*
         * Lock file is {@link java.io.RandomAccessFile} that has two regions:
         * - lock state region, locked for the duration of the operation
         * - lock info region, locked just to write the lock info or read info from it
         * <br><br>
         *
         * Algorithm:<br>
         * 1. We first try to acquire a lock on the state region with retries, see {@link #lockStateRegion(LockMode)}.<br>

    // while creating the tf operations.
    new_types.pop_back();

    llvm::SmallVector<std::unique_ptr<Region>, 1> new_regions;
    for (auto &region : op->getRegions()) {
      new_regions.push_back(std::make_unique<Region>());
      new_regions.back()->takeBody(region);
    }

    llvm::SmallVector<NamedAttribute, 4> attrs;
    if (failed(ReformatOpAttributes(getContext(), op->getAttrs(), attrs)))

  // Registered hook to check if the given region, which is attached to an
  // operation that is *not* isolated from above (i.e. no internal regions
  // reference values defined in an enclosing region), should be used when
  // materializing constants.
  // In the executor dialect we materialize inside an island.
  bool shouldMaterializeInto(Region *region) const final {
    return isa<tf_executor::IslandOp>(region->getParentOp());

	4:   {lang: 0x1f, region: 0x9a},
	5:   {lang: 0x3a, region: 0x6c},
	7:   {lang: 0x3b, region: 0x9d},
	8:   {lang: 0x1d7, region: 0x28},
	9:   {lang: 0x13, region: 0x9d},
	10:  {lang: 0x5b, region: 0x96},
	11:  {lang: 0x60, region: 0x52},
	12:  {lang: 0xb9, region: 0xb5},
	13:  {lang: 0x63, region: 0x96},
	14:  {lang: 0xa5, region: 0x35},
	15:  {lang: 0x3e9, region: 0x9a},
	17:  {lang: 0x529, region: 0x12f},

containers with local storage (JBOD/JBOF) mapped as persistent local volumes. This architecture enables multi-tenant MinIO, allowing isolation of data between customers.

MinIO also supports multi-cluster, multi-site federation similar to AWS regions and tiers. Using MinIO Information Lifecycle Management (ILM), you can configure data to be tiered between NVMe based hot storage, and HDD based warm storage. All data is encrypted with per-object key. Access Control and Identity Management between...

  let description = [{
    This pass extracts a CPU computation cluster with `_xla_outside_compilation`
    annotation, which denotes ops that should be run on CPU/host, from a device cluster.
    Each outside compilation cluster is moved to
    a tf_device.parallel_execute region. The device cluster is also moved to a

```

</div>

```

</div>

// summary in the root level may represent a 16 GiB region of address space,
// and in the next level there could be 8 corresponding entries which represent 2
// GiB subsections of that 16 GiB region, each of which could correspond to 8
// entries in the next level which each represent 256 MiB regions, and so on.
//
// Thus, this design only scales to heaps so large, but can always be extended to

  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}

def WhileOutlinePass : Pass<"tfl-while-loop-outline", "mlir::ModuleOp"> {
  let summary = "Hoist while op regions into functions";
  let constructor = "CreateWhileOutlinePass()";
  let dependentDialects = ["TF::TensorFlowDialect"];
}

def LegalizeTensorListPass : Pass<"tfl-legalize-tensorlist", "mlir::ModuleOp"> {