intel/llvm
1
0
Fork 0
mirror of https://github.com/intel/llvm.git synced 2026-01-21 04:14:03 +08:00
Code Issues Packages Projects Releases Wiki Activity

[mlir][sparse] cleanup sparse tensor materialization parameter setup (#68956)

Browse Source
This commit is contained in:
Aart Bik
2023-10-13 09:41:53 -07:00
committed by GitHub
parent 3d75c7c11b
commit bbecd422a9
1 changed files with 1 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp
View File

@@ -209,27 +209,12 @@ public:
genMapBuffers(builder, loc, stt, dimSizesValues, params[kParamDimSizes],
params[kParamDim2Lvl], params[kParamLvl2Dim]);
// Secondary and primary types encoding.
setTemplateTypes(stt);
// Finally, make note that initialization is complete.
assert(isInitialized() && "Initialization failed");
// And return `this` for method chaining.
return *this;
}
/// (Re)sets the C++ template type parameters, and returns `this`
/// for method chaining. This is already done as part of `genBuffers`,
/// but is factored out so that it can also be called independently
/// whenever subsequent `genNewCall` calls want to reuse the same
/// buffers but different type parameters.
//
// TODO: This is only ever used by sparse2sparse-viaCOO `ConvertOp`;
// is there a better way to handle that than this one-off setter method?
NewCallParams &setTemplateTypes(SparseTensorType stt) {
const auto enc = stt.getEncoding();
params[kParamPosTp] = constantPosTypeEncoding(builder, loc, enc);
params[kParamCrdTp] = constantCrdTypeEncoding(builder, loc, enc);
params[kParamValTp] =
constantPrimaryTypeEncoding(builder, loc, stt.getElementType());
// Return `this` for method chaining.
return *this;
}