Change PadOp's padding to TOSA Shape

PadOp's padding input is now a tosa.shape type.
Changed serialization of PadOp to not store padding as attribute.
Changed deserialization of PadOp to not restore padding from attribute.

Signed-off-by: Tai Ly <tai.ly@arm.com>
Change-Id: I8a622978ea184b8d2779d311adba629c1a0d1fbd

1 files changed, 3 insertions, 11 deletions

diff --git a/src/TosaDeserialize.cpp b/src/TosaDeserialize.cpp
index 2421d79..5956bc8 100644
--- a/src/TosaDeserialize.cpp
+++ b/src/TosaDeserialize.cpp
@@ -1029,6 +1029,7 @@ template <>
 std::vector<mlir::Value>
 TosaMlirOperatorBuilder::build<Op_PAD>(TosaSerializationOperator *op) const {
   mlir::Value input_val = tensor_map->at(op->GetInputTensorNames()[0]);
+  mlir::Value padding_val = tensor_map->at(op->GetInputTensorNames()[1]);
   mlir::RankedTensorType input_type =
       tensor_type_map->at(op->GetInputTensorNames()[0]);
   mlir::RankedTensorType output_type =
@@ -1038,15 +1039,6 @@ TosaMlirOperatorBuilder::build<Op_PAD>(TosaSerializationOperator *op) const {
          Attribute_PadAttribute); // double check attribute type
   TosaPadAttribute *attr = static_cast<TosaPadAttribute *>(op->GetAttribute());
 
-  // padding has shape {rank(input_type), 2}
-  auto padding_type = mlir::RankedTensorType::get({input_type.getRank(), 2},
-                                                  op_builder->getI32Type());
-  auto padding_attr =
-      BuildDenseI32ElementsAttr(op_builder, padding_type, attr->padding());
-  mlir::Operation *mlir_const_op =
-      op_builder->create<mlir::tosa::ConstOp>(loc, padding_type, padding_attr);
-  block->push_back(mlir_const_op);
-  auto padding_value = mlir_const_op->getResult(0);
   auto pad_const_int = attr->pad_const_int();
   auto pad_const_fp = attr->pad_const_fp();
   // todo: int input_zp = attr->pad_input_zp();
@@ -1055,7 +1047,7 @@ TosaMlirOperatorBuilder::build<Op_PAD>(TosaSerializationOperator *op) const {
   if (pad_const_int == 0 && pad_const_fp == 0.0f) {
     // no pad_const input
     mlir_op = op_builder->create<mlir::tosa::PadOp>(loc, output_type, input_val,
-                                                    padding_value);
+                                                    padding_val);
   } else {
     // create a const value for pad_const input
     const auto input_element_type =
@@ -1083,7 +1075,7 @@ TosaMlirOperatorBuilder::build<Op_PAD>(TosaSerializationOperator *op) const {
       pad_const_value = pad_const_fp_op->getResult(0);
     }
     mlir_op = op_builder->create<mlir::tosa::PadOp>(
-        loc, output_type, input_val, padding_value, pad_const_value);
+        loc, output_type, input_val, padding_val, pad_const_value);
   }
   block->push_back(mlir_op);
   return std::vector<mlir::Value>({mlir_op->getResult(0)});