// of summary indices which must be mapped to support those addresses
	// in the summary range.
	addrRangeToSummaryRange := func(level int, r addrRange) (int, int) {
		sumIdxBase, sumIdxLimit := addrsToSummaryRange(level, r.base.addr(), r.limit.addr())
		return blockAlignSummaryRange(level, sumIdxBase, sumIdxLimit)
	}

	// summaryRangeToSumAddrRange converts a range of indices in any

  z = cond.cond(p, lambda: x, lambda: y)
  array_ops.identity(z, name='result')


def tfgather(_):
  params = array_ops.placeholder(dtypes.float32, name='params')
  indices = array_ops.placeholder(dtypes.int32, name='indices')
  array_ops.gather(params, indices, name='gather_output')


def tfmatmul(_):
  x = array_ops.placeholder(dtypes.float32, name='x_hold')
  y = array_ops.placeholder(dtypes.float32, name='y_hold')

  let description = [{
    The op compiles and executes a GPU cluster function.

    func_name is the name of the function to be executed on GPU.
    resource_indices are the indices of inputs that are resources.
    used_output_indices are the indices of outputs that have users.

    Example:
      %results = gpurt.compile_and_execute {func_name = "xla_func_0", resource_indices = [1] ...}
  }];

  let arguments = (ins

  // CHECK: [[ch3:%.*]], [[results:%.*]]:2 = tfrt_fallback_async.get_resource [[ready_ch]] {device = "/device:CPU:0", indices = [0, 1]}
  // CHECK: tfrt_fallback_async.executeop key({{.*}}) cost({{.*}}) device("/device:CPU:0") "tf.MatMul"([[results]]#0, [[results]]#1)
  %a, %b = "tf._TfrtGetResource"() {device = "/device:CPU:0", indices = [0, 1], shared_name = ["", ""], container = ["", ""]} : () -> (tensor<3x1xf32>, tensor<1x3xf32>)

//
// TODO(mdempsky): Rename this too.
type RelocEnt struct {
	Kind RelocKind
	Idx  Index
}

// Reserved indices within the meta relocation section.
const (
	PublicRootIdx  Index = 0
	PrivateRootIdx Index = 1
)

const (
	RelocString RelocKind = iota
	RelocMeta
	RelocPosBase
	RelocPkg
	RelocName
	RelocType
	RelocObj
	RelocObjExt
	RelocObjDict
	RelocBody

	numRelocs = iota

import org.codelibs.opensearch.runner.OpenSearchRunner;
import org.junit.AfterClass;
import org.junit.Before;
import org.junit.BeforeClass;
import org.junit.Test;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction.AnalyzeToken;
import org.opensearch.index.IndexNotFoundException;

public class AnalyzerSettingsTest {
    String id = "analyzerSettingsTest";

    static SuggestSettings settings;

    Stateful operands correspond to TF's variables semantics. An op that has 1
    or more stateful operands is a stateful op.
  }];

  let methods = [
    InterfaceMethod<
      [{Returns the indices of stateful operands.}],
      "std::vector<int>", "GetStatefulOperands", (ins)
    >,
  ];
}

//===----------------------------------------------------------------------===//
// TFL op interface for sparse operands.

    CustomOpInfo new_node_info;
    switch (update_option) {
      case CustomOpUpdateOptions::kInputIndices: {
        const std::vector<std::string> indices =
            absl::StrSplit(node_specification, '-');
        for (const std::string& cur_index : indices) {
          custom_op_map[node_name].quantizable_input_indices.push_back(
              std::stoi(cur_index));
        }
        break;
      }

// license that can be found in the LICENSE file.

#include <windows.h>

int main(int argc, char **argv) {
    if (argc < 3) {
        return 1;
    }
    // Allocate more than 64 TLS indices
    // so the Go runtime doesn't find
    // enough space in the TEB TLS slots.
    for (int i = 0; i < 65; i++) {
        TlsAlloc();
    }
    HMODULE hlib = LoadLibrary(argv[1]);
    if (hlib == NULL) {

	switch n := x.(type) {
	default:
		error_(token.NoPos, "unexpected type %T in walk", x)
		panic("unexpected type")

	case *ast.IndexListExpr:
		f.walk(&n.X, ctxExpr, visit)
		f.walk(n.Indices, ctxExpr, visit)
	}
}

func funcTypeTypeParams(n *ast.FuncType) *ast.FieldList {
	return n.TypeParams
}

func typeSpecTypeParams(n *ast.TypeSpec) *ast.FieldList {
	return n.TypeParams