
-  mlir::RankedTensorType tensor =
-      op.getOperand(0).getType().cast<mlir::RankedTensorType>();
+  int32_t input_zp =
+      op.hasAttr("input_zp")
+          ? op.getAttr("input_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t weight_zp =
+      op.hasAttr("weight_zp")
+          ? op.getAttr("weight_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
   bool local_bound =
       op.hasAttr("local_bound")
@@ -843,11 +848,15 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::TransposeConv2DOp>(
   std::string input2_name = GetTensorName(op.getOperand(2));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info =
-      op.getAttrOfType<mlir::tosa::ConvOpQuantizationAttr>("quantization_info");
+  int32_t input_zp =
+      op.hasAttr("input_zp")
+          ? op.getAttr("input_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t weight_zp =
+      op.hasAttr("weight_zp")
+          ? op.getAttr("weight_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t weight_zp = quant_info ? quant_info.getWeightZp() : 0;
   mlir::RankedTensorType tensor =
       op.getOperand(0).getType().cast<mlir::RankedTensorType>();
 
@@ -876,14 +885,15 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::FullyConnectedOp>(
   std::string input2_name = GetTensorName(op.getOperand(2));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info =
-      op.getAttrOfType<mlir::tosa::ConvOpQuantizationAttr>("quantization_info");
-
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t weight_zp = quant_info ? quant_info.getWeightZp() : 0;
+  int32_t input_zp =
+      op.hasAttr("input_zp")
+          ? op.getAttr("input_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t weight_zp =
+      op.hasAttr("weight_zp")
+          ? op.getAttr("weight_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
-  mlir::RankedTensorType tensor =
-      op.getOperand(0).getType().cast<mlir::RankedTensorType>();
   TosaFullyConnectedAttribute attribute(input_zp, weight_zp);
 
   TosaSerializationOperator *tyop = new TosaSerializationOperator(
@@ -902,13 +912,12 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::MatMulOp>(
   std::string input1_name = GetTensorName(op.getOperand(1));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info = op.getAttrOfType<mlir::tosa::MatMulOpQuantizationAttr>(
-      "quantization_info");
-
-  int32_t A_zp = quant_info ? quant_info.getAZp() : 0;
-  int32_t B_zp = quant_info ? quant_info.getBZp() : 0;
-  mlir::RankedTensorType tensor =
-      op.getOperand(0).getType().cast<mlir::RankedTensorType>();
+  int32_t A_zp = op.hasAttr("a_zp")
+                     ? op.getAttr("a_zp").cast<mlir::IntegerAttr>().getInt()
+                     : 0;
+  int32_t B_zp = op.hasAttr("b_zp")
+                     ? op.getAttr("b_zp").cast<mlir::IntegerAttr>().getInt()
+                     : 0;
 
   TosaMatMulAttribute attribute(A_zp, B_zp);
 
@@ -1035,13 +1044,16 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::NegateOp>(
   std::string input_name = GetTensorName(op.getOperand(0));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  auto quant_info = op.getAttrOfType<mlir::tosa::UnaryOpQuantizationAttr>(
-      "quantization_info");
-
-  int32_t input_zp = quant_info ? quant_info.getInputZp() : 0;
-  int32_t output_zp = quant_info ? quant_info.getOutputZp() : 0;
+  int32_t input1_zp =
+      op.hasAttr("input1_zp")
+          ? op.getAttr("input1_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
+  int32_t output_zp =
+      op.hasAttr("output_zp")
+          ? op.getAttr("output_zp").cast<mlir::IntegerAttr>().getInt()
+          : 0;
 
-  TosaNegateAttribute attribute(input_zp, output_zp);
+  TosaNegateAttribute attribute(input1_zp, output_zp);
 
   TosaSerializationOperator *tyop = new TosaSerializationOperator(
       Op_NEGATE, Attribute_NegateAttribute, &attribute,
@@ -1075,9 +1087,9 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::PadOp>(
   std::string output_name = GetTensorName(op.getResult(0));
   auto pad_op = llvm::cast<mlir::tosa::PadOp>(op);
 
-  auto quant_info = pad_op.getQuantizationInfoAttr();
+  auto input_zp_attr = pad_op.getInputZpAttr();
   // pad_const includes the zero point if the tensor uses a zero point.
-  int32_t pad_const_int = quant_info ? quant_info.getInputZp() : 0;
+  int32_t pad_const_int = input_zp_attr ? input_zp_attr.getInt() : 0;
   float pad_const_fp = 0.f;
 
   if (auto tensor = pad_op.getPadConst()) {