[tosa_mlir_translator] Support dynamic tensors

This adds serialization and deserialization support for:
  -  unranked tensors (eg, *xi32) and
  -  tensors with dynamic shapes (eg, ?x?xi32)

Signed-off-by: Tai Ly <tai.ly@arm.com>
Change-Id: Ib2943333d8e3a199cf8a909b6db7197150666700

1 files changed, 18 insertions, 6 deletions

diff --git a/src/TosaSerialize.cpp b/src/TosaSerialize.cpp
index 741597b..f74df1d 100644
--- a/src/TosaSerialize.cpp
+++ b/src/TosaSerialize.cpp
@@ -1650,13 +1650,25 @@ TosaSerializationBlockBuilder::BuildTosaSerializationTensor(
     return nullptr;
   }
 
-  auto ranked = val.getType().dyn_cast<mlir::RankedTensorType>();
-  std::vector<int32_t> shape =
-      ttype.hasRank() ? std::vector<int32_t>(ranked.getShape().begin(),
-                                             ranked.getShape().end())
-                      : std::vector<int32_t>();
+  const bool is_unranked = !ttype.hasRank();
+  std::vector<int32_t> shape;
+  if (!is_unranked) {
+    auto shaped = val.getType().dyn_cast<mlir::ShapedType>();
+    assert(shaped);
+    for (int idx = 0; idx < ttype.getRank(); idx++) {
+      if (shaped.isDynamicDim(idx)) {
+        shape.push_back(0); // size of 0 represents dynamic dimension
+      } else {
+        auto dim = shaped.getDimSize(idx);
+        assert(dim > 0);
+        shape.push_back(dim);
+      }
+    }
+  }
+
   DType type = Type2DType(ttype.getElementType());
-  ts = new TosaSerializationTensor(name, shape, type, std::vector<uint8_t>());
+  ts = new TosaSerializationTensor(name, shape, type, std::vector<uint8_t>(),
+                                   /* variable = */ false, is_unranked);
 
   return ts;
 }