tensorflow/compiler/xla/mlir_hlo/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.h

/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#ifndef MLIR_HLO_DIALECT_MHLO_IR_CHLO_OPS_H
#define MLIR_HLO_DIALECT_MHLO_IR_CHLO_OPS_H

#include "llvm/ADT/StringRef.h"
#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
#include "mlir-hlo/utils/hlo_utils.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/Dialect.h"
#include "mlir/IR/DialectImplementation.h"
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/OpDefinition.h"
#include "mlir/IR/Operation.h"
#include "mlir/IR/TypeUtilities.h"
#include "mlir/IR/Types.h"
#include "mlir/Interfaces/ControlFlowInterfaces.h"
#include "mlir/Interfaces/InferTypeOpInterface.h"
#include "mlir/Interfaces/SideEffectInterfaces.h"

namespace mlir {
namespace chlo {

class ChloDialect : public Dialect {
  void initialize();

 public:
  explicit ChloDialect(MLIRContext* context)
      : Dialect(getDialectNamespace(), context, TypeID::get<ChloDialect>()) {
    initialize();
  }
  Operation* materializeConstant(OpBuilder& builder, Attribute value, Type type,
                                 Location loc) override;
  static StringRef getDialectNamespace() { return "chlo"; }
};

}  // namespace chlo
}  // namespace mlir

namespace mlir {
namespace chlo {
namespace OpTrait {

template <typename ConcreteType>
class Broadcasting
    : public mlir::OpTrait::TraitBase<ConcreteType, Broadcasting> {};

}  // namespace OpTrait
}  // namespace chlo
}  // namespace mlir

#define GET_OP_CLASSES
#include "mlir-hlo/Dialect/mhlo/IR/chlo_ops.h.inc"

namespace mlir {
namespace chlo {

template <typename T>
static Value getConstantLike(OpBuilder& b, Location loc, T constant,
                             Value val) {
  Type ty = getElementTypeOrSelf(val.getType());
  if (auto complexTy = ty.dyn_cast<ComplexType>()) {
    // TODO(b/190374484): This code will only work for static shapes.
    // The proper way to support these constants is through chlo.constant_like
    // which then legalizes to code which works well for both static and dynamic
    // shapes of val.
    // The problem with that approach for complex numbers is that constant_like
    // doesn't work for complex numbers - it carries constants via attributes,
    // and there's no built-in attribute that carries complex numbers.
    return b.create<mhlo::ConstantOp>(
        loc,
        hlo::getSplat(&b, val.getType().cast<RankedTensorType>(), constant));
  }

  auto getAttr = [&]() -> Attribute {
    if (ty.isa<IntegerType>()) return b.getIntegerAttr(ty, constant);
    if (ty.isa<FloatType>()) return b.getFloatAttr(ty, constant);
    llvm_unreachable("unhandled element type");
  };
  return b.create<ConstantLikeOp>(loc, getAttr(), val);
}

Value getConstantLike(OpBuilder& b, Location loc, const APFloat& constant,
                      Value val);

Value getConstantLikeMaxFiniteValue(OpBuilder& b, Location loc, Value val);

Value getConstantLikeInfValue(OpBuilder& b, Location loc, Value val,
                              bool negative);

Value getConstantLikeSmallestFiniteValue(OpBuilder& b, Location loc, Value val);

}  // namespace chlo
}  // namespace mlir

#endif  // MLIR_HLO_DIALECT_MHLO_IR_CHLO_OPS_H