constant fold linalg.map (generated from tensor.pad for padding)
refactor pim helpers in PimCommon
This commit is contained in:
2
.gitignore
vendored
2
.gitignore
vendored
@@ -1,2 +1,4 @@
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.idea
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.idea
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.claude
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AGENTS.md
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build
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build
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@@ -20,7 +20,7 @@ add_onnx_mlir_library(OMPIMAccel
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Pass/CountInstructionPass.cpp
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Pass/CountInstructionPass.cpp
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Pass/EmitPimJsonPass.cpp
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Pass/EmitPimJsonPass.cpp
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Pass/MessagePass.cpp
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Pass/MessagePass.cpp
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Pass/PimFoldHostConstantsPass.cpp
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Pass/PimConstantFoldingPass.cpp
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Pass/PimHostVerificationPass.cpp
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Pass/PimHostVerificationPass.cpp
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EXCLUDE_FROM_OM_LIBS
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EXCLUDE_FROM_OM_LIBS
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@@ -12,7 +12,15 @@ using namespace mlir;
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namespace onnx_mlir {
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namespace onnx_mlir {
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std::string getOutputDir() { return outputBaseName.substr(0, outputBaseName.find_last_of('/')); }
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std::string getOutputDir() {
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if (outputBaseName.empty() || outputBaseName == "-")
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return {};
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size_t lastSlash = outputBaseName.find_last_of('/');
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if (lastSlash == std::string::npos)
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return ".";
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return outputBaseName.substr(0, lastSlash);
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}
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void createDirectory(const std::string& directory) {
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void createDirectory(const std::string& directory) {
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std::error_code errorCode;
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std::error_code errorCode;
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@@ -21,7 +29,11 @@ void createDirectory(const std::string& directory) {
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}
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}
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void dumpModule(ModuleOp moduleOp, const std::string& name) {
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void dumpModule(ModuleOp moduleOp, const std::string& name) {
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std::string dialectsDir = getOutputDir() + "/dialects";
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std::string outputDir = getOutputDir();
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if (outputDir.empty())
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return;
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std::string dialectsDir = outputDir + "/dialects";
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createDirectory(dialectsDir);
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createDirectory(dialectsDir);
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std::fstream file(dialectsDir + "/" + name + ".mlir", std::ios::out);
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std::fstream file(dialectsDir + "/" + name + ".mlir", std::ios::out);
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@@ -143,4 +155,85 @@ FailureOr<Operation*> getOtherEndOfChannel(Operation* op, bool opIsReceive, Rewr
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}
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}
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}
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}
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SmallVector<int64_t> computeRowMajorStrides(ArrayRef<int64_t> shape) {
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SmallVector<int64_t> strides(shape.size(), 1);
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for (int64_t dim = static_cast<int64_t>(shape.size()) - 2; dim >= 0; --dim)
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strides[dim] = strides[dim + 1] * shape[dim + 1];
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return strides;
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}
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SmallVector<int64_t> delinearizeIndex(int64_t linearIndex, ArrayRef<int64_t> shape, ArrayRef<int64_t> strides) {
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SmallVector<int64_t> indices(shape.size(), 0);
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for (auto [dim, stride] : llvm::enumerate(strides)) {
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indices[dim] = linearIndex / stride;
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linearIndex %= stride;
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}
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return indices;
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}
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int64_t linearizeIndex(ArrayRef<int64_t> indices, ArrayRef<int64_t> strides) {
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int64_t linearIndex = 0;
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for (auto [index, stride] : llvm::zip_equal(indices, strides))
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linearIndex += index * stride;
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return linearIndex;
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}
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int64_t getNumElements(ArrayRef<int64_t> shape) {
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int64_t numElements = 1;
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for (int64_t dim : shape)
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numElements *= dim;
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return numElements;
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}
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bool isMemoryContiguous(ArrayRef<int64_t> srcShape,
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ArrayRef<int64_t> offsets,
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ArrayRef<int64_t> sizes,
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ArrayRef<int64_t> strides) {
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if (std::any_of(strides.begin(), strides.end(), [](int64_t stride) -> bool { return stride != 1; }))
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return false;
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auto offsetsAndSizesAndShape = llvm::zip_equal(llvm::make_range(offsets.rbegin(), offsets.rend()),
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llvm::make_range(sizes.rbegin(), sizes.rend()),
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llvm::make_range(srcShape.rbegin(), srcShape.rend()));
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auto firstNonZeroOffset = std::find_if(
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offsetsAndSizesAndShape.begin(), offsetsAndSizesAndShape.end(), [&](auto offsetAndSizeAndShape) -> bool {
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auto [offset, _size, _dimension] = offsetAndSizeAndShape;
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return offset != 0;
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});
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if (firstNonZeroOffset != offsetsAndSizesAndShape.end()) {
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auto [offset, size, dimension] = *firstNonZeroOffset;
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if (size > dimension - offset)
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return false;
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++firstNonZeroOffset;
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if (std::any_of(firstNonZeroOffset, offsetsAndSizesAndShape.end(), [](auto offsetAndSizeAndShape) -> bool {
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auto [_offset, size, _dimension] = offsetAndSizeAndShape;
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return size != 1;
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}))
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return false;
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}
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auto sizesAndShape = llvm::zip_equal(llvm::make_range(sizes.rbegin(), sizes.rend()),
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llvm::make_range(srcShape.rbegin(), srcShape.rend()));
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auto firstDifferentSize = std::find_if(sizesAndShape.begin(), sizesAndShape.end(), [&](auto sizeAndShape) -> bool {
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auto [size, dimension] = sizeAndShape;
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return size != dimension;
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});
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if (firstDifferentSize != sizesAndShape.end()) {
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++firstDifferentSize;
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if (std::any_of(firstDifferentSize, sizesAndShape.end(), [](auto sizeAndShape) -> bool {
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auto [size, _dimension] = sizeAndShape;
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return size != 1;
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}))
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return false;
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}
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return true;
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}
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} // namespace onnx_mlir
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} // namespace onnx_mlir
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@@ -6,6 +6,8 @@
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/IR/Value.h"
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#include "mlir/IR/Value.h"
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#include "llvm/ADT/ArrayRef.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/ADT/StringRef.h"
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#include "llvm/ADT/StringRef.h"
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#include "src/Compiler/CompilerOptions.hpp"
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#include "src/Compiler/CompilerOptions.hpp"
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@@ -32,4 +34,18 @@ mlir::memref::GlobalOp lookupGlobalForGetGlobal(mlir::ModuleOp moduleOp, mlir::m
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llvm::FailureOr<mlir::Operation*>
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llvm::FailureOr<mlir::Operation*>
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getOtherEndOfChannel(mlir::Operation* op, bool opIsReceive, mlir::RewriterBase& rewriter);
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getOtherEndOfChannel(mlir::Operation* op, bool opIsReceive, mlir::RewriterBase& rewriter);
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llvm::SmallVector<int64_t> computeRowMajorStrides(llvm::ArrayRef<int64_t> shape);
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llvm::SmallVector<int64_t>
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delinearizeIndex(int64_t linearIndex, llvm::ArrayRef<int64_t> shape, llvm::ArrayRef<int64_t> strides);
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int64_t linearizeIndex(llvm::ArrayRef<int64_t> indices, llvm::ArrayRef<int64_t> strides);
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int64_t getNumElements(llvm::ArrayRef<int64_t> shape);
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bool isMemoryContiguous(llvm::ArrayRef<int64_t> srcShape,
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llvm::ArrayRef<int64_t> offsets,
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llvm::ArrayRef<int64_t> sizes,
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llvm::ArrayRef<int64_t> strides);
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} // namespace onnx_mlir
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} // namespace onnx_mlir
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@@ -15,7 +15,6 @@
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#include "Common/PimCommon.hpp"
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#include "Common/PimCommon.hpp"
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#include "Conversion/ONNXToSpatial/ONNXToSpatialCommon.hpp"
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#include "Conversion/ONNXToSpatial/ONNXToSpatialCommon.hpp"
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#include "Conversion/SpatialToPim/SpatialToPimCommon.hpp"
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#include "src/Accelerators/PIM/Compiler/PimCodeGen.hpp"
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#include "src/Accelerators/PIM/Compiler/PimCodeGen.hpp"
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#include "src/Accelerators/PIM/Compiler/PimCompilerOptions.hpp"
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#include "src/Accelerators/PIM/Compiler/PimCompilerOptions.hpp"
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#include "src/Accelerators/PIM/Dialect/Pim/PimOps.hpp"
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#include "src/Accelerators/PIM/Dialect/Pim/PimOps.hpp"
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@@ -382,12 +381,9 @@ void PimCodeGen::codeGenTransposeOp(pim::PimTransposeOp transposeOp) const {
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size_t elementSize = srcType.getElementTypeBitWidth() / 8;
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size_t elementSize = srcType.getElementTypeBitWidth() / 8;
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size_t totalElements = srcType.getNumElements();
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size_t totalElements = srcType.getNumElements();
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// Read permutation and compute its inverse
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// Read permutation. Destination dim i corresponds to source dim perm[i].
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SmallVector<int64_t> perm =
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SmallVector<int64_t> perm =
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map_to_vector(transposeOp.getPerms().getAsRange<IntegerAttr>(), [](auto attr) -> int64_t { return attr.getInt(); });
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map_to_vector(transposeOp.getPerms().getAsRange<IntegerAttr>(), [](auto attr) -> int64_t { return attr.getInt(); });
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SmallVector<int64_t> permInv(rank);
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for (size_t i = 0; i < rank; i++)
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permInv[perm[i]] = i;
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// Destination shape: dstShape[i] = srcShape[perm[i]]
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// Destination shape: dstShape[i] = srcShape[perm[i]]
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SmallVector<int64_t> dstShape(rank);
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SmallVector<int64_t> dstShape(rank);
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@@ -412,10 +408,10 @@ void PimCodeGen::codeGenTransposeOp(pim::PimTransposeOp transposeOp) const {
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remaining %= srcStrides[d];
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remaining %= srcStrides[d];
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}
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}
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// Compute flat destination index: dstIdx[d] = srcIdx[permInv[d]]
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// Compute flat destination index: dstIdx[d] = srcIdx[perm[d]]
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size_t dstFlat = 0;
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size_t dstFlat = 0;
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for (size_t d = 0; d < rank; d++)
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for (size_t d = 0; d < rank; d++)
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dstFlat += srcIdx[permInv[d]] * dstStrides[d];
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dstFlat += srcIdx[perm[d]] * dstStrides[d];
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emitMemCopyOp("lmv", dstAddr, dstFlat * elementSize, srcAddr, srcFlat * elementSize, elementSize, "len");
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emitMemCopyOp("lmv", dstAddr, dstFlat * elementSize, srcAddr, srcFlat * elementSize, elementSize, "len");
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}
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}
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@@ -46,8 +46,8 @@ void addPassesPim(OwningOpRef<ModuleOp>& module,
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}
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}
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if (pimEmissionTarget >= EmitPimCodegen) {
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if (pimEmissionTarget >= EmitPimCodegen) {
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pm.addPass(createPimFoldHostConstantsPass());
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pm.addPass(createPimConstantFoldingPass());
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pm.addPass(createMessagePass("Pim host constants folded"));
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pm.addPass(createMessagePass("Pim constants folded"));
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pm.addPass(createPimHostVerificationPass());
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pm.addPass(createPimHostVerificationPass());
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pm.addPass(createMessagePass("Pim host verified"));
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pm.addPass(createMessagePass("Pim host verified"));
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pm.addPass(createEmitPimJsonPass());
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pm.addPass(createEmitPimJsonPass());
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@@ -54,7 +54,7 @@ size_t getSliceActualOffset(tensor::ExtractSliceOp& sliceOp, ShapedType& inputSh
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return returnValue;
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return returnValue;
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}
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}
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Operation* getEarliestUserWithinBlock(Value value) {
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Operation* getEarliestUserWithinBlock(mlir::Value value) {
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auto users = value.getUsers();
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auto users = value.getUsers();
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assert(!users.empty());
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assert(!users.empty());
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@@ -67,23 +67,24 @@ Operation* getEarliestUserWithinBlock(Value value) {
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return earliestUser;
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return earliestUser;
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}
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}
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SmallVector<Value> getOpOperandsSortedByUses(Operation* operation) {
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SmallVector<mlir::Value> getOpOperandsSortedByUses(Operation* operation) {
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auto operandsAndUses = map_to_vector(operation->getOperands(), [](Value operand) -> std::pair<Value, size_t> {
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auto operandsAndUses =
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map_to_vector(operation->getOperands(), [](mlir::Value operand) -> std::pair<mlir::Value, size_t> {
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return {operand, std::distance(operand.use_begin(), operand.use_end())};
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return {operand, std::distance(operand.use_begin(), operand.use_end())};
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});
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});
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sort(operandsAndUses, [](auto a, auto b) { return a.second < b.second; });
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sort(operandsAndUses, [](auto a, auto b) { return a.second < b.second; });
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return map_to_vector(operandsAndUses, [](auto operandAndUse) { return operandAndUse.first; });
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return map_to_vector(operandsAndUses, [](auto operandAndUse) { return operandAndUse.first; });
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}
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}
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Value getBestOutputTensorFromOperandsOrAllocate(PatternRewriter& rewriter, Operation* operation) {
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mlir::Value getBestOutputTensorFromOperandsOrAllocate(PatternRewriter& rewriter, Operation* operation) {
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assert("Only support operations with a single result" && operation->getNumResults() == 1);
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assert("Only support operations with a single result" && operation->getNumResults() == 1);
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Value result = operation->getResult(0);
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mlir::Value result = operation->getResult(0);
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auto resultType = result.getType();
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auto resultType = result.getType();
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assert("Only support result ShapedType as result type" && isa<ShapedType>(resultType));
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assert("Only support result ShapedType as result type" && isa<ShapedType>(resultType));
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SmallVector<Value> operands = getOpOperandsSortedByUses(operation);
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SmallVector<mlir::Value> operands = getOpOperandsSortedByUses(operation);
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auto validOperands =
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auto validOperands =
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make_filter_range(operands, [resultType](Value operand) { return operand.getType() == resultType; });
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make_filter_range(operands, [resultType](mlir::Value operand) { return operand.getType() == resultType; });
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auto bestOperand = validOperands.begin();
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auto bestOperand = validOperands.begin();
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if (bestOperand != validOperands.end())
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if (bestOperand != validOperands.end())
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@@ -2,6 +2,7 @@
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#include "mlir/Dialect/Tensor/IR/Tensor.h"
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#include "mlir/Dialect/Tensor/IR/Tensor.h"
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#include "src/Accelerators/PIM/Common/PimCommon.hpp"
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#include "src/Accelerators/PIM/Dialect/Spatial/SpatialOps.hpp"
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#include "src/Accelerators/PIM/Dialect/Spatial/SpatialOps.hpp"
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namespace onnx_mlir {
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namespace onnx_mlir {
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@@ -39,71 +40,13 @@ mlir::SmallVector<mlir::Value> getOpOperandsSortedByUses(mlir::Operation* operat
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mlir::Value getBestOutputTensorFromOperandsOrAllocate(mlir::PatternRewriter& rewriter, mlir::Operation* operation);
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mlir::Value getBestOutputTensorFromOperandsOrAllocate(mlir::PatternRewriter& rewriter, mlir::Operation* operation);
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static bool isMemoryContiguous(const mlir::ArrayRef<int64_t> srcShape,
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const mlir::ArrayRef<int64_t> offsets,
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const mlir::ArrayRef<int64_t> sizes,
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const mlir::ArrayRef<int64_t> strides) {
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// Check that all strides are 1
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if (std::any_of(strides.begin(), strides.end(), [](int64_t stride) -> bool { return stride != 1; }))
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return false;
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// Check offsets from right to left:
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// The first offset_n at position n different from 0:
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// - limits all sizes to the left to 1
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// - limits size_n to dimension_n - offset_n
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auto offsetsAndSizesAndShape = llvm::zip_equal(llvm::make_range(offsets.rbegin(), offsets.rend()),
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llvm::make_range(sizes.rbegin(), sizes.rend()),
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llvm::make_range(srcShape.rbegin(), srcShape.rend()));
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auto firstNonZeroOffset = std::find_if(
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offsetsAndSizesAndShape.begin(), offsetsAndSizesAndShape.end(), [&](auto offsetAndSizeAndShape) -> bool {
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auto [offset, _size, _dimension] = offsetAndSizeAndShape;
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return offset != 0;
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});
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if (firstNonZeroOffset != offsetsAndSizesAndShape.end()) {
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auto [offset, size, dimension] = *firstNonZeroOffset;
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if (size > dimension - offset)
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return false;
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++firstNonZeroOffset;
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if (std::any_of(firstNonZeroOffset, offsetsAndSizesAndShape.end(), [](auto offsetAndSizeAndShape) -> bool {
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auto [_offset, size, _dimension] = offsetAndSizeAndShape;
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return size != 1;
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}))
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return false;
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}
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// Check sizes from right to left:
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// The first size_n at position n different from shape_n limits all sizes to the left to 1
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auto sizesAndShape = llvm::zip_equal(llvm::make_range(sizes.rbegin(), sizes.rend()),
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llvm::make_range(srcShape.rbegin(), srcShape.rend()));
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auto firstDifferentSize = std::find_if(sizesAndShape.begin(), sizesAndShape.end(), [&](auto sizeAndShape) -> bool {
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auto [size, dimension] = sizeAndShape;
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return size != dimension;
|
|
||||||
});
|
|
||||||
|
|
||||||
if (firstDifferentSize != sizesAndShape.end()) {
|
|
||||||
++firstDifferentSize;
|
|
||||||
|
|
||||||
if (std::any_of(firstDifferentSize, sizesAndShape.end(), [](auto sizeAndShape) -> bool {
|
|
||||||
auto [size, _] = sizeAndShape;
|
|
||||||
return size != 1;
|
|
||||||
}))
|
|
||||||
return false;
|
|
||||||
}
|
|
||||||
|
|
||||||
return true;
|
|
||||||
}
|
|
||||||
|
|
||||||
inline mlir::tensor::EmptyOp
|
inline mlir::tensor::EmptyOp
|
||||||
createEmptyTensorFromShaped(mlir::IRRewriter& rewriter, mlir::Location loc, mlir::ShapedType shapedType) {
|
createEmptyTensorFromShaped(mlir::IRRewriter& rewriter, mlir::Location loc, mlir::ShapedType shapedType) {
|
||||||
return mlir::tensor::EmptyOp::create(rewriter, loc, shapedType.getShape(), shapedType.getElementType());
|
return mlir::tensor::EmptyOp::create(rewriter, loc, shapedType.getShape(), shapedType.getElementType());
|
||||||
}
|
}
|
||||||
|
|
||||||
inline bool isAConcatOp(mlir::Operation* op) {
|
inline bool isAConcatOp(mlir::Operation* op) {
|
||||||
return isa<mlir::tensor::ConcatOp>(op) || isa<spatial::SpatImgConcatOp>(op);
|
return llvm::isa<mlir::tensor::ConcatOp>(op) || llvm::isa<spatial::SpatImgConcatOp>(op);
|
||||||
}
|
}
|
||||||
|
|
||||||
} // namespace onnx_mlir
|
} // namespace onnx_mlir
|
||||||
|
|||||||
@@ -129,7 +129,7 @@ void SpatialToPimPass::runOnOperation() {
|
|||||||
}
|
}
|
||||||
|
|
||||||
// Dump to file for debug
|
// Dump to file for debug
|
||||||
dumpModule(moduleOp, "pim");
|
dumpModule(moduleOp, "pim0");
|
||||||
}
|
}
|
||||||
|
|
||||||
void SpatialToPimPass::runOnComputeOp(spatial::SpatWeightedCompute computeOp, IRRewriter& rewriter) {
|
void SpatialToPimPass::runOnComputeOp(spatial::SpatWeightedCompute computeOp, IRRewriter& rewriter) {
|
||||||
|
|||||||
@@ -89,7 +89,7 @@ void PimBufferizationPass::runOnOperation() {
|
|||||||
annotateWeightsMemrefs(moduleOp, funcOp);
|
annotateWeightsMemrefs(moduleOp, funcOp);
|
||||||
|
|
||||||
// Dump to file for debug
|
// Dump to file for debug
|
||||||
dumpModule(moduleOp, "pim_buf");
|
dumpModule(moduleOp, "pim1_buff");
|
||||||
}
|
}
|
||||||
|
|
||||||
void PimBufferizationPass::annotateWeightsMemrefs(ModuleOp moduleOp, func::FuncOp funcOp) const {
|
void PimBufferizationPass::annotateWeightsMemrefs(ModuleOp moduleOp, func::FuncOp funcOp) const {
|
||||||
|
|||||||
618
src/PIM/Pass/PimConstantFoldingPass.cpp
Normal file
618
src/PIM/Pass/PimConstantFoldingPass.cpp
Normal file
@@ -0,0 +1,618 @@
|
|||||||
|
#include "mlir/Dialect/Linalg/IR/Linalg.h"
|
||||||
|
#include "mlir/Dialect/MemRef/IR/MemRef.h"
|
||||||
|
#include "mlir/IR/BuiltinAttributes.h"
|
||||||
|
#include "mlir/IR/BuiltinTypes.h"
|
||||||
|
#include "mlir/IR/MLIRContext.h"
|
||||||
|
#include "mlir/IR/Matchers.h"
|
||||||
|
#include "mlir/IR/PatternMatch.h"
|
||||||
|
#include "mlir/Pass/Pass.h"
|
||||||
|
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
|
||||||
|
|
||||||
|
#include "llvm/ADT/STLExtras.h"
|
||||||
|
#include "llvm/ADT/SmallBitVector.h"
|
||||||
|
#include "llvm/ADT/SmallPtrSet.h"
|
||||||
|
#include "llvm/ADT/SmallVector.h"
|
||||||
|
|
||||||
|
#include <memory>
|
||||||
|
|
||||||
|
#include "src/Accelerators/PIM/Common/PimCommon.hpp"
|
||||||
|
#include "src/Accelerators/PIM/Dialect/Pim/PimOps.hpp"
|
||||||
|
|
||||||
|
using namespace mlir;
|
||||||
|
|
||||||
|
namespace onnx_mlir {
|
||||||
|
|
||||||
|
namespace {
|
||||||
|
|
||||||
|
static Value stripMemRefCasts(Value value) {
|
||||||
|
while (auto castOp = value.getDefiningOp<memref::CastOp>())
|
||||||
|
value = castOp.getSource();
|
||||||
|
return value;
|
||||||
|
}
|
||||||
|
|
||||||
|
static memref::GlobalOp createFoldedGlobal(ModuleOp moduleOp,
|
||||||
|
Location loc,
|
||||||
|
MemRefType globalType,
|
||||||
|
DenseElementsAttr denseAttr,
|
||||||
|
StringRef nameStem,
|
||||||
|
IntegerAttr alignment = {}) {
|
||||||
|
auto globalName = nameStem.str();
|
||||||
|
unsigned suffix = 0;
|
||||||
|
while (moduleOp.lookupSymbol(globalName))
|
||||||
|
globalName = (nameStem + "_" + std::to_string(++suffix)).str();
|
||||||
|
|
||||||
|
auto visibility = StringAttr::get(moduleOp.getContext(), "private");
|
||||||
|
OpBuilder moduleBuilder(moduleOp.getBodyRegion());
|
||||||
|
moduleBuilder.setInsertionPointToStart(moduleOp.getBody());
|
||||||
|
return memref::GlobalOp::create(moduleBuilder,
|
||||||
|
loc,
|
||||||
|
globalName,
|
||||||
|
visibility,
|
||||||
|
globalType,
|
||||||
|
denseAttr,
|
||||||
|
/*constant=*/true,
|
||||||
|
alignment);
|
||||||
|
}
|
||||||
|
|
||||||
|
static FailureOr<DenseElementsAttr> getDenseGlobalValue(ModuleOp moduleOp, Value value) {
|
||||||
|
value = stripMemRefCasts(value);
|
||||||
|
|
||||||
|
auto getGlobalOp = value.getDefiningOp<memref::GetGlobalOp>();
|
||||||
|
if (!getGlobalOp)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
|
||||||
|
if (!globalOp || !globalOp.getConstant() || !globalOp.getInitialValue())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto denseAttr = dyn_cast<DenseElementsAttr>(*globalOp.getInitialValue());
|
||||||
|
if (!denseAttr)
|
||||||
|
return failure();
|
||||||
|
return denseAttr;
|
||||||
|
}
|
||||||
|
|
||||||
|
static FailureOr<DenseElementsAttr> transposeDenseElements(DenseElementsAttr denseAttr, ArrayRef<int64_t> perms) {
|
||||||
|
auto tensorType = dyn_cast<RankedTensorType>(denseAttr.getType());
|
||||||
|
if (!tensorType)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
int64_t rank = tensorType.getRank();
|
||||||
|
if (static_cast<int64_t>(perms.size()) != rank)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
llvm::SmallBitVector seen(rank);
|
||||||
|
SmallVector<int64_t> transposedShape;
|
||||||
|
transposedShape.reserve(rank);
|
||||||
|
for (int64_t perm : perms) {
|
||||||
|
if (perm < 0 || perm >= rank || seen.test(perm))
|
||||||
|
return failure();
|
||||||
|
seen.set(perm);
|
||||||
|
transposedShape.push_back(tensorType.getShape()[perm]);
|
||||||
|
}
|
||||||
|
|
||||||
|
auto transposedType = RankedTensorType::get(transposedShape, tensorType.getElementType());
|
||||||
|
if (denseAttr.isSplat())
|
||||||
|
return DenseElementsAttr::get(transposedType, denseAttr.getSplatValue<Attribute>());
|
||||||
|
|
||||||
|
SmallVector<Attribute> originalValues(denseAttr.getValues<Attribute>());
|
||||||
|
SmallVector<Attribute> transposedValues(originalValues.size());
|
||||||
|
|
||||||
|
SmallVector<int64_t> originalStrides(rank, 1);
|
||||||
|
SmallVector<int64_t> transposedStrides(rank, 1);
|
||||||
|
for (int64_t dim = rank - 2; dim >= 0; --dim) {
|
||||||
|
originalStrides[dim] = originalStrides[dim + 1] * tensorType.getShape()[dim + 1];
|
||||||
|
transposedStrides[dim] = transposedStrides[dim + 1] * transposedShape[dim + 1];
|
||||||
|
}
|
||||||
|
|
||||||
|
SmallVector<int64_t> originalIndices(rank);
|
||||||
|
SmallVector<int64_t> transposedIndices(rank);
|
||||||
|
for (auto [linearIndex, value] : llvm::enumerate(originalValues)) {
|
||||||
|
int64_t remaining = static_cast<int64_t>(linearIndex);
|
||||||
|
for (int64_t dim = 0; dim < rank; ++dim) {
|
||||||
|
originalIndices[dim] = remaining / originalStrides[dim];
|
||||||
|
remaining %= originalStrides[dim];
|
||||||
|
}
|
||||||
|
|
||||||
|
for (int64_t dim = 0; dim < rank; ++dim)
|
||||||
|
transposedIndices[dim] = originalIndices[perms[dim]];
|
||||||
|
|
||||||
|
int64_t transposedLinearIndex = 0;
|
||||||
|
for (int64_t dim = 0; dim < rank; ++dim)
|
||||||
|
transposedLinearIndex += transposedIndices[dim] * transposedStrides[dim];
|
||||||
|
|
||||||
|
transposedValues[transposedLinearIndex] = value;
|
||||||
|
}
|
||||||
|
|
||||||
|
return DenseElementsAttr::get(transposedType, transposedValues);
|
||||||
|
}
|
||||||
|
|
||||||
|
struct ConstantSubviewCopy {
|
||||||
|
DenseElementsAttr source;
|
||||||
|
SmallVector<int64_t> offsets;
|
||||||
|
SmallVector<int64_t> strides;
|
||||||
|
Operation* copyOp = nullptr;
|
||||||
|
};
|
||||||
|
|
||||||
|
static FailureOr<Attribute> getConstantMapYield(linalg::MapOp mapOp) {
|
||||||
|
if (!mapOp.getInputs().empty())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto yieldOp = dyn_cast<linalg::YieldOp>(mapOp.getMapper().front().getTerminator());
|
||||||
|
if (!yieldOp || yieldOp.getNumOperands() != 1)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
Attribute attr;
|
||||||
|
if (!matchPattern(yieldOp.getValues().front(), m_Constant(&attr)))
|
||||||
|
return failure();
|
||||||
|
return attr;
|
||||||
|
}
|
||||||
|
|
||||||
|
struct FoldConstantCoreMapPattern final : OpRewritePattern<linalg::MapOp> {
|
||||||
|
using OpRewritePattern::OpRewritePattern;
|
||||||
|
|
||||||
|
LogicalResult matchAndRewrite(linalg::MapOp mapOp, PatternRewriter& rewriter) const override {
|
||||||
|
auto coreOp = mapOp->getParentOfType<pim::PimCoreOp>();
|
||||||
|
if (!coreOp)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto initType = dyn_cast<MemRefType>(mapOp.getInit().getType());
|
||||||
|
if (!initType || !initType.hasStaticShape())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto fillValue = getConstantMapYield(mapOp);
|
||||||
|
if (failed(fillValue))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto tensorType = RankedTensorType::get(initType.getShape(), initType.getElementType());
|
||||||
|
DenseElementsAttr splatAttr = DenseElementsAttr::get(tensorType, *fillValue);
|
||||||
|
|
||||||
|
auto moduleOp = mapOp->getParentOfType<ModuleOp>();
|
||||||
|
if (!moduleOp)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto globalOp = createFoldedGlobal(moduleOp, mapOp.getLoc(), initType, splatAttr, "pim_core_fill");
|
||||||
|
|
||||||
|
OpBuilder::InsertionGuard guard(rewriter);
|
||||||
|
rewriter.setInsertionPoint(coreOp);
|
||||||
|
auto getGlobalOp = memref::GetGlobalOp::create(rewriter, mapOp.getLoc(), initType, globalOp.getName());
|
||||||
|
|
||||||
|
size_t elementByteWidth = initType.getElementTypeBitWidth() / 8;
|
||||||
|
if (elementByteWidth == 0)
|
||||||
|
return failure();
|
||||||
|
size_t totalBytes = initType.getNumElements() * elementByteWidth;
|
||||||
|
|
||||||
|
rewriter.setInsertionPoint(mapOp);
|
||||||
|
pim::PimMemCopyHostToDevOp::create(rewriter,
|
||||||
|
mapOp.getLoc(),
|
||||||
|
initType,
|
||||||
|
mapOp.getInit(),
|
||||||
|
getGlobalOp.getResult(),
|
||||||
|
rewriter.getI32IntegerAttr(0),
|
||||||
|
rewriter.getI32IntegerAttr(0),
|
||||||
|
rewriter.getI32IntegerAttr(static_cast<int32_t>(totalBytes)));
|
||||||
|
rewriter.eraseOp(mapOp);
|
||||||
|
return success();
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
struct StaticSubviewInfo {
|
||||||
|
Value source;
|
||||||
|
SmallVector<int64_t> sourceShape;
|
||||||
|
SmallVector<int64_t> offsets;
|
||||||
|
SmallVector<int64_t> sizes;
|
||||||
|
SmallVector<int64_t> strides;
|
||||||
|
};
|
||||||
|
|
||||||
|
static FailureOr<StaticSubviewInfo> getStaticSubviewInfo(Value value) {
|
||||||
|
auto subviewOp = value.getDefiningOp<memref::SubViewOp>();
|
||||||
|
if (!subviewOp)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto source = stripMemRefCasts(subviewOp.getSource());
|
||||||
|
auto sourceType = dyn_cast<MemRefType>(source.getType());
|
||||||
|
auto subviewType = dyn_cast<MemRefType>(subviewOp.getType());
|
||||||
|
if (!sourceType || !subviewType || !sourceType.hasStaticShape() || !subviewType.hasStaticShape())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
StaticSubviewInfo info;
|
||||||
|
info.source = source;
|
||||||
|
info.sourceShape.assign(sourceType.getShape().begin(), sourceType.getShape().end());
|
||||||
|
for (OpFoldResult offset : subviewOp.getMixedOffsets()) {
|
||||||
|
auto staticOffset = getConstantIntValue(offset);
|
||||||
|
if (!staticOffset)
|
||||||
|
return failure();
|
||||||
|
info.offsets.push_back(*staticOffset);
|
||||||
|
}
|
||||||
|
for (OpFoldResult size : subviewOp.getMixedSizes()) {
|
||||||
|
auto staticSize = getConstantIntValue(size);
|
||||||
|
if (!staticSize)
|
||||||
|
return failure();
|
||||||
|
info.sizes.push_back(*staticSize);
|
||||||
|
}
|
||||||
|
for (OpFoldResult stride : subviewOp.getMixedStrides()) {
|
||||||
|
auto staticStride = getConstantIntValue(stride);
|
||||||
|
if (!staticStride)
|
||||||
|
return failure();
|
||||||
|
info.strides.push_back(*staticStride);
|
||||||
|
}
|
||||||
|
return info;
|
||||||
|
}
|
||||||
|
|
||||||
|
static int64_t
|
||||||
|
getSubviewChunkOffsetBytes(const StaticSubviewInfo& info, ArrayRef<int64_t> outerIndices, int64_t elementByteWidth) {
|
||||||
|
SmallVector<int64_t> sourceIndices;
|
||||||
|
sourceIndices.reserve(info.sourceShape.size());
|
||||||
|
for (size_t dim = 0; dim + 1 < info.sourceShape.size(); ++dim)
|
||||||
|
sourceIndices.push_back(info.offsets[dim] + outerIndices[dim] * info.strides[dim]);
|
||||||
|
sourceIndices.push_back(info.offsets.back());
|
||||||
|
return linearizeIndex(sourceIndices, computeRowMajorStrides(info.sourceShape)) * elementByteWidth;
|
||||||
|
}
|
||||||
|
|
||||||
|
struct RewriteCoreSubviewCopyPattern final : OpRewritePattern<pim::PimMemCopyOp> {
|
||||||
|
using OpRewritePattern::OpRewritePattern;
|
||||||
|
|
||||||
|
LogicalResult matchAndRewrite(pim::PimMemCopyOp copyOp, PatternRewriter& rewriter) const override {
|
||||||
|
if (!copyOp->getParentOfType<pim::PimCoreOp>())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto srcSubview = getStaticSubviewInfo(copyOp.getSrc());
|
||||||
|
auto dstSubview = getStaticSubviewInfo(copyOp.getDst());
|
||||||
|
const bool splitSrc = succeeded(srcSubview)
|
||||||
|
&& !isMemoryContiguous(srcSubview->sourceShape, srcSubview->offsets, srcSubview->sizes, srcSubview->strides);
|
||||||
|
const bool splitDst = succeeded(dstSubview)
|
||||||
|
&& !isMemoryContiguous(dstSubview->sourceShape, dstSubview->offsets, dstSubview->sizes, dstSubview->strides);
|
||||||
|
if (!splitSrc && !splitDst)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto sourceType = dyn_cast<MemRefType>(copyOp.getSrc().getType());
|
||||||
|
auto dstType = dyn_cast<MemRefType>(copyOp.getDst().getType());
|
||||||
|
if (!sourceType || !dstType || !sourceType.hasStaticShape() || !dstType.hasStaticShape())
|
||||||
|
return failure();
|
||||||
|
if (sourceType.getElementType() != dstType.getElementType())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
if (splitSrc && llvm::any_of(srcSubview->strides, [](int64_t stride) { return stride != 1; }))
|
||||||
|
return failure();
|
||||||
|
if (splitDst && llvm::any_of(dstSubview->strides, [](int64_t stride) { return stride != 1; }))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
ArrayRef<int64_t> copyShape = splitSrc ? ArrayRef<int64_t>(srcSubview->sizes) : ArrayRef<int64_t>(dstSubview->sizes);
|
||||||
|
if (splitSrc && splitDst && copyShape != ArrayRef<int64_t>(dstSubview->sizes))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
const int64_t elementByteWidth = sourceType.getElementTypeBitWidth() / 8;
|
||||||
|
if (elementByteWidth <= 0)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
const int64_t totalBytes = getNumElements(copyShape) * elementByteWidth;
|
||||||
|
if (copyOp.getSize() != totalBytes)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
const int64_t sliceBytes = copyShape.back() * elementByteWidth;
|
||||||
|
if (sliceBytes <= 0)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
SmallVector<int64_t> outerShape(copyShape.begin(), copyShape.end() - 1);
|
||||||
|
auto outerStrides = computeRowMajorStrides(outerShape);
|
||||||
|
const int64_t numSlices = outerShape.empty() ? 1 : getNumElements(outerShape);
|
||||||
|
|
||||||
|
rewriter.setInsertionPoint(copyOp);
|
||||||
|
for (int64_t linearIndex = 0; linearIndex < numSlices; ++linearIndex) {
|
||||||
|
SmallVector<int64_t> outerIndices =
|
||||||
|
outerShape.empty() ? SmallVector<int64_t>{} : delinearizeIndex(linearIndex, outerShape, outerStrides);
|
||||||
|
const int64_t srcByteOffset = copyOp.getSrcOffset()
|
||||||
|
+ (splitSrc ? getSubviewChunkOffsetBytes(*srcSubview, outerIndices, elementByteWidth)
|
||||||
|
: linearIndex * sliceBytes);
|
||||||
|
const int64_t dstByteOffset = copyOp.getDstOffset()
|
||||||
|
+ (splitDst ? getSubviewChunkOffsetBytes(*dstSubview, outerIndices, elementByteWidth)
|
||||||
|
: linearIndex * sliceBytes);
|
||||||
|
pim::PimMemCopyOp::create(rewriter,
|
||||||
|
copyOp.getLoc(),
|
||||||
|
splitDst ? cast<MemRefType>(dstSubview->source.getType()) : dstType,
|
||||||
|
splitDst ? dstSubview->source : copyOp.getDst(),
|
||||||
|
splitSrc ? srcSubview->source : copyOp.getSrc(),
|
||||||
|
rewriter.getI32IntegerAttr(static_cast<int32_t>(dstByteOffset)),
|
||||||
|
rewriter.getI32IntegerAttr(static_cast<int32_t>(srcByteOffset)),
|
||||||
|
rewriter.getI32IntegerAttr(static_cast<int32_t>(sliceBytes)));
|
||||||
|
}
|
||||||
|
|
||||||
|
rewriter.replaceOp(copyOp, copyOp.getDst());
|
||||||
|
return success();
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
static FailureOr<DenseElementsAttr> foldConstantAlloc(memref::AllocOp allocOp, ModuleOp moduleOp) {
|
||||||
|
auto allocType = dyn_cast<MemRefType>(allocOp.getType());
|
||||||
|
if (!allocType || !allocType.hasStaticShape())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto resultTensorType = RankedTensorType::get(allocType.getShape(), allocType.getElementType());
|
||||||
|
const int64_t numElements = resultTensorType.getNumElements();
|
||||||
|
if (numElements < 0)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
Attribute fillValue;
|
||||||
|
SmallVector<ConstantSubviewCopy> copies;
|
||||||
|
llvm::SmallPtrSet<Operation*, 8> visitedAliases;
|
||||||
|
SmallVector<Value> pendingAliases;
|
||||||
|
pendingAliases.push_back(allocOp.getResult());
|
||||||
|
|
||||||
|
while (!pendingAliases.empty()) {
|
||||||
|
Value alias = pendingAliases.pop_back_val();
|
||||||
|
for (Operation* user : alias.getUsers()) {
|
||||||
|
if (!visitedAliases.insert(user).second)
|
||||||
|
continue;
|
||||||
|
|
||||||
|
if (auto mapOp = dyn_cast<linalg::MapOp>(user)) {
|
||||||
|
if (mapOp.getInit() != alias)
|
||||||
|
return failure();
|
||||||
|
auto maybeFillValue = getConstantMapYield(mapOp);
|
||||||
|
if (failed(maybeFillValue))
|
||||||
|
return failure();
|
||||||
|
if (fillValue && fillValue != *maybeFillValue)
|
||||||
|
return failure();
|
||||||
|
fillValue = *maybeFillValue;
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
if (auto subviewOp = dyn_cast<memref::SubViewOp>(user)) {
|
||||||
|
SmallVector<int64_t> offsets;
|
||||||
|
SmallVector<int64_t> strides;
|
||||||
|
offsets.reserve(subviewOp.getMixedOffsets().size());
|
||||||
|
strides.reserve(subviewOp.getMixedStrides().size());
|
||||||
|
for (OpFoldResult offset : subviewOp.getMixedOffsets()) {
|
||||||
|
auto staticOffset = getConstantIntValue(offset);
|
||||||
|
if (!staticOffset)
|
||||||
|
return failure();
|
||||||
|
offsets.push_back(*staticOffset);
|
||||||
|
}
|
||||||
|
for (OpFoldResult stride : subviewOp.getMixedStrides()) {
|
||||||
|
auto staticStride = getConstantIntValue(stride);
|
||||||
|
if (!staticStride)
|
||||||
|
return failure();
|
||||||
|
strides.push_back(*staticStride);
|
||||||
|
}
|
||||||
|
|
||||||
|
for (Operation* subviewUser : subviewOp->getUsers()) {
|
||||||
|
if (auto copyOp = dyn_cast<memref::CopyOp>(subviewUser)) {
|
||||||
|
if (copyOp.getTarget() != subviewOp.getResult())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto denseAttr = getDenseGlobalValue(moduleOp, copyOp.getSource());
|
||||||
|
if (failed(denseAttr))
|
||||||
|
return failure();
|
||||||
|
copies.push_back({*denseAttr, offsets, strides, copyOp});
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
return failure();
|
||||||
|
}
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
if (isa<pim::PimCoreOp, memref::DeallocOp>(user))
|
||||||
|
continue;
|
||||||
|
|
||||||
|
if (auto castOp = dyn_cast<memref::CastOp>(user)) {
|
||||||
|
pendingAliases.push_back(castOp.getResult());
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
return failure();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!fillValue)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
SmallVector<Attribute> resultValues(numElements, fillValue);
|
||||||
|
auto resultStrides = computeRowMajorStrides(resultTensorType.getShape());
|
||||||
|
|
||||||
|
llvm::sort(copies, [](const ConstantSubviewCopy& lhs, const ConstantSubviewCopy& rhs) {
|
||||||
|
return lhs.copyOp->isBeforeInBlock(rhs.copyOp);
|
||||||
|
});
|
||||||
|
|
||||||
|
for (const ConstantSubviewCopy& copy : copies) {
|
||||||
|
auto sourceType = dyn_cast<RankedTensorType>(copy.source.getType());
|
||||||
|
if (!sourceType || !sourceType.hasStaticShape())
|
||||||
|
return failure();
|
||||||
|
if (sourceType.getRank() != static_cast<int64_t>(copy.offsets.size())
|
||||||
|
|| sourceType.getRank() != static_cast<int64_t>(copy.strides.size()))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto sourceStrides = computeRowMajorStrides(sourceType.getShape());
|
||||||
|
SmallVector<Attribute> sourceValues(copy.source.getValues<Attribute>());
|
||||||
|
for (auto [linearIndex, value] : llvm::enumerate(sourceValues)) {
|
||||||
|
SmallVector<int64_t> sourceIndices =
|
||||||
|
delinearizeIndex(static_cast<int64_t>(linearIndex), sourceType.getShape(), sourceStrides);
|
||||||
|
SmallVector<int64_t> resultIndices;
|
||||||
|
resultIndices.reserve(sourceIndices.size());
|
||||||
|
for (auto [offset, sourceIndex, stride] : llvm::zip_equal(copy.offsets, sourceIndices, copy.strides))
|
||||||
|
resultIndices.push_back(offset + sourceIndex * stride);
|
||||||
|
|
||||||
|
int64_t resultLinearIndex = linearizeIndex(resultIndices, resultStrides);
|
||||||
|
resultValues[resultLinearIndex] = value;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return DenseElementsAttr::get(resultTensorType, resultValues);
|
||||||
|
}
|
||||||
|
|
||||||
|
struct FoldConstantTransposePattern final : OpRewritePattern<pim::PimTransposeOp> {
|
||||||
|
using OpRewritePattern::OpRewritePattern;
|
||||||
|
|
||||||
|
LogicalResult matchAndRewrite(pim::PimTransposeOp transposeOp, PatternRewriter& rewriter) const override {
|
||||||
|
auto resultType = dyn_cast<MemRefType>(transposeOp.getOutRes().getType());
|
||||||
|
if (!resultType || !resultType.hasStaticShape())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto sourceGetGlobal = transposeOp.getData().getDefiningOp<memref::GetGlobalOp>();
|
||||||
|
if (!sourceGetGlobal)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto moduleOp = transposeOp->getParentOfType<ModuleOp>();
|
||||||
|
if (!moduleOp)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto sourceGlobal = lookupGlobalForGetGlobal(moduleOp, sourceGetGlobal);
|
||||||
|
if (!sourceGlobal || !sourceGlobal.getConstant() || !sourceGlobal.getInitialValue())
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto denseAttr = dyn_cast<DenseElementsAttr>(*sourceGlobal.getInitialValue());
|
||||||
|
if (!denseAttr)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
SmallVector<int64_t> perms;
|
||||||
|
perms.reserve(transposeOp.getPerms().size());
|
||||||
|
for (IntegerAttr attr : transposeOp.getPerms().getAsRange<IntegerAttr>())
|
||||||
|
perms.push_back(attr.getInt());
|
||||||
|
FailureOr<DenseElementsAttr> transposedAttr = transposeDenseElements(denseAttr, perms);
|
||||||
|
if (failed(transposedAttr))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto transposedShape = cast<RankedTensorType>(transposedAttr->getType()).getShape();
|
||||||
|
if (!llvm::equal(transposedShape, resultType.getShape()))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
MemRefType globalType = resultType;
|
||||||
|
|
||||||
|
auto newGlobal = createFoldedGlobal(moduleOp,
|
||||||
|
transposeOp.getLoc(),
|
||||||
|
globalType,
|
||||||
|
*transposedAttr,
|
||||||
|
sourceGlobal.getName().str() + "__folded_transpose",
|
||||||
|
sourceGlobal.getAlignmentAttr());
|
||||||
|
|
||||||
|
rewriter.setInsertionPoint(transposeOp);
|
||||||
|
auto newGetGlobal = memref::GetGlobalOp::create(rewriter, transposeOp.getLoc(), globalType, newGlobal.getName());
|
||||||
|
|
||||||
|
bool isAlwaysWeight =
|
||||||
|
!transposeOp->getUsers().empty()
|
||||||
|
&& llvm::all_of(transposeOp->getUsers(), [](Operation* user) { return isa<pim::PimCoreOp>(user); });
|
||||||
|
if (isAlwaysWeight) {
|
||||||
|
markWeightAlways(newGlobal);
|
||||||
|
markWeightAlways(newGetGlobal);
|
||||||
|
}
|
||||||
|
|
||||||
|
rewriter.replaceOp(transposeOp, newGetGlobal.getResult());
|
||||||
|
return success();
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
struct FoldConstantAllocPattern final : OpRewritePattern<memref::AllocOp> {
|
||||||
|
using OpRewritePattern::OpRewritePattern;
|
||||||
|
|
||||||
|
LogicalResult matchAndRewrite(memref::AllocOp allocOp, PatternRewriter& rewriter) const override {
|
||||||
|
auto moduleOp = allocOp->getParentOfType<ModuleOp>();
|
||||||
|
if (!moduleOp)
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto foldedAttr = foldConstantAlloc(allocOp, moduleOp);
|
||||||
|
if (failed(foldedAttr))
|
||||||
|
return failure();
|
||||||
|
|
||||||
|
auto allocType = cast<MemRefType>(allocOp.getType());
|
||||||
|
auto newGlobal = createFoldedGlobal(moduleOp, allocOp.getLoc(), allocType, *foldedAttr, "pim_folded_constant");
|
||||||
|
|
||||||
|
rewriter.setInsertionPoint(allocOp);
|
||||||
|
auto newGetGlobal = memref::GetGlobalOp::create(rewriter, allocOp.getLoc(), allocType, newGlobal.getName());
|
||||||
|
|
||||||
|
SmallVector<Operation*> opsToErase;
|
||||||
|
SmallVector<memref::CastOp> castsToReplace;
|
||||||
|
bool allLiveUsersAreCoreOps = true;
|
||||||
|
for (Operation* user : llvm::make_early_inc_range(allocOp->getUsers())) {
|
||||||
|
if (isa<linalg::MapOp, memref::SubViewOp, memref::DeallocOp>(user)) {
|
||||||
|
opsToErase.push_back(user);
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
if (auto castOp = dyn_cast<memref::CastOp>(user)) {
|
||||||
|
castsToReplace.push_back(castOp);
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!isa<pim::PimCoreOp>(user))
|
||||||
|
return failure();
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!llvm::all_of(castsToReplace, [](memref::CastOp castOp) {
|
||||||
|
return llvm::all_of(castOp->getUsers(), [](Operation* user) { return isa<pim::PimCoreOp>(user); });
|
||||||
|
})) {
|
||||||
|
allLiveUsersAreCoreOps = false;
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!llvm::all_of(allocOp->getUsers(), [](Operation* user) {
|
||||||
|
return isa<linalg::MapOp, memref::SubViewOp, memref::DeallocOp, memref::CastOp, pim::PimCoreOp>(user);
|
||||||
|
})) {
|
||||||
|
return failure();
|
||||||
|
}
|
||||||
|
|
||||||
|
if (allLiveUsersAreCoreOps) {
|
||||||
|
markWeightAlways(newGlobal);
|
||||||
|
markWeightAlways(newGetGlobal);
|
||||||
|
}
|
||||||
|
|
||||||
|
llvm::SmallPtrSet<Operation*, 8> preservedUsers(opsToErase.begin(), opsToErase.end());
|
||||||
|
for (memref::CastOp castOp : castsToReplace)
|
||||||
|
preservedUsers.insert(castOp);
|
||||||
|
rewriter.replaceAllUsesExcept(allocOp.getResult(), newGetGlobal.getResult(), preservedUsers);
|
||||||
|
|
||||||
|
for (memref::CastOp castOp : castsToReplace) {
|
||||||
|
rewriter.setInsertionPoint(castOp);
|
||||||
|
Value replacementCast = memref::CastOp::create(rewriter, castOp.getLoc(), castOp.getType(), newGetGlobal);
|
||||||
|
rewriter.replaceOp(castOp, replacementCast);
|
||||||
|
if (allLiveUsersAreCoreOps)
|
||||||
|
markWeightAlways(replacementCast.getDefiningOp());
|
||||||
|
}
|
||||||
|
|
||||||
|
for (Operation* op : llvm::make_early_inc_range(opsToErase)) {
|
||||||
|
if (auto subviewOp = dyn_cast<memref::SubViewOp>(op))
|
||||||
|
for (Operation* subviewUser : llvm::make_early_inc_range(subviewOp->getUsers()))
|
||||||
|
rewriter.eraseOp(subviewUser);
|
||||||
|
if (op->use_empty())
|
||||||
|
rewriter.eraseOp(op);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (allocOp.use_empty())
|
||||||
|
rewriter.eraseOp(allocOp);
|
||||||
|
return success();
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
struct PimConstantFoldingPass : PassWrapper<PimConstantFoldingPass, OperationPass<ModuleOp>> {
|
||||||
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(PimConstantFoldingPass)
|
||||||
|
|
||||||
|
StringRef getArgument() const override { return "pim-constant-folding-pass"; }
|
||||||
|
StringRef getDescription() const override { return "Fold host-side constant expressions before PIM verification"; }
|
||||||
|
|
||||||
|
LogicalResult initialize(MLIRContext* context) override {
|
||||||
|
RewritePatternSet owningPatterns(context);
|
||||||
|
for (auto* dialect : context->getLoadedDialects())
|
||||||
|
dialect->getCanonicalizationPatterns(owningPatterns);
|
||||||
|
for (RegisteredOperationName op : context->getRegisteredOperations())
|
||||||
|
op.getCanonicalizationPatterns(owningPatterns, context);
|
||||||
|
owningPatterns
|
||||||
|
.add<FoldConstantTransposePattern, FoldConstantAllocPattern, FoldConstantCoreMapPattern, RewriteCoreSubviewCopyPattern>(
|
||||||
|
context);
|
||||||
|
patterns = std::make_shared<FrozenRewritePatternSet>(std::move(owningPatterns));
|
||||||
|
return success();
|
||||||
|
}
|
||||||
|
|
||||||
|
void runOnOperation() override {
|
||||||
|
GreedyRewriteConfig config;
|
||||||
|
config.enableFolding();
|
||||||
|
if (failed(applyPatternsGreedily(getOperation(), *patterns, config))) {
|
||||||
|
signalPassFailure();
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
dumpModule(getOperation(), "pim2_folded");
|
||||||
|
}
|
||||||
|
|
||||||
|
std::shared_ptr<const FrozenRewritePatternSet> patterns;
|
||||||
|
};
|
||||||
|
|
||||||
|
} // namespace
|
||||||
|
|
||||||
|
std::unique_ptr<Pass> createPimConstantFoldingPass() { return std::make_unique<PimConstantFoldingPass>(); }
|
||||||
|
|
||||||
|
} // namespace onnx_mlir
|
||||||
@@ -1,181 +0,0 @@
|
|||||||
#include "mlir/Dialect/MemRef/IR/MemRef.h"
|
|
||||||
#include "mlir/IR/BuiltinAttributes.h"
|
|
||||||
#include "mlir/IR/BuiltinTypes.h"
|
|
||||||
#include "mlir/IR/MLIRContext.h"
|
|
||||||
#include "mlir/IR/PatternMatch.h"
|
|
||||||
#include "mlir/Pass/Pass.h"
|
|
||||||
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
|
|
||||||
|
|
||||||
#include "llvm/ADT/STLExtras.h"
|
|
||||||
#include "llvm/ADT/SmallBitVector.h"
|
|
||||||
#include "llvm/ADT/SmallVector.h"
|
|
||||||
|
|
||||||
#include <memory>
|
|
||||||
|
|
||||||
#include "src/Accelerators/PIM/Common/PimCommon.hpp"
|
|
||||||
#include "src/Accelerators/PIM/Dialect/Pim/PimOps.hpp"
|
|
||||||
|
|
||||||
using namespace mlir;
|
|
||||||
|
|
||||||
namespace onnx_mlir {
|
|
||||||
|
|
||||||
namespace {
|
|
||||||
|
|
||||||
static FailureOr<DenseElementsAttr> transposeDenseElements(DenseElementsAttr denseAttr, ArrayRef<int64_t> perms) {
|
|
||||||
auto tensorType = dyn_cast<RankedTensorType>(denseAttr.getType());
|
|
||||||
if (!tensorType)
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
int64_t rank = tensorType.getRank();
|
|
||||||
if (static_cast<int64_t>(perms.size()) != rank)
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
llvm::SmallBitVector seen(rank);
|
|
||||||
SmallVector<int64_t> transposedShape;
|
|
||||||
transposedShape.reserve(rank);
|
|
||||||
for (int64_t perm : perms) {
|
|
||||||
if (perm < 0 || perm >= rank || seen.test(perm))
|
|
||||||
return failure();
|
|
||||||
seen.set(perm);
|
|
||||||
transposedShape.push_back(tensorType.getShape()[perm]);
|
|
||||||
}
|
|
||||||
|
|
||||||
auto transposedType = RankedTensorType::get(transposedShape, tensorType.getElementType());
|
|
||||||
if (denseAttr.isSplat())
|
|
||||||
return DenseElementsAttr::get(transposedType, denseAttr.getSplatValue<Attribute>());
|
|
||||||
|
|
||||||
SmallVector<Attribute> originalValues(denseAttr.getValues<Attribute>());
|
|
||||||
SmallVector<Attribute> transposedValues(originalValues.size());
|
|
||||||
|
|
||||||
SmallVector<int64_t> originalStrides(rank, 1);
|
|
||||||
SmallVector<int64_t> transposedStrides(rank, 1);
|
|
||||||
for (int64_t dim = rank - 2; dim >= 0; --dim) {
|
|
||||||
originalStrides[dim] = originalStrides[dim + 1] * tensorType.getShape()[dim + 1];
|
|
||||||
transposedStrides[dim] = transposedStrides[dim + 1] * transposedShape[dim + 1];
|
|
||||||
}
|
|
||||||
|
|
||||||
SmallVector<int64_t> originalIndices(rank);
|
|
||||||
SmallVector<int64_t> transposedIndices(rank);
|
|
||||||
for (auto [linearIndex, value] : llvm::enumerate(originalValues)) {
|
|
||||||
int64_t remaining = static_cast<int64_t>(linearIndex);
|
|
||||||
for (int64_t dim = 0; dim < rank; ++dim) {
|
|
||||||
originalIndices[dim] = remaining / originalStrides[dim];
|
|
||||||
remaining %= originalStrides[dim];
|
|
||||||
}
|
|
||||||
|
|
||||||
for (int64_t dim = 0; dim < rank; ++dim)
|
|
||||||
transposedIndices[dim] = originalIndices[perms[dim]];
|
|
||||||
|
|
||||||
int64_t transposedLinearIndex = 0;
|
|
||||||
for (int64_t dim = 0; dim < rank; ++dim)
|
|
||||||
transposedLinearIndex += transposedIndices[dim] * transposedStrides[dim];
|
|
||||||
|
|
||||||
transposedValues[transposedLinearIndex] = value;
|
|
||||||
}
|
|
||||||
|
|
||||||
return DenseElementsAttr::get(transposedType, transposedValues);
|
|
||||||
}
|
|
||||||
|
|
||||||
struct FoldConstantTransposePattern final : OpRewritePattern<pim::PimTransposeOp> {
|
|
||||||
using OpRewritePattern::OpRewritePattern;
|
|
||||||
|
|
||||||
LogicalResult matchAndRewrite(pim::PimTransposeOp transposeOp, PatternRewriter& rewriter) const override {
|
|
||||||
auto resultType = dyn_cast<MemRefType>(transposeOp.getOutRes().getType());
|
|
||||||
if (!resultType || !resultType.hasStaticShape())
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
auto sourceGetGlobal = transposeOp.getData().getDefiningOp<memref::GetGlobalOp>();
|
|
||||||
if (!sourceGetGlobal)
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
auto moduleOp = transposeOp->getParentOfType<ModuleOp>();
|
|
||||||
if (!moduleOp)
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
auto sourceGlobal = lookupGlobalForGetGlobal(moduleOp, sourceGetGlobal);
|
|
||||||
if (!sourceGlobal || !sourceGlobal.getConstant() || !sourceGlobal.getInitialValue())
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
auto denseAttr = dyn_cast<DenseElementsAttr>(*sourceGlobal.getInitialValue());
|
|
||||||
if (!denseAttr)
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
SmallVector<int64_t> perms;
|
|
||||||
perms.reserve(transposeOp.getPerms().size());
|
|
||||||
for (IntegerAttr attr : transposeOp.getPerms().getAsRange<IntegerAttr>())
|
|
||||||
perms.push_back(attr.getInt());
|
|
||||||
FailureOr<DenseElementsAttr> transposedAttr = transposeDenseElements(denseAttr, perms);
|
|
||||||
if (failed(transposedAttr))
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
auto transposedShape = cast<RankedTensorType>(transposedAttr->getType()).getShape();
|
|
||||||
if (!llvm::equal(transposedShape, resultType.getShape()))
|
|
||||||
return failure();
|
|
||||||
|
|
||||||
MemRefType globalType = resultType;
|
|
||||||
|
|
||||||
auto globalName = sourceGlobal.getName().str() + "__folded_transpose";
|
|
||||||
unsigned suffix = 0;
|
|
||||||
while (moduleOp.lookupSymbol(globalName))
|
|
||||||
globalName = sourceGlobal.getName().str() + "__folded_transpose_" + std::to_string(++suffix);
|
|
||||||
|
|
||||||
auto visibility = rewriter.getStringAttr("private");
|
|
||||||
OpBuilder moduleBuilder(moduleOp.getBodyRegion());
|
|
||||||
moduleBuilder.setInsertionPointToStart(moduleOp.getBody());
|
|
||||||
auto newGlobal = memref::GlobalOp::create(moduleBuilder,
|
|
||||||
transposeOp.getLoc(),
|
|
||||||
globalName,
|
|
||||||
visibility,
|
|
||||||
globalType,
|
|
||||||
*transposedAttr,
|
|
||||||
/*constant=*/true,
|
|
||||||
sourceGlobal.getAlignmentAttr());
|
|
||||||
|
|
||||||
rewriter.setInsertionPoint(transposeOp);
|
|
||||||
auto newGetGlobal = memref::GetGlobalOp::create(rewriter, transposeOp.getLoc(), globalType, newGlobal.getName());
|
|
||||||
|
|
||||||
bool isAlwaysWeight =
|
|
||||||
!transposeOp->getUsers().empty()
|
|
||||||
&& llvm::all_of(transposeOp->getUsers(), [](Operation* user) { return isa<pim::PimCoreOp>(user); });
|
|
||||||
if (isAlwaysWeight) {
|
|
||||||
markWeightAlways(newGlobal);
|
|
||||||
markWeightAlways(newGetGlobal);
|
|
||||||
}
|
|
||||||
|
|
||||||
rewriter.replaceOp(transposeOp, newGetGlobal.getResult());
|
|
||||||
return success();
|
|
||||||
}
|
|
||||||
};
|
|
||||||
|
|
||||||
struct PimFoldHostConstantsPass : PassWrapper<PimFoldHostConstantsPass, OperationPass<ModuleOp>> {
|
|
||||||
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(PimFoldHostConstantsPass)
|
|
||||||
|
|
||||||
StringRef getArgument() const override { return "fold-pim-host-constants-pass"; }
|
|
||||||
StringRef getDescription() const override { return "Fold host-side constant expressions before PIM verification"; }
|
|
||||||
|
|
||||||
LogicalResult initialize(MLIRContext* context) override {
|
|
||||||
RewritePatternSet owningPatterns(context);
|
|
||||||
for (auto* dialect : context->getLoadedDialects())
|
|
||||||
dialect->getCanonicalizationPatterns(owningPatterns);
|
|
||||||
for (RegisteredOperationName op : context->getRegisteredOperations())
|
|
||||||
op.getCanonicalizationPatterns(owningPatterns, context);
|
|
||||||
owningPatterns.add<FoldConstantTransposePattern>(context);
|
|
||||||
patterns = std::make_shared<FrozenRewritePatternSet>(std::move(owningPatterns));
|
|
||||||
return success();
|
|
||||||
}
|
|
||||||
|
|
||||||
void runOnOperation() override {
|
|
||||||
GreedyRewriteConfig config;
|
|
||||||
config.enableFolding();
|
|
||||||
if (failed(applyPatternsGreedily(getOperation(), *patterns, config)))
|
|
||||||
signalPassFailure();
|
|
||||||
}
|
|
||||||
|
|
||||||
std::shared_ptr<const FrozenRewritePatternSet> patterns;
|
|
||||||
};
|
|
||||||
|
|
||||||
} // namespace
|
|
||||||
|
|
||||||
std::unique_ptr<Pass> createPimFoldHostConstantsPass() { return std::make_unique<PimFoldHostConstantsPass>(); }
|
|
||||||
|
|
||||||
} // namespace onnx_mlir
|
|
||||||
@@ -15,7 +15,7 @@ std::unique_ptr<mlir::Pass> createSpatialToPimPass();
|
|||||||
|
|
||||||
std::unique_ptr<mlir::Pass> createBufferizePimPass();
|
std::unique_ptr<mlir::Pass> createBufferizePimPass();
|
||||||
|
|
||||||
std::unique_ptr<mlir::Pass> createPimFoldHostConstantsPass();
|
std::unique_ptr<mlir::Pass> createPimConstantFoldingPass();
|
||||||
|
|
||||||
std::unique_ptr<mlir::Pass> createPimHostVerificationPass();
|
std::unique_ptr<mlir::Pass> createPimHostVerificationPass();
|
||||||
|
|
||||||
|
|||||||
@@ -73,7 +73,7 @@ void PimAccelerator::registerPasses(int optLevel) const {
|
|||||||
registerPass(createSpatialToGraphvizPass);
|
registerPass(createSpatialToGraphvizPass);
|
||||||
registerPass(createSpatialToPimPass);
|
registerPass(createSpatialToPimPass);
|
||||||
registerPass(createBufferizePimPass);
|
registerPass(createBufferizePimPass);
|
||||||
registerPass(createPimFoldHostConstantsPass);
|
registerPass(createPimConstantFoldingPass);
|
||||||
registerPass(createPimHostVerificationPass);
|
registerPass(createPimHostVerificationPass);
|
||||||
registerPass(createEmitPimJsonPass);
|
registerPass(createEmitPimJsonPass);
|
||||||
}
|
}
|
||||||
|
|||||||
Reference in New Issue
Block a user