}
  return expanded_input;
}

#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/generated_legalize_hlo.inc"

/// Performs the lowering to TF dialect.
void LegalizeHloToTf::runOnOperation() {
  MLIRContext& context = getContext();
  mlir::ModuleOp module = getOperation();

  RewritePatternSet patterns(&getContext());

}

bool StridedSliceOp::GetSlicedBoundRanges(
    SmallVectorImpl<int64_t> *slice_begin, SmallVectorImpl<int64_t> *slice_end,
    SmallVectorImpl<int64_t> *slice_stride) {
  // TODO(hinsu): Support lowering for ops with dynamic begin and end values
  // when it is possible to derive indices based on mask attributes.
  DenseIntElementsAttr sparse_begin_attr, sparse_end_attr, sparse_strides_attr;

- Kube-controller-manager: increased the global level for broadcaster's logging to 3 so that users can ignore event messages by lowering the logging level. It reduces information noise. ([#122293](https://github.com/kubernetes/kubernetes/pull/122293), [@mengjiao-liu](https://github.com/mengjiao-liu))

//      that the chlo ops emit produces more useful tests.
//   2. With chlo legalization enabled, verifying diagnostics to pick up any
//      issues with the full lowering (can catch some broadcasting corner
//      cases which emit with a warning).

//===----------------------------------------------------------------------===//
// BatchNorm op legalizations.

// Putting [1]*byte and similar into direct interfaces.
(IMake _typ (ArrayMake1 val)) => (IMake _typ val)
(ArraySelect [0] (IData x)) => (IData x)

// string ops
// Decomposing StringMake and lowering of StringPtr and StringLen
// happens in a later pass, dec, so that these operations are available
// to other passes for optimizations.
(StringPtr (StringMake (Addr <t> {s} base) _)) => (Addr <t> {s} base)

        ML authoring is generally discouraged.
    *   Add support for unsigned 16-bit integer tensor types in cast op.
    *   Experimental support for lowering `list_ops.tensor_list_set_item` with
        `DynamicUpdateSlice`.
    *   Enabled a new MLIR-based dynamic range quantization backend by default
        *   The new backend is used for post-training int8 dynamic range