<td>
			<div class="stacked-bar-graph">
			{{$Goroutine := .}}
			{{range $.NonOverlappingStats}}
				{{$Time := index $Goroutine.NonOverlappingStats .}}
				{{if $Time}}
					<span {{barStyle . $Time $.MaxTotal}}>&nbsp;</span>
				{{end}}
			{{end}}
			</div>
		</td>
		{{$Goroutine := .}}
		{{range $.NonOverlappingStats}}
			{{$Time := index $Goroutine.NonOverlappingStats .}}
			<td> {{$Time.String}}</td>

	if err != nil {
		return &webhookutil.ErrCallingWebhook{WebhookName: h.Name, Reason: fmt.Errorf("could not get REST client: %w", err), Status: apierrors.NewBadRequest("error getting REST client")}
	}
	ctx, span := tracing.Start(ctx, "Call validating webhook",
		attribute.String("configuration", invocation.Webhook.GetConfigurationName()),
		attribute.String("webhook", h.Name),
		attribute.Stringer("resource", attr.GetResource()),

          }
        } else {
          if (range2.isEmpty()) {
            expected = range1;
          } else {
            expected = range1.span(range2);
          }
        }

        try {
          assertEquals(expected, rangeMap.span());
          assertNotNull(expected);
        } catch (NoSuchElementException e) {
          assertNull(expected);
        }
      }
    }
  }

// to provide an info.Origin that can allow the error to be cached.
func Query(ctx context.Context, path, query, current string, allowed AllowedFunc) (*modfetch.RevInfo, error) {
	ctx, span := trace.StartSpan(ctx, "modload.Query "+path)
	defer span.Done()

	return queryReuse(ctx, path, query, current, allowed, nil)
}

// queryReuse is like Query but also takes a map of module info that can be reused

	Init:           buildop,
	Preprocess:     preprocess,
	Assemble:       span0,
	Progedit:       progedit,
	DWARFRegisters: MIPSDWARFRegisters,
}

var Linkmips64le = obj.LinkArch{
	Arch:           sys.ArchMIPS64LE,
	Init:           buildop,
	Preprocess:     preprocess,
	Assemble:       span0,
	Progedit:       progedit,
	DWARFRegisters: MIPSDWARFRegisters,
}

  mlir::DialectRegistry registry;
  mlir::func::registerAllExtensions(registry);
  mlir::MLIRContext context(registry);
  auto module_or = ConvertSavedModelToMlir(
      &bundle, &context, absl::Span<std::string>(exported_names));
  if (!module_or.status().ok()) {
    tsl::Set_TF_Status_from_Status(status, module_or.status());
    return "// error";
  }

}

void CreateSubgraphCallingFunctionWithRefVar(const Scope& s) {
  NameAttrList ref_float_function;
  ref_float_function.set_name("RefFloatFn");
  ops::PartitionedCall call(s.WithOpName("RefFloat"), {absl::Span<Input>{}},
                            {DT_FLOAT}, ref_float_function);
  Output constant =
      ops::Const(s.WithOpName("constant_ref_pco"), Input::Initializer(0.0));

#include <memory>
#include <optional>
#include <string>
#include <unordered_set>
#include <utility>
#include <vector>

#include "absl/status/status.h"
#include "absl/types/span.h"
#include "llvm/ADT/StringSet.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinAttributes.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

    }
  }

  return absl::OkStatus();
}

tensorflow::MemoryTypeVector GetInputMemoryTypes(
    const tensorflow::FunctionBody* fbody,
    absl::Span<int const> constant_arg_indices,
    absl::Span<int const> resource_arg_indices) {
  // Set input and output memory types.
  tensorflow::MemoryTypeVector input_memory_types(fbody->arg_types.size(),

	}

	// find the containing object
	base, span, _ := findObject(uintptr(e.data), 0, 0)

	if base == 0 {
		if isGoPointerWithoutSpan(e.data) {
			return
		}
		throw("runtime.SetFinalizer: pointer not in allocated block")
	}

	// Move base forward if we've got an allocation header.
	if !span.spanclass.noscan() && !heapBitsInSpan(span.elemsize) && span.spanclass.sizeclass() != 0 {
		base += mallocHeaderSize
	}