Switch ArrayAttr to DenseArrayAttr

Align with mlir commits:
  9e1a344155c0b78be46348b94cae635b7305326c
  11030c7d67a7ac0b469e3fbc53dd7a09b47792c9

Change-Id: I5be0fc084fabc1057a39127b67a1ee9a55e5079f
Signed-off-by: TatWai Chong <tatwai.chong@arm.com>

1 files changed, 41 insertions, 139 deletions

diff --git a/src/TosaSerialize.cpp b/src/TosaSerialize.cpp
index 51923ea..ead54f1 100644
--- a/src/TosaSerialize.cpp
+++ b/src/TosaSerialize.cpp
@@ -202,6 +202,19 @@ TosaSerializationOperatorBuilder::GetTensorName(mlir::Value val) const {
   assert(0);
 }
 
+// Unpack 64-bit integer attribute element and pack into a std vector.
+template <class T>
+static std::vector<T> getDenseI64ArrayAttr(mlir::Attribute attr) {
+  auto array_ref = attr.cast<mlir::DenseI64ArrayAttr>().asArrayRef();
+
+  std::vector<T> vec;
+  for (auto val : array_ref) {
+    vec.push_back(val);
+  }
+
+  return vec;
+}
+
 // Main template to catch unimplemented translation.
 template <typename T>
 TosaSerializationOperator *
@@ -225,26 +238,13 @@ TosaSerializationOperatorBuilder::build(mlir::Operation &op) const {
 TosaSerializationOperator *
 TosaSerializationOperatorBuilder::BuildPoolOpFromMlirOp(mlir::Operation &op,
                                                         Op opcode) const {
-  std::vector<int> pad, stride, kernel;
-
-  auto pad_attr = op.getAttr("pad").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : pad_attr) {
-    pad.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto pad = getDenseI64ArrayAttr<int>(op.getAttr("pad"));
   ASSERT_VECTOR_LENGTH(pad, 4);
 
-  auto stride_attr =
-      op.getAttr("stride").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : stride_attr) {
-    stride.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto stride = getDenseI64ArrayAttr<int>(op.getAttr("stride"));
   ASSERT_VECTOR_LENGTH(stride, 2);
 
-  auto kernel_attr =
-      op.getAttr("kernel").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : kernel_attr) {
-    kernel.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto kernel = getDenseI64ArrayAttr<int>(op.getAttr("kernel"));
   ASSERT_VECTOR_LENGTH(kernel, 2);
 
   std::string input_name = GetTensorName(op.getOperand(0));
@@ -549,26 +549,13 @@ template <>
 TosaSerializationOperator *
 TosaSerializationOperatorBuilder::build<mlir::tosa::Conv2DOp>(
     mlir::Operation &op) const {
-  std::vector<int> pad, stride, dilation;
-
-  auto pad_attr = op.getAttr("pad").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : pad_attr) {
-    pad.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto pad = getDenseI64ArrayAttr<int>(op.getAttr("pad"));
   ASSERT_VECTOR_LENGTH(pad, 4);
 
-  auto stride_attr =
-      op.getAttr("stride").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : stride_attr) {
-    stride.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto stride = getDenseI64ArrayAttr<int>(op.getAttr("stride"));
   ASSERT_VECTOR_LENGTH(stride, 2);
 
-  auto dilation_attr =
-      op.getAttr("dilation").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : dilation_attr) {
-    dilation.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto dilation = getDenseI64ArrayAttr<int>(op.getAttr("dilation"));
   ASSERT_VECTOR_LENGTH(dilation, 2);
 
   std::string input0_name = GetTensorName(op.getOperand(0));
@@ -600,26 +587,13 @@ template <>
 TosaSerializationOperator *
 TosaSerializationOperatorBuilder::build<mlir::tosa::Conv3DOp>(
     mlir::Operation &op) const {
-  std::vector<int> pad, stride, dilation;
-
-  auto pad_attr = op.getAttr("pad").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : pad_attr) {
-    pad.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto pad = getDenseI64ArrayAttr<int>(op.getAttr("pad"));
   ASSERT_VECTOR_LENGTH(pad, 6);
 
-  auto stride_attr =
-      op.getAttr("stride").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : stride_attr) {
-    stride.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto stride = getDenseI64ArrayAttr<int>(op.getAttr("stride"));
   ASSERT_VECTOR_LENGTH(stride, 3);
 
-  auto dilation_attr =
-      op.getAttr("dilation").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : dilation_attr) {
-    dilation.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto dilation = getDenseI64ArrayAttr<int>(op.getAttr("dilation"));
   ASSERT_VECTOR_LENGTH(dilation, 3);
 
   std::string input0_name = GetTensorName(op.getOperand(0));
@@ -650,26 +624,13 @@ template <>
 TosaSerializationOperator *
 TosaSerializationOperatorBuilder::build<mlir::tosa::DepthwiseConv2DOp>(
     mlir::Operation &op) const {
-  std::vector<int> pad, stride, dilation;
-
-  auto pad_attr = op.getAttr("pad").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : pad_attr) {
-    pad.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto pad = getDenseI64ArrayAttr<int>(op.getAttr("pad"));
   ASSERT_VECTOR_LENGTH(pad, 4);
 
-  auto stride_attr =
-      op.getAttr("stride").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : stride_attr) {
-    stride.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto stride = getDenseI64ArrayAttr<int>(op.getAttr("stride"));
   ASSERT_VECTOR_LENGTH(stride, 2);
 
-  auto dilation_attr =
-      op.getAttr("dilation").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : dilation_attr) {
-    dilation.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto dilation = getDenseI64ArrayAttr<int>(op.getAttr("dilation"));
   ASSERT_VECTOR_LENGTH(dilation, 2);
 
   std::string input0_name = GetTensorName(op.getOperand(0));
@@ -700,28 +661,14 @@ template <>
 TosaSerializationOperator *
 TosaSerializationOperatorBuilder::build<mlir::tosa::TransposeConv2DOp>(
     mlir::Operation &op) const {
-  std::vector<int> outpad, stride, dilation, output_shape;
-
-  auto outpad_attr =
-      op.getAttr("out_pad").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : outpad_attr) {
-    outpad.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
-  ASSERT_VECTOR_LENGTH(outpad, 4);
+  auto out_pad = getDenseI64ArrayAttr<int>(op.getAttr("out_pad"));
+  ASSERT_VECTOR_LENGTH(out_pad, 4);
 
-  auto stride_attr =
-      op.getAttr("stride").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : stride_attr) {
-    stride.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto stride = getDenseI64ArrayAttr<int>(op.getAttr("stride"));
   ASSERT_VECTOR_LENGTH(stride, 2);
 
-  auto output_shape_attr =
-      op.getAttr("out_shape").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : output_shape_attr) {
-    output_shape.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
-  ASSERT_VECTOR_LENGTH(output_shape, 4);
+  auto out_shape = getDenseI64ArrayAttr<int>(op.getAttr("out_shape"));
+  ASSERT_VECTOR_LENGTH(out_shape, 4);
 
   std::string input0_name = GetTensorName(op.getOperand(0));
   std::string input1_name = GetTensorName(op.getOperand(1));
@@ -737,7 +684,7 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::TransposeConv2DOp>(
       op.getOperand(0).getType().cast<mlir::RankedTensorType>();
   DType type = Type2AccumDType(tensor.getElementType());
 
-  TosaTransposeConvAttribute attribute(outpad, stride, output_shape, input_zp, weight_zp, type);
+  TosaTransposeConvAttribute attribute(out_pad, stride, out_shape, input_zp, weight_zp, type);
 
   TosaSerializationOperator *tyop = new TosaSerializationOperator(
       Op_TRANSPOSE_CONV2D, Attribute_TransposeConvAttribute, &attribute,
@@ -919,13 +866,7 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::ReshapeOp>(
     mlir::Operation &op) const {
   std::string input_name = GetTensorName(op.getOperand(0));
   std::string output_name = GetTensorName(op.getResult(0));
-
-  std::vector<int> shape;
-  auto shape_attr =
-      op.getAttr("new_shape").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : shape_attr) {
-    shape.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto shape = getDenseI64ArrayAttr<int>(op.getAttr("new_shape"));
 
   TosaReshapeAttribute attribute(shape);
 
@@ -993,17 +934,8 @@ template <>
 TosaSerializationOperator *
 TosaSerializationOperatorBuilder::build<mlir::tosa::SliceOp>(
     mlir::Operation &op) const {
-  std::vector<int> start, size;
-  auto begin_attr = op.getAttr("start").dyn_cast<mlir::ArrayAttr>().getValue();
-  auto size_attr = op.getAttr("size").dyn_cast<mlir::ArrayAttr>().getValue();
-
-  for (auto &int_attr : begin_attr) {
-    start.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
-
-  for (auto &int_attr : size_attr) {
-    size.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto start = getDenseI64ArrayAttr<int>(op.getAttr("start"));
+  auto size = getDenseI64ArrayAttr<int>(op.getAttr("size"));
 
   TosaSliceAttribute attribute(start, size);
 
@@ -1024,13 +956,7 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::TileOp>(
     mlir::Operation &op) const {
   std::string input_name = GetTensorName(op.getOperand(0));
   std::string output_name = GetTensorName(op.getResult(0));
-
-  std::vector<int> multiples;
-  auto multiples_attr =
-      op.getAttr("multiples").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : multiples_attr) {
-    multiples.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto multiples = getDenseI64ArrayAttr<int>(op.getAttr("multiples"));
 
   TosaTileAttribute attribute(multiples);
 
@@ -1082,28 +1008,13 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::ResizeOp>(
   std::string input_name = GetTensorName(op.getOperand(0));
   std::string output_name = GetTensorName(op.getResult(0));
 
-  std::vector<int16_t> scale;
-  auto scale_attr =
-      op.getAttr("scale").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : scale_attr) {
-    scale.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto scale = getDenseI64ArrayAttr<int16_t>(op.getAttr("scale"));
   ASSERT_VECTOR_LENGTH(scale, 4);
 
-  std::vector<int16_t> offset;
-  auto offset_attr =
-      op.getAttr("offset").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : offset_attr) {
-    offset.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto offset = getDenseI64ArrayAttr<int16_t>(op.getAttr("offset"));
   ASSERT_VECTOR_LENGTH(offset, 2);
 
-  std::vector<int16_t> border;
-  auto border_attr =
-      op.getAttr("border").dyn_cast<mlir::ArrayAttr>().getValue();
-  for (auto &int_attr : border_attr) {
-    border.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto border = getDenseI64ArrayAttr<int16_t>(op.getAttr("border"));
   ASSERT_VECTOR_LENGTH(border, 2);
 
   auto mode_str =
@@ -1222,18 +1133,9 @@ TosaSerializationOperatorBuilder::build<mlir::tosa::RescaleOp>(
   bool per_channel =
       op.getAttr("per_channel").dyn_cast<mlir::BoolAttr>().getValue();
 
-  std::vector<int> multiplier, shift;
-  auto multiplier_attr =
-      op.getAttr("multiplier").dyn_cast<mlir::ArrayAttr>().getValue();
-  auto shift_attr = op.getAttr("shift").dyn_cast<mlir::ArrayAttr>().getValue();
-
-  for (auto &int_attr : multiplier_attr) {
-    multiplier.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
-
-  for (auto &int_attr : shift_attr) {
-    shift.push_back(int_attr.dyn_cast<mlir::IntegerAttr>().getInt());
-  }
+  auto multiplier =
+      op.getAttr("multiplier").dyn_cast<mlir::DenseI32ArrayAttr>().asArrayRef();
+  auto shift = op.getAttr("shift").dyn_cast<mlir::DenseI32ArrayAttr>().asArrayRef();
 
   std::string input_name = GetTensorName(op.getOperand(0));
   std::string output_name = GetTensorName(op.getResult(0));