// start with a generic forbidden error
		retval := admission.NewForbidden(a, errors.New("Not allowed by PodSecurity")).(*apierrors.StatusError)
		// use message/reason/details/code from admission library if populated
		if result.Result != nil {
			if len(result.Result.Message) > 0 {
				retval.ErrStatus.Message = result.Result.Message
			}
			if len(result.Result.Reason) > 0 {
				retval.ErrStatus.Reason = result.Result.Reason
			}

        }
        map.put(key, this);
    }

    public static ArtifactStatus valueOf(String status) {
        ArtifactStatus retVal = null;

        if (status != null) {
            retVal = map.get(status);
        }

        return retVal != null ? retVal : NONE;
    }

    public boolean equals(Object o) {
        if (this == o) {
            return true;
        }

			}
			retVal = thisVal
		case 3: // match something like aaa[100]
			thisVal := val[match[1]]
			// If it is a list and looking for more down the path
			if thisVal.GetListValue() != nil && len(path) > 1 {
				index, _ := strconv.Atoi(match[2])
				return getConfigValue(path[1:], thisVal.GetListValue().Values[index].GetStructValue().Fields)
			}
			retVal = thisVal
		}
	}
	return retVal
}

		if dst != nil && srcPatch != nil {
			retVal, errMerge := util.MergeAnyWithAny(dst, srcPatch)
			if errMerge != nil {
				return false, fmt.Errorf("function MergeAnyWithAny failed for ApplyClusterMerge: %v", errMerge)
			}

			// Merge the above result with the whole cluster
			merge.Merge(dst, retVal)
		}
	}
	return true, nil
}

  kAsync,
};

enum class DeviceCompileState {
  kUncompiled,
  kCompiling,
  kCompiled,
};

// Creates a single-node graph using the specified `node_def` as the only op
// apart from the arg and retval nodes corresponding to `args` and
// `result_types` respectively.
absl::StatusOr<std::unique_ptr<Graph>> CreateSingleOpGraph(
    const NodeDef& node_def, absl::Span<const XlaArgument> args,

      auto metadata_arg = metadata_proto.add_args();
      metadata_arg->set_kind(
          tensorflow::tpu::TPUCompileMetadataProto::Arg::PARAMETER);
      metadata_arg->set_dtype(dtype);
    }
    // Set up one dummy retval.
    metadata_proto.add_retvals();
    bool use_tuple_args = true;
    std::vector<tensorflow::tpu::ShardingAndIndex> arg_core_mapping;
    std::vector<std::vector<xla::Shape>> per_core_arg_shapes;

// Return value of sigtrampgo is stored in R0.
TEXT sigtramp<>(SB),NOSPLIT|NOFRAME,$0
	MOVM.DB.W [R4-R11, R14], (R13)	// push {r4-r11, lr} (SP-=40)
	SUB	$(16), R13		// reserve space for parameters/retval to go call

	MOVW	R0, R6			// Save param0
	MOVW	R1, R7			// Save param1
	BL	runtime·load_g(SB)	// Clobbers R0

	MOVW	$0, R4
	MOVW	R4, 0(R13)	// No saved link register.

	}

	for _, res := range s.resources {
		if res == nil {
			continue
		}
		resVal := reflect.ValueOf(res)
		if resVal.Type().AssignableTo(targetT) {
			if refVal.Kind() == reflect.Slice {
				refVal.Set(reflect.Append(refVal, resVal))
			} else {
				refVal.Set(resVal)
				return nil
			}
		}
	}

	if s.parent != nil {
		// either didn't find the value or need to continue filling the slice

Kuat <******@****.***> 1704828110 -0800

    for (auto input : inputs) {
      TF_RETURN_IF_ERROR(fn_op->AddInput(input));
    }
    int retvals = outputs.size() - null_indices.size();
    std::vector<AbstractTensorHandle*> fn_outputs(retvals);
    TF_RETURN_IF_ERROR(fn_op->Execute(
        absl::Span<AbstractTensorHandle*>(fn_outputs.data(), fn_outputs.size()),
        &retvals));
    int skipped_indices = 0;
    for (int i = 0; i < outputs.size(); i++) {