diff options
Diffstat (limited to 'src/TosaDeserialize.cpp')
-rw-r--r-- | src/TosaDeserialize.cpp | 34 |
1 files changed, 17 insertions, 17 deletions
diff --git a/src/TosaDeserialize.cpp b/src/TosaDeserialize.cpp index 45e1f18..3f8a6ef 100644 --- a/src/TosaDeserialize.cpp +++ b/src/TosaDeserialize.cpp @@ -101,12 +101,12 @@ mlir::LogicalResult BuildTensorType(mlir::OpBuilder *op_builder, template <class T> mlir::DenseElementsAttr BuildDenseI8ElementsAttr(mlir::OpBuilder *op_builder, const std::vector<T> &values) { - std::vector<int8_t> vec; + llvm::SmallVector<int8_t> vec; for (auto val : values) { vec.push_back(val); } - auto type = - mlir::RankedTensorType::get({vec.size()}, op_builder->getI8Type()); + auto type = mlir::RankedTensorType::get({static_cast<int64_t>(vec.size())}, + op_builder->getI8Type()); return mlir::DenseElementsAttr::get(type, llvm::ArrayRef(vec)); } @@ -114,12 +114,12 @@ template <class T> mlir::DenseElementsAttr BuildDenseI16ElementsAttr(mlir::OpBuilder *op_builder, const std::vector<T> &values) { - std::vector<int16_t> vec; + llvm::SmallVector<int16_t> vec; for (auto val : values) { vec.push_back(val); } - auto type = - mlir::RankedTensorType::get({vec.size()}, op_builder->getI16Type()); + auto type = mlir::RankedTensorType::get({static_cast<int64_t>(vec.size())}, + op_builder->getI16Type()); return mlir::DenseElementsAttr::get(type, llvm::ArrayRef(vec)); } @@ -127,12 +127,12 @@ template <class T> mlir::DenseElementsAttr BuildDenseI32ElementsAttr(mlir::OpBuilder *op_builder, const std::vector<T> &values) { - std::vector<int32_t> vec; + llvm::SmallVector<int32_t> vec; for (auto val : values) { vec.push_back(val); } - auto type = - mlir::RankedTensorType::get({vec.size()}, op_builder->getI32Type()); + auto type = mlir::RankedTensorType::get({static_cast<int64_t>(vec.size())}, + op_builder->getI32Type()); return mlir::DenseElementsAttr::get(type, llvm::ArrayRef(vec)); } @@ -810,8 +810,8 @@ TosaMlirOperatorBuilder::build<Op_PAD>(TosaSerializationOperator *op) const { TosaPadAttribute *attr = static_cast<TosaPadAttribute *>(op->GetAttribute()); auto padding_attr = BuildDenseI32ElementsAttr(op_builder, attr->padding()); - auto padding_type = mlir::RankedTensorType::get({attr->padding().size()}, - op_builder->getI32Type()); + auto padding_type = mlir::RankedTensorType::get( + {static_cast<int64_t>(attr->padding().size())}, op_builder->getI32Type()); mlir::Operation *mlir_const_op = op_builder->create<mlir::tosa::ConstOp>(loc, padding_type, padding_attr); block->push_back(mlir_const_op); @@ -872,8 +872,8 @@ std::vector<mlir::Value> TosaMlirOperatorBuilder::build<Op_TRANSPOSE>( // make a constant op from attr->perms values, of type: { shape = { perms.size // }, element_type = I32 } const auto perms_values = attr->perms(); - auto const_type = mlir::RankedTensorType::get({perms_values.size()}, - op_builder->getI32Type()); + auto const_type = mlir::RankedTensorType::get( + {static_cast<int64_t>(perms_values.size())}, op_builder->getI32Type()); mlir::DenseElementsAttr const_attr = BuildDenseI32ElementsAttr(op_builder, perms_values); mlir::Operation *mlir_const_op = @@ -1045,13 +1045,13 @@ TosaMlirOperatorBuilder::build<Op_TABLE>(TosaSerializationOperator *op) const { input_val.getType().cast<mlir::ShapedType>().getElementType(); if (input_element_type.isInteger(8)) { // table is signed 8 mode - const_type = mlir::RankedTensorType::get({table_values.size()}, - op_builder->getI8Type()); + const_type = mlir::RankedTensorType::get( + {static_cast<int64_t>(table_values.size())}, op_builder->getI8Type()); const_attr = BuildDenseI8ElementsAttr(op_builder, table_values); } else { // table is signed 16 mode - const_type = mlir::RankedTensorType::get({table_values.size()}, - op_builder->getI16Type()); + const_type = mlir::RankedTensorType::get( + {static_cast<int64_t>(table_values.size())}, op_builder->getI16Type()); const_attr = BuildDenseI16ElementsAttr(op_builder, table_values); } mlir::Operation *mlir_const_op = |