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refactorone
Validate Operations / validate-operations (push) Has been cancelled
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NiccoloN
2026-05-20 19:06:41 +02:00
parent f56c4159b5
commit a50e77ff38
50 changed files with 3420 additions and 1187 deletions
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src/PIM/Conversion/ONNXToSpatial/Common/ComputeRegionBuilder.hpp
+15 -6
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@@ -18,13 +18,17 @@ namespace detail {
inline mlir::ValueRange getBlockArgs(mlir::Block* block) { return mlir::ValueRange(block->getArguments()); }
inline mlir::ValueRange getInputBlockArgs(mlir::Block* block, size_t weightCount) {
return mlir::ValueRange(block->getArguments()).drop_front(weightCount);
}
template <typename Fn, size_t... Is>
decltype(auto) invokeWithBlockArgs(Fn&& fn, mlir::Block* block, std::index_sequence<Is...>) {
return std::forward<Fn>(fn)(block->getArgument(Is)...);
}
template <typename Fn, size_t... Is>
decltype(auto) invokeWithValues(Fn&& fn, mlir::ArrayRef<mlir::Value> values, std::index_sequence<Is...>) {
decltype(auto) invokeWithValues(Fn&& fn, mlir::ValueRange values, std::index_sequence<Is...>) {
return std::forward<Fn>(fn)(values[Is]...);
}
@@ -85,6 +89,8 @@ auto createSpatCompute(RewriterT& rewriter,
auto computeOp = spatial::SpatCompute::create(rewriter, loc, resultTypes, weights, inputs);
auto* block = new mlir::Block();
for (mlir::Value weight : weights)
block->addArgument(weight.getType(), loc);
for (mlir::Value input : inputs)
block->addArgument(input.getType(), loc);
@@ -93,14 +99,15 @@ auto createSpatCompute(RewriterT& rewriter,
using BodyResult = detail::InvokeWithBlockArgsResultT<std::decay_t<BodyFn>, std::make_index_sequence<NumInputs>>;
if constexpr (std::is_same_v<BodyResult, void>) {
detail::invokeWithBlockArgs(std::forward<BodyFn>(body), block, std::make_index_sequence<NumInputs> {});
detail::invokeWithValues(
std::forward<BodyFn>(body), detail::getInputBlockArgs(block, weights.size()), std::make_index_sequence<NumInputs> {});
rewriter.setInsertionPointAfter(computeOp);
return computeOp;
}
else {
auto bodyResult =
detail::invokeWithBlockArgs(std::forward<BodyFn>(body), block, std::make_index_sequence<NumInputs> {});
auto bodyResult = detail::invokeWithValues(
std::forward<BodyFn>(body), detail::getInputBlockArgs(block, weights.size()), std::make_index_sequence<NumInputs> {});
if (mlir::failed(bodyResult)) {
rewriter.setInsertionPointAfter(computeOp);
rewriter.eraseOp(computeOp);
@@ -123,6 +130,8 @@ auto createSpatCompute(RewriterT& rewriter,
auto computeOp = spatial::SpatCompute::create(rewriter, loc, resultTypes, weights, inputs);
auto* block = new mlir::Block();
for (mlir::Value weight : weights)
block->addArgument(weight.getType(), loc);
for (mlir::Value input : inputs)
block->addArgument(input.getType(), loc);
@@ -131,13 +140,13 @@ auto createSpatCompute(RewriterT& rewriter,
using BodyResult = detail::InvokeWithValueRangeResultT<std::decay_t<BodyFn>>;
if constexpr (std::is_same_v<BodyResult, void>) {
std::forward<BodyFn>(body)(detail::getBlockArgs(block));
std::forward<BodyFn>(body)(detail::getInputBlockArgs(block, weights.size()));
rewriter.setInsertionPointAfter(computeOp);
return computeOp;
}
else {
auto bodyResult = std::forward<BodyFn>(body)(detail::getBlockArgs(block));
auto bodyResult = std::forward<BodyFn>(body)(detail::getInputBlockArgs(block, weights.size()));
if (mlir::failed(bodyResult)) {
rewriter.setInsertionPointAfter(computeOp);
rewriter.eraseOp(computeOp);