//===- LinalgInterface.h - Linalg operations interfaces -------------------===// // // 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 // //===----------------------------------------------------------------------===// // // This file implements the operation interfaces for Linalg operations. // //===----------------------------------------------------------------------===// #ifndef MLIR_DIALECT_LINALG_IR_LINALGINTERFACES_H_ #define MLIR_DIALECT_LINALG_IR_LINALGINTERFACES_H_ #include "mlir/Dialect/Utils/StructuredOpsUtils.h" #include "mlir/IR/AffineMap.h" #include "mlir/IR/BuiltinTypes.h" #include "mlir/IR/IRMapping.h" #include "mlir/IR/ImplicitLocOpBuilder.h" #include "mlir/IR/OpDefinition.h" #include "mlir/Interfaces/DestinationStyleOpInterface.h" #include "mlir/Interfaces/InferTypeOpInterface.h" #include "mlir/Interfaces/ViewLikeInterface.h" #include "mlir/Support/RawOstreamExtras.h" namespace mlir { namespace linalg { class IteratorTypeAttr; class LinalgOp; class GenericOp; namespace detail { /// Implementation of the method that check if given operands /// can be dropped, i.e. the remaining operands can compute the loop /// bounds of the op. bool canOpOperandsBeDroppedImpl(linalg::LinalgOp linalgOp, ArrayRef<OpOperand *> droppedOperands); } // namespace detail /// Positions of a Linalg op loops that correspond to different kinds of a /// contraction dimension. struct ContractionDimensions { … }; /// Find at least 2 parallel (m and n) and 1 reduction (k) dimension candidates /// that form a matmul subcomputation within `linalgOp`. /// These dimensions are such that: /// 1. The m dimension is involved in an outer-product along LHS /// (i.e. it is a permutation on RES and LHS and does not appear in RHS). /// 2. The n dimension is involved in an outer-product along RHS /// (i.e. it is a permutation on RES and RHS and does not appear in LHS). /// 3. The k dimension appears as a permutation on LHS and RHS. /// 4. m, n and k appear only once in any given indexing. /// 5. Optional batch dimensions that appear in all operands are captured. /// This allows e.g. detecting that some contraction is embedded within /// `linalgOp` with some orthogonal heuristic. /// When multiple dimension occurrences exist that match `batch`, `m`, `n`, or /// `k`, indices are returned in sorted order. /// Returns a failure if any of `m`, `n` or `k` is empty. FailureOr<ContractionDimensions> inferContractionDims(LinalgOp linalgOp); FailureOr<ContractionDimensions> inferContractionDims(ArrayRef<AffineMap> indexingMaps); /// Checks whether `linalgOp` conforms to ContractionOpInterface. // TODO: embed within `isa<ContractionOpInterface>` if possible / natural. bool isaContractionOpInterface(LinalgOp linalgOp); /// Positions of a Linalg op loops that correspond to different kinds of a /// convolution dimension. struct ConvolutionDimensions { … }; /// Find at least 1 parallel (output_image) and reduction (filter_loop) /// dimension candidates that form a convolution subcomputation within /// `linalgOp`. The LHS is assumed to be the convolution input while the /// RHS is assumed as the filter. /// These dimensions are such that: /// 1. Optional batch dimensions that appear in the input and filter. /// 2. The output_image dimension is involved in a cross-correlation along LHS /// (i.e. it is a permutation on RES and LHS and has an associated /// filter_loop in RHS). /// 3. Optional output_channel dimension is involved in an outer-product along /// RHS (i.e. it is a permutation on RES and RHS and does not appear in /// LHS). /// 4. Optional input_channel dimension appears as a permutation on LHS and /// RHS. /// 5. The filter_loop dimension appears as a permutation on the RHS and /// represents the shape of the kernel cross-correlated along a /// corresponding output_image dim. /// 6. The input_channel dimension appears as a permutation on LHS and RHS. /// 7. All dimensions appear only once in any given indexing map. /// This allows e.g. detecting that some convolution is embedded within /// `linalgOp` with some orthogonal heuristic. /// When multiple dimension occurrences exist that match any classification /// indices are returned in sorted order. /// Returns a failure if `output_image` (and implicitly `filter_loop`) is empty. FailureOr<ConvolutionDimensions> inferConvolutionDims(LinalgOp linalgOp); /// Checks whether `linalgOp` conforms to ConvolutionOpInterface. /// By default, we require the `linalgOp` to have non-empty convolved dims /// (implicitly non-empty `output_image` and `filter_loop`). /// Users can loosen the constraint by setting `allowEmptyConvolvedDims` to true // TODO: embed within `isa<ConvolutionOpInterface>` if possible / natural. bool isaConvolutionOpInterface(LinalgOp linalgOp, bool allowEmptyConvolvedDims = false); /// Checks whether `linalgOp` is semantically equivalent to a `linalg.copyOp`. bool isaCopyOpInterface(LinalgOp linalgOp); /// Checks whether a given `genericOp` is semantically equivalent to a single /// linalgelementwise unary op. e.g. linalg.exp. /// A linalg.generic body could be a series of unary elementwise ops e.g. /// `exp(neg(x))`, such as formed by linalg op fusion. Here we restrict it to /// detecting cases where body is is a single computation op. bool isaElemwiseSingleUnaryOpInterface(GenericOp genericOp); /// Checks whether `genericOp` is semantically equivalent to a single linalg /// elementwise binary op e.g. linalg.sub. bool isaElemwiseSingleBinaryOpInterface(GenericOp genericOp); /// Checks whether `genericOp` is semantically equivalent to a `linalg.fill`. /// Returns the scalar fill value if true. std::optional<Value> isaFillOpInterface(GenericOp genericOp); namespace detail { /// Returns true if the block contains a contraction of the following form: /// /// %0 = <elemwise>(permutation-of(cu(block-argument-0), /// cu(block-argument-1))) /// %1 = <reduce>(permutation-of(cu(%0), cu(block-argument-2))) /// return-like cu(%1) /// /// where <elemwise> and <reduce> are binary operations constituting a /// contraction (in the canonical case, <elemwise> is a multiplication and /// <reduce> is an addition). The name and other properties of these operations /// are checked by `isaPair`. All operands of all operations may be supplied /// through a chain of side effect-free unary operations, such as casts, which /// is denoted as `cu` above. /// /// When the body does not contain a contraction, a more precise description of /// the failed precondition is send to the `errs` stream, if provided. bool isContractionBody(Block &block, function_ref<bool(Operation *, Operation *)> isaPair, llvm::raw_ostream &errs = mlir::thread_safe_nulls()); /// Result of matching a Linalg generic against the predicates of it being a /// contraction. enum class MatchContractionResult; /// Checks whether `op` conforms to ContractionOpInterface and populates /// `dimensions` with indexes of the different kinds of dimensions when /// present. MatchContractionResult isContractionInterfaceImpl(Operation *op, ContractionDimensions *dimensions = nullptr); /// Returns the error message corresponding to the contraction checking return /// code. StringRef getMatchContractionMessage(MatchContractionResult res); /// Result of matching a Linalg generic against the predicates of it being a /// convolution. enum class MatchConvolutionResult; /// Checks whether `op` conforms to ConvolutionOpInterface and populates /// `dimensions` with indexes of the different kinds of dimensions when /// present. /// If `allowEmptyConvolvedDims` is not set, we further checks whether the `op` /// contains convolved dims. MatchConvolutionResult isConvolutionInterfaceImpl(Operation *op, ConvolutionDimensions *dimensions = nullptr, bool allowEmptyConvolvedDims = false); /// Returns the error message corresponding to the convolution checking return /// code. StringRef getMatchConvolutionMessage(MatchConvolutionResult res); /// Verify that `op` conforms to ContractionOpInterface. LogicalResult verifyContractionInterface(Operation *op); /// Verify that `op` conforms to the ConvolutionOpInterface. LogicalResult verifyConvolutionInterface(Operation *op); /// Verify that `op` conforms to the FillOpInterface. LogicalResult verifyFillInterface(Operation *op); /// Verify that `op` conforms to the invariants of StructuredOpInterface LogicalResult verifyStructuredOpInterface(Operation *op); } // namespace detail } // namespace linalg } // namespace mlir #include "mlir/Dialect/Linalg/IR/LinalgStructuredOps.h.inc" /// Include the generated interface declarations. #include "mlir/Dialect/Linalg/IR/LinalgInterfaces.h.inc" #endif // MLIR_DIALECT_LINALG_IR_LINALGINTERFACES_H_