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add .clang-format

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reformat all src
This commit is contained in:
NiccoloN
2026-02-26 19:16:42 +01:00
parent a2c31836ae
commit 810e5e75f9
32 changed files with 902 additions and 953 deletions
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133
src/PIM/Conversion/SpatialToGraphviz/SpatialToGraphviz.cpp
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@@ -1,23 +1,21 @@
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Tosa/IR/TosaOps.h"
#include "mlir/IR/Block.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/IR/Value.h"
#include "mlir/Support/LLVM.h"
#include "src/Accelerators/PIM/Dialect/Spatial/SpatialOps.hpp"
#include "src/Accelerators/PIM/Pass/PimPasses.hpp"
#include "src/Dialect/ONNX/ONNXOps.hpp"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Tosa/IR/TosaOps.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Support/LLVM.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/Format.h"
#define FORMAT_OPERATION(op) \
'x' << llvm::format_hex_no_prefix(reinterpret_cast<size_t>(op), 0)
#define FORMAT_ARGUMENT(computeOpPointer, argumentNum) \
llvm::format("Arg_%p_%u", computeOpPointer, argumentNum)
#include "src/Accelerators/PIM/Dialect/Spatial/SpatialOps.hpp"
#include "src/Accelerators/PIM/Pass/PimPasses.hpp"
#include "src/Dialect/ONNX/ONNXOps.hpp"
#define FORMAT_OPERATION(op) 'x' << llvm::format_hex_no_prefix(reinterpret_cast<size_t>(op), 0)
#define FORMAT_ARGUMENT(computeOpPointer, argumentNum) llvm::format("Arg_%p_%u", computeOpPointer, argumentNum)
using namespace mlir;
@@ -25,26 +23,22 @@ namespace onnx_mlir {
namespace {
struct SpatialToGraphvizPass
: public PassWrapper<SpatialToGraphvizPass, OperationPass<ModuleOp>> {
struct SpatialToGraphvizPass : public PassWrapper<SpatialToGraphvizPass, OperationPass<ModuleOp>> {
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(SpatialToGraphvizPass)
StringRef getArgument() const override {
return "convert-spatial-to-graphviz";
}
StringRef getArgument() const override { return "convert-spatial-to-graphviz"; }
StringRef getDescription() const override {
return "Lower ONNX ops to Spatial ops.";
}
StringRef getDescription() const override { return "Lower ONNX ops to Spatial ops."; }
SpatialToGraphvizPass(raw_ostream &os = llvm::errs()) : os(os) {}
SpatialToGraphvizPass(const SpatialToGraphvizPass &pass)
: SpatialToGraphvizPass(pass.os) {}
SpatialToGraphvizPass(raw_ostream& os = llvm::errs())
: os(os) {}
SpatialToGraphvizPass(const SpatialToGraphvizPass& pass)
: SpatialToGraphvizPass(pass.os) {}
void runOnOperation() final;
private:
raw_ostream &os;
raw_ostream& os;
/**
* Draws the subgraph for a given spatial::SpatWeightedCompute, including:
@@ -56,31 +50,27 @@ private:
* @param computeNum The number of the compute operation.
*/
void drawComputeOpSubgraph(spatial::SpatWeightedCompute op, size_t computeNum) {
os << "\tsubgraph cluster" << computeNum << " {\n\t\tlabel=\"Compute"
<< computeNum << "\";\n"
os << "\tsubgraph cluster" << computeNum << " {\n\t\tlabel=\"Compute" << computeNum << "\";\n"
<< "\t\tstyle=filled;\n"
<< "\t\tcolor=lightblue;\n";
Block &block = op.getBody().front();
Block& block = op.getBody().front();
// Inputs
size_t inputNum = 0;
for (BlockArgument &input : block.getArguments()) {
for (BlockArgument& input : block.getArguments()) {
auto fromOp = FORMAT_ARGUMENT(op.getOperation(), inputNum);
os << "\t\t" << fromOp << " [label=\"Arg" << inputNum
<< "\",shape=box];\n";
for (auto userOp : input.getUsers()) {
os << "\t\t" << fromOp << " [label=\"Arg" << inputNum << "\",shape=box];\n";
for (auto userOp : input.getUsers())
os << "\t\t" << fromOp << " -> " << FORMAT_OPERATION(userOp) << ";\n";
}
inputNum++;
}
// Iterate operations
for (auto &childOp : block.getOperations()) {
os << "\t\t" << FORMAT_OPERATION(&childOp) << " [label=\""
<< childOp.getName() << "\"];\n";
for (auto& childOp : block.getOperations()) {
os << "\t\t" << FORMAT_OPERATION(&childOp) << " [label=\"" << childOp.getName() << "\"];\n";
drawEdgesFromOpToItsUsers(&childOp);
}
@@ -88,7 +78,7 @@ private:
os << "\t}\n";
// Draw edges from the yield to the users of this computeOp
Operation *yieldOp = block.getTerminator();
Operation* yieldOp = block.getTerminator();
if (!isa<spatial::SpatYieldOp>(yieldOp)) {
yieldOp->emitError("Terminator of block must be YieldOp ???");
signalPassFailure();
@@ -96,9 +86,8 @@ private:
}
for (auto computeOpResult : op->getResults()) {
for (auto &computeOpUse : computeOpResult.getUses()) {
auto toOp = FORMAT_ARGUMENT(
computeOpUse.getOwner(), computeOpUse.getOperandNumber());
for (auto& computeOpUse : computeOpResult.getUses()) {
auto toOp = FORMAT_ARGUMENT(computeOpUse.getOwner(), computeOpUse.getOperandNumber());
os << "\t" << FORMAT_OPERATION(yieldOp) << " -> " << toOp << ";\n";
}
}
@@ -114,9 +103,8 @@ private:
* @param concatOp The concatOp for which the subgraph is drawn.
* @param concatOpNum The number of the concatOp.
*/
void drawConcatOpSubgraph(Operation *concatOp, size_t concatOpNum) {
os << "\tsubgraph clusterconcat" << concatOpNum
<< " {\n\t\tlabel=\"ConcatOp" << concatOpNum << "\";\n"
void drawConcatOpSubgraph(Operation* concatOp, size_t concatOpNum) {
os << "\tsubgraph clusterconcat" << concatOpNum << " {\n\t\tlabel=\"ConcatOp" << concatOpNum << "\";\n"
<< "\t\tstyle=filled;\n"
<< "\t\tcolor=orange;\n";
@@ -126,9 +114,8 @@ private:
auto fromOp = FORMAT_ARGUMENT(concatOp, inputNum);
os << "\t\t" << fromOp << " [label=\"Input" << inputNum << "\"];\n";
for (auto userOp : input.getUsers()) {
for (auto userOp : input.getUsers())
os << "\t\t" << fromOp << " -> " << FORMAT_OPERATION(userOp) << ";\n";
}
inputNum++;
}
@@ -139,11 +126,9 @@ private:
// Edges from output to users
for (auto &computeOpUse : concatOp->getResult(0).getUses()) {
for (auto& computeOpUse : concatOp->getResult(0).getUses()) {
os << "\t" << FORMAT_OPERATION(concatOp) << " -> "
<< FORMAT_ARGUMENT(
computeOpUse.getOwner(), computeOpUse.getOperandNumber())
<< ";\n";
<< FORMAT_ARGUMENT(computeOpUse.getOwner(), computeOpUse.getOperandNumber()) << ";\n";
}
}
@@ -164,10 +149,8 @@ private:
sliceOp.getStaticOffsetsAttr().print(os);
os << "\",color=lawngreen];\n";
for (auto &computeOpUse : sliceOp.getResult().getUses()) {
os << "\t" << nodeId << " -> "
<< FORMAT_ARGUMENT(
computeOpUse.getOwner(), computeOpUse.getOperandNumber())
for (auto& computeOpUse : sliceOp.getResult().getUses()) {
os << "\t" << nodeId << " -> " << FORMAT_ARGUMENT(computeOpUse.getOwner(), computeOpUse.getOperandNumber())
<< ";\n";
}
}
@@ -178,9 +161,8 @@ private:
sliceOp.getStaticOffsetsAttr().print(os);
os << "\",color=lightpink];\n";
for (auto user : sliceOp.getResult().getUsers()) {
for (auto user : sliceOp.getResult().getUsers())
os << "\t" << nodeId << " -> " << FORMAT_OPERATION(user) << ";\n";
}
}
/**
@@ -188,13 +170,10 @@ private:
*
* @param fromOp The operation from which the edges are drawn.
*/
void drawEdgesFromOpToItsUsers(mlir::Operation *fromOp) {
for (auto result : fromOp->getResults()) {
for (auto userOp : result.getUsers()) {
os << "\t\t" << FORMAT_OPERATION(fromOp) << " -> "
<< FORMAT_OPERATION(userOp) << ";\n";
}
}
void drawEdgesFromOpToItsUsers(mlir::Operation* fromOp) {
for (auto result : fromOp->getResults())
for (auto userOp : result.getUsers())
os << "\t\t" << FORMAT_OPERATION(fromOp) << " -> " << FORMAT_OPERATION(userOp) << ";\n";
}
/**
@@ -202,16 +181,15 @@ private:
*
* @param funcOp The `funcOp` for which to draw input nodes and edges.
*/
void drawInputNodesAndEdges(func::FuncOp &funcOp) {
void drawInputNodesAndEdges(func::FuncOp& funcOp) {
os << "\tinput [label=\"Module Input\",color=green];\n";
size_t funcOpArgNum = 0;
for (BlockArgument &arg : funcOp.getArguments()) {
for (BlockArgument& arg : funcOp.getArguments()) {
for (auto &useOp : arg.getUses()) {
os << "\tinput -> "
<< FORMAT_ARGUMENT(useOp.getOwner(), useOp.getOperandNumber())
<< "[label=" << funcOpArgNum << "];\n";
for (auto& useOp : arg.getUses()) {
os << "\tinput -> " << FORMAT_ARGUMENT(useOp.getOwner(), useOp.getOperandNumber()) << "[label=" << funcOpArgNum
<< "];\n";
}
funcOpArgNum++;
}
@@ -237,20 +215,22 @@ void SpatialToGraphvizPass::runOnOperation() {
// Iterate over the ComputeOps within FuncOp:
// 1. Print their subgraph
// 2. Print the edges from its inputs to its outputs
for (Operation &op : func.getOps()) {
for (Operation& op : func.getOps()) {
if (auto computeOp = dyn_cast<spatial::SpatWeightedCompute>(op)) {
drawComputeOpSubgraph(computeOp, computeNum++);
} else if (auto concatOp = dyn_cast<tensor::ConcatOp>(op)) {
}
else if (auto concatOp = dyn_cast<tensor::ConcatOp>(op)) {
drawConcatOpSubgraph(concatOp, concatNum++);
} else if (auto imgConcatOp = dyn_cast<spatial::SpatImgConcatOp>(op)) {
}
else if (auto imgConcatOp = dyn_cast<spatial::SpatImgConcatOp>(op)) {
drawConcatOpSubgraph(imgConcatOp, concatNum++);
} else if (auto extractSliceOp = dyn_cast<tensor::ExtractSliceOp>(op)) {
}
else if (auto extractSliceOp = dyn_cast<tensor::ExtractSliceOp>(op)) {
auto producerOp = extractSliceOp->getOperand(0).getDefiningOp();
if (producerOp) {
// Skip extractSliceOp if producer is constant weights (ONNXConstantOp)
if (llvm::isa<ONNXConstantOp>(producerOp)) {
if (llvm::isa<ONNXConstantOp>(producerOp))
continue;
}
// If produced by tosa::ReshapeOp (i.e. it is a bias tile) connect
// directly to its user, which is not a ComputeOp argument.
if (llvm::isa<tosa::ReshapeOp>(producerOp)) {
@@ -268,16 +248,13 @@ void SpatialToGraphvizPass::runOnOperation() {
// Draw output node (use the return Operation - argument number=0 - as nodeId)
auto returnOp = func.getBody().front().getTerminator();
os << '\t' << FORMAT_ARGUMENT(returnOp, 0)
<< " [label=\"Module Output\",color=green];\n";
os << '\t' << FORMAT_ARGUMENT(returnOp, 0) << " [label=\"Module Output\",color=green];\n";
os << "}\n";
}
} // namespace
std::unique_ptr<Pass> createSpatialToGraphvizPass() {
return std::make_unique<SpatialToGraphvizPass>();
}
std::unique_ptr<Pass> createSpatialToGraphvizPass() { return std::make_unique<SpatialToGraphvizPass>(); }
} // namespace onnx_mlir
} // namespace onnx_mlir