OpTraits.td

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//===-- OpTraits.td - Custom Trait classes for ops ---------*- tablegen -*-===//
//
// Part of the LLZK Project, under the Apache License v2.0.
// See LICENSE.txt for license information.
// Copyright 2025 Veridise Inc.
// SPDX-License-Identifier: Apache-2.0
//
//===----------------------------------------------------------------------===//
 
#ifndef LLZK_SHARED_OP_HELPER
#define LLZK_SHARED_OP_HELPER
 
include "mlir/Interfaces/InferTypeOpInterface.td"
include "mlir/Interfaces/SideEffectInterfaces.td"
include "mlir/IR/SymbolInterfaces.td"
 
// Do not use this directly. Use LLZKSymbolTable.
def LLZKSymbolTableImplTrait : NativeOpTrait<"LLZKSymbolTableImplTrait"> {
  string cppNamespace = "::llzk";
}
 
// Always use this trait instead of builtin `SymbolTable` trait.
//
// This trait avoids an assertion failure in the `SymbolTable` class constructor
// when the symbol table is malformed (e.g. duplicate symbols), instead allowing
// it to produce an error diagnostic. This can happen due to the implementations
// of `verifySymbolUses()` that do symbol lookups from the root module. These
// are called before ancestor module symbol tables are verified, thus leading to
// an assertion failure before the verifier would produce a friendly diagnostic.
// This trait handles that by injecting the usual symbol table verification on
// ancestor symbol tables before performing verification of the current symbol
// table.
def LLZKSymbolTable : TraitList<[LLZKSymbolTableImplTrait, SymbolTable]>;
 
/// Verify that the operation has a parent of type `op` somewhere in its
/// ancestry.
class HasAncestor<string op> : ParamNativeOpTrait<"HasAncestor", op>,
                               StructuralOpTrait {
  string cppNamespace = "::llzk";
}
 
/// Verify that the operation has a parent of one of the `ops` types somewhere
/// in its ancestry.
class HasAncestorOf<list<string> ops>
    : ParamNativeOpTrait<"HasAncestor", !interleave(ops, ", ")>,
      StructuralOpTrait {
  string cppNamespace = "::llzk";
}
 
// Implements verification for ops with an affine_map instantiation list. These
// ops are expected to contain the following in their `arguments` list:
//  - VariadicOfVariadic<Index, "mapOpGroupSizes">:$mapOperands
//  - DefaultValuedAttr<DenseI32ArrayAttr, "{}">:$numDimsPerMap
//  - DenseI32ArrayAttr:$mapOpGroupSizes
// Additionally, if the op also has the `AttrSizedOperandSegments` trait, the
// parameter of this trait specifies the index within the `operandSegmentSizes`
// attribute associated with the `$mapOperands` argument, otherwise the
// parameter is ignored. All of these attributes are necessary because MLIR
// stores all operands for an Op in a single list. These attributes specify how
// the list of operands is split into logical pieces for the operand components.
//
// For example, suppose the `CreateArrayOp` is used to create an array with type
//    `!array.type<affine_map<(d0)->(d0)>,affine_map<(d0)[s0]->(d0+s0)> x i1>`
//
// 1) `CreateArrayOp` requires the `AttrSizedOperandSegments` trait because it
// defines two variadic arguments: `$elements` and `$mapOperands` (in that
// order). Thus, the `operandSegmentSizes` attribute is automatically defined
// to specify the number of operands that belong to each variadic argument:
//    `operandSegmentSizes = array<i32: COUNT($elements), COUNT($mapOperands)>`
// In the case of `CreateArrayOp`, one of those sizes will always be 0 because
// its assembly format has `$elements` and `$mapOperands` as alternatives. In
// this example, `COUNT($elements) = 0` and `COUNT($mapOperands) = 3` (this is
// the sum of operand count for all affine_map that are used as array dimensions
// in the result array type).
//
// 2) The `$mapOpGroupSizes` attribute groups the `$mapOperands` per affine_map.
// This implies that their sum equals `COUNT($mapOperands)`. In the example, the
// first affine_map has 1 parameter and the second has 2 so:
//     `mapOpGroupSizes = array<i32: 1, 2>`
//
// 3) Finally, the `$numDimsPerMap` attribute splits the `$mapOperands` in each
// group into the dimensional and symbolic inputs for each affine_map.
// Dimensional inputs appear between the () and symbolic inputs appear between
// the []. LLZK mainly uses dimensional inputs and not symbolic inputs but both
// are fully supported. The length of `$numDimsPerMap` must equal the length of
// `$mapOpGroupSizes` and each element of `$numDimsPerMap` must be less than the
// corresponding element of `$mapOpGroupSizes`. In the example, the both
// affine_map instantiations in the array type have 1 dimensional input so:
//     `numDimsPerMap = array<i32: 1, 1>`
//
// It is also recomended to use `custom<AttrDictWithWarnings>(attr-dict)` in the
// assembly format (or the associated parse/print functions directly) to parse
// the attribute dictionary in these ops and present warnings if the
// aforementioned attributes are manually specified.
class VerifySizesForMultiAffineOps<int operandSegmentIndex>
    : ParamNativeOpTrait<"VerifySizesForMultiAffineOps",
                         ""#operandSegmentIndex>,
      StructuralOpTrait {
  string cppNamespace = "::llzk";
}
 
// Identical to `TypesMatchWith` with `rhsArg = result`. This should be used
// instead of `TypesMatchWith` when custom return type inference is necessary
// (via `InferTypeOpAdaptor*`) because MLIR has special handing for
// `TypesMatchWith` that results in "error: redefinition of 'inferReturnTypes'".
class TypeMatchResultWith<string lhsArg, string lhsSummary = lhsArg,
                          string transform,
                          string comparator = "std::equal_to<>()">
    : PredOpTrait<
          "result type matches with "#lhsSummary#" type",
          CPred<comparator#"("#!subst("$_self", "$"#lhsArg#".getType()",
                                      transform)#", $result.getType())">> {
  string lhs = lhsArg;
  string rhs = "result";
  string transformer = transform;
}
 
// Like TypesUnify with `rhsArg = "result"`
class TypeUnifyWithResult<string lhsArg, string lhsSummary = lhsArg,
                          string transform = "$_self">
    : TypeMatchResultWith<lhsArg, lhsSummary, transform, "::llzk::typesUnify">;
 
// Implementation of TypesMatchWith for Variadic `rhsArg` that returns success
// if `rhsArg` is empty.
class VariadicTypesMatchWith<string summary, string lhsArg, string rhsArg,
                             string transform,
                             string comparator = "std::equal_to<>()">
    : TypesMatchWith<
          summary, lhsArg, rhsArg, transform,
          "get"#snakeCaseToCamelCase<rhsArg>.ret#"().empty() || "#comparator>;
 
// Type constraint `llzk::typesUnify(transform(lhs.getType()), rhs.getType())`.
// If either parameter is `$result` it is recommended to use TypeUnifyWithResult
// instead as this is likely too restrictive when type variables are involved.
class TypesUnify<string lhsArg, string rhsArg, string lhsSummary = lhsArg,
                 string rhsSummary = rhsArg, string transform = "$_self">
    : TypesMatchWith<rhsSummary#" type matches with "#lhsSummary#" type",
                     lhsArg, rhsArg, transform, "::llzk::typesUnify">;
 
// Returns success if `elementArg` unifies with the `arrayArg` element type.
class ArrayElemTypeUnifyWith<string arrayArg, string elementArg>
    : TypesUnify<
          arrayArg, elementArg, arrayArg#" element", elementArg,
          "::llvm::cast<::llzk::array::ArrayType>($_self).getElementType()">;
 
// Returns success if `$result` unifies with the `arrayArg` element type.
class ArrayElemTypeUnifyWithResult<string arrayArg>
    : TypeMatchResultWith<
          arrayArg, arrayArg#" element",
          "::llvm::cast<::llzk::array::ArrayType>($_self).getElementType()",
          "::llzk::typesUnify">;
 
// ArrayElemTypeUnifyWithResult + InferTypeOpAdaptorWithIsCompatible (i.e.
// generate inferReturnTypes() and isCompatibleReturnTypes() functions)
class ArrayTypeElemsUnifyWithResultCustomInfer<string arrayArg>
    : TraitList<[ArrayElemTypeUnifyWithResult<arrayArg>,
                 InferTypeOpAdaptorWithIsCompatible]>;
 
#endif // LLZK_SHARED_OP_HELPER