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//===- Linalg.cpp - C Interface for Linalg dialect ------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "mlir-c/Dialect/Linalg.h"
#include "mlir/CAPI/AffineMap.h"
#include "mlir/CAPI/Registration.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
using namespace mlir;
using namespace mlir::linalg;
/// Apply the special region builder for the builtin named Linalg op.
/// Assert that `op` is a builtin named Linalg op.
void mlirLinalgFillBuiltinNamedOpRegion(MlirOperation mlirOp) {
Operation *op = unwrap(mlirOp);
auto linalgOp = cast<LinalgOp>(op);
auto *dialect = static_cast<LinalgDialect *>(linalgOp->getDialect());
LinalgDialect::RegionBuilderFunType fun =
dialect->getRegionBuilder(op->getName().getStringRef());
assert(fun && "Expected a builtin named Linalg op.");
assert(op->getNumRegions() == 1 && "Expected Linalg op with 1 region");
assert(op->getRegion(0).getBlocks().empty() &&
"Expected Linalg op with 0 blocks");
SmallVector<Type, 8> argTypes;
SmallVector<Location, 8> argLocs;
for (OpOperand &opOperand : linalgOp->getOpOperands()) {
argTypes.push_back(getElementTypeOrSelf(opOperand.get().getType()));
argLocs.push_back(opOperand.get().getLoc());
}
ImplicitLocOpBuilder b(op->getLoc(), op->getContext());
Region ®ion = op->getRegion(0);
Block *body = b.createBlock(®ion, /*insertPt=*/{}, argTypes, argLocs);
b.setInsertionPointToStart(body);
fun(b, *body, op->getAttrs(), /*emitError=*/{});
}
MLIR_CAPI_EXPORTED bool mlirLinalgIsAContractionOp(MlirOperation op) {
auto linalgOp = llvm::dyn_cast<mlir::linalg::LinalgOp>(unwrap(op));
// isaContractionOpInterface handles null linalgOp internally.
return linalg::isaContractionOpInterface(linalgOp);
}
MLIR_CAPI_EXPORTED MlirLinalgContractionDimensions
mlirLinalgInferContractionDimensions(MlirOperation op) {
MlirLinalgContractionDimensions result{};
auto linalgOp = dyn_cast<linalg::LinalgOp>(unwrap(op));
if (!linalgOp)
return result;
FailureOr<linalg::ContractionDimensions> maybeDims =
linalg::inferContractionDims(linalgOp);
if (failed(maybeDims))
return result;
const linalg::ContractionDimensions &contractionDims = *maybeDims;
MLIRContext *ctx = linalgOp.getContext();
auto toAttr = [ctx](ArrayRef<unsigned> vals) -> MlirAttribute {
return wrap(DenseI32ArrayAttr::get(ctx, llvm::to_vector_of<int32_t>(vals)));
};
result.batch = toAttr(contractionDims.batch);
result.m = toAttr(contractionDims.m);
result.n = toAttr(contractionDims.n);
result.k = toAttr(contractionDims.k);
return result;
}
MLIR_CAPI_EXPORTED MlirLinalgContractionDimensions
mlirLinalgInferContractionDimensionsFromMaps(const MlirAffineMap *indexingMaps,
size_t numMaps) {
MlirLinalgContractionDimensions result{};
if (!indexingMaps || numMaps == 0)
return result;
SmallVector<AffineMap, 3> maps;
maps.reserve(numMaps);
for (size_t i = 0; i < numMaps; ++i) {
maps.push_back(unwrap(indexingMaps[i]));
}
FailureOr<linalg::ContractionDimensions> maybeDims =
linalg::inferContractionDims(maps);
if (failed(maybeDims))
return result;
MLIRContext *ctx = maps[0].getContext();
auto toAttr = [ctx](ArrayRef<unsigned> vals) -> MlirAttribute {
return wrap(DenseI32ArrayAttr::get(ctx, llvm::to_vector_of<int32_t>(vals)));
};
result.batch = toAttr(maybeDims->batch);
result.m = toAttr(maybeDims->m);
result.n = toAttr(maybeDims->n);
result.k = toAttr(maybeDims->k);
return result;
}
MLIR_CAPI_EXPORTED bool mlirLinalgIsAConvolutionOp(MlirOperation op) {
auto linalgOp = llvm::dyn_cast<mlir::linalg::LinalgOp>(unwrap(op));
if (!linalgOp)
return false;
return linalg::isaConvolutionOpInterface(linalgOp);
}
MLIR_CAPI_EXPORTED MlirLinalgConvolutionDimensions
mlirLinalgInferConvolutionDimensions(MlirOperation op) {
MlirLinalgConvolutionDimensions result{};
auto linalgOp = llvm::dyn_cast<mlir::linalg::LinalgOp>(unwrap(op));
if (!linalgOp)
return result;
FailureOr<linalg::ConvolutionDimensions> maybeDims =
linalg::inferConvolutionDims(linalgOp);
if (failed(maybeDims))
return result;
const linalg::ConvolutionDimensions &dims = *maybeDims;
MLIRContext *ctx = linalgOp.getContext();
auto toI32Attr =
[&ctx](const SmallVector<unsigned, 2> &vals) -> MlirAttribute {
return wrap(DenseI32ArrayAttr::get(ctx, llvm::to_vector_of<int32_t>(vals)));
};
auto toI64Attr =
[&ctx](const SmallVector<int64_t, 2> &vals) -> MlirAttribute {
return wrap(DenseI64ArrayAttr::get(ctx, vals));
};
result.batch = toI32Attr(dims.batch);
result.outputImage = toI32Attr(dims.outputImage);
result.outputChannel = toI32Attr(dims.outputChannel);
result.filterLoop = toI32Attr(dims.filterLoop);
result.inputChannel = toI32Attr(dims.inputChannel);
result.depth = toI32Attr(dims.depth);
result.strides = toI64Attr(dims.strides);
result.dilations = toI64Attr(dims.dilations);
return result;
}
MLIR_CAPI_EXPORTED MlirAttribute
mlirLinalgGetIndexingMapsAttribute(MlirOperation op) {
auto linalgOp = llvm::dyn_cast<mlir::linalg::LinalgOp>(unwrap(op));
if (!linalgOp)
return MlirAttribute{nullptr};
ArrayAttr attr = linalgOp.getIndexingMaps();
return wrap(attr);
}
MLIR_DEFINE_CAPI_DIALECT_REGISTRATION(Linalg, linalg, LinalgDialect)
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