/*===- TableGen'erated file -------------------------------------*- C++ -*-===*\
|*                                                                            *|
|* Interface Definitions                                                      *|
|*                                                                            *|
|* Automatically generated file, do not edit!                                 *|
|*                                                                            *|
\*===----------------------------------------------------------------------===*/


/// Return the `in_bounds` attribute name.
::mlir::StringRef mlir::VectorTransferOpInterface::getInBoundsAttrName() {
      return getImpl()->getInBoundsAttrName(getImpl(), getOperation());
  }

/// Return the `permutation_map` attribute name.
::mlir::StringRef mlir::VectorTransferOpInterface::getPermutationMapAttrName() {
      return getImpl()->getPermutationMapAttrName(getImpl(), getOperation());
  }

/// Return the optional in_bounds attribute that specifies for each vector
/// dimension whether it is in-bounds or not. (Broadcast dimensions are
/// always in-bounds).
::mlir::ArrayAttr mlir::VectorTransferOpInterface::getInBounds() {
      return getImpl()->getInBounds(getImpl(), getOperation());
  }

/// Return the memref or ranked tensor operand that this operation operates
/// on. In case of a "read" operation, that's the source from which the
/// operation reads. In case of a "write" operation, that's the destination
/// into which the operation writes.
/// TODO: Change name of operand, which is not accurate for xfer_write.
::mlir::Value mlir::VectorTransferOpInterface::getBase() {
      return getImpl()->getBase(getImpl(), getOperation());
  }

/// Return the vector that this operation operates on. In case of a "read",
/// that's the vector OpResult. In case of a "write", that's the vector
/// operand value that is written by the op.
::mlir::Value mlir::VectorTransferOpInterface::getVector() {
      return getImpl()->getVector(getImpl(), getOperation());
  }

/// Return the type of the vector that this operation operates on.
::mlir::VectorType mlir::VectorTransferOpInterface::getVectorType() {
      return getImpl()->getVectorType(getImpl(), getOperation());
  }

/// Return the indices that specify the starting offsets into the source
/// operand. The starting offsets are guaranteed to be in-bounds except
/// when the transfer operation is masked or the `in_bounds` array doesn't
/// specify that that dimension is not necessarily in bounds. It is undefinied
/// behavior if these guarantees are violated.
::mlir::OperandRange mlir::VectorTransferOpInterface::getIndices() {
      return getImpl()->getIndices(getImpl(), getOperation());
  }

/// Return the permutation map that describes the mapping of vector
/// dimensions to source dimensions, as well as broadcast dimensions.
/// 
/// The permutation result has one result per vector transfer dimension.
/// Each result is either a dim expression, indicating the corresponding
/// dimension in the source operand, or a constant "0" expression,
/// indicating a broadcast dimension.
/// 
/// Note: Nested vector dimensions that are flattened by this op are not
/// accounted for in the permutation map. E.g.:
/// ```
/// // Vector type has rank 4, but permutation map has only 2 results. That
/// // is because there are only 2 transfer dimensions.
/// %0 = vector.transfer_read %arg1[%c3, %c3], %vf0
///     {permutation_map = affine_map<(d0, d1) -> (d0, d1)>}
///     : memref<?x?xvector<4x3xf32>>, vector<1x1x4x3xf32>
/// ```
::mlir::AffineMap mlir::VectorTransferOpInterface::getPermutationMap() {
      return getImpl()->getPermutationMap(getImpl(), getOperation());
  }

/// Return the mask operand if the op has a mask. Otherwise, return an
/// empty value.
Value mlir::VectorTransferOpInterface::getMask() {
      return getImpl()->getMask(getImpl(), getOperation());
  }

/// Returns whether replacing the base operand with a shaped value of
/// `newBaseType` and updating the permutation map according to
/// `newPermutationMap`, where the replacement would adhere to the
/// conditions specified by `updateStartingPosition`, passes any additional
/// op-specific constraints.
::mlir::LogicalResult mlir::VectorTransferOpInterface::mayUpdateStartingPosition(::mlir::ShapedType newBaseType, ::mlir::AffineMap newPermutationMap) {
      return getImpl()->mayUpdateStartingPosition(getImpl(), getOperation(), newBaseType, newPermutationMap);
  }

/// Updates the base of this transfer operation to `newBase`, the indices into
/// that base into `newIndices`, and the permutation map to `newPermutationMap`.
/// The new base, indices, and map must:
/// - Keep the same element type as the base (this condition could be relaxed
///   in the future)
/// - Preserve the number of transfer dimensions and avoid inserting new
///   dimensions unaccounted for in the permutation map - that is, if the transfer operation is
///   reading or writing a 4x2 vector to/from an Nx4x2 tensor or memref, it is
///   not valid to update that base to an Nx8 one, but updating in an N0xN1x4x2
///   base - or even an Nx16x32 one - is acceptable. Similarly, if the transfer
///   rank is 2 and the base is MxN, replacing it with a base that is Mx1xN or
///   MxKxN is only permitted if the permutation map is updated to skip the new
///   dimension. This restriction means that the updater does not need to reshape
///   or otherwise adjust the vector type of the transfer or other related attributes
///   like the inbounds attribute array.
/// - Must not shrink the size of a transfer dimension such that an `inbounds`
///   annotation becomes incorrect.
/// - Must pass any op-specific conditions in `mayUpdateStartingPosition`
/// 
/// The update is performed in-place. Implementations of the interface
/// should use `RewriterBase::modifyOpInPlace` to ensure proper pattern
/// rewriter operation.
void mlir::VectorTransferOpInterface::updateStartingPosition(::mlir::RewriterBase& rewriter, ::mlir::Value newBase, ::mlir::ValueRange newIndices, ::mlir::AffineMapAttr newPermutationMap) {
      return getImpl()->updateStartingPosition(getImpl(), getOperation(), rewriter, newBase, newIndices, newPermutationMap);
  }

/// Return the shape ratio of unrolling to the target vector shape
/// `targetShape`. Return `std::nullopt` if the op cannot be unrolled to the
/// target vector shape.
::std::optional<::llvm::SmallVector<int64_t, 4>> mlir::VectorUnrollOpInterface::getShapeForUnroll() {
      return getImpl()->getShapeForUnroll(getImpl(), getOperation());
  }