TF_RETURN_IF_ERROR(run_result.status());
  xla::ExecutionOutput execution_output = std::move(run_result).value();
  absl::StatusOr<std::vector<VariableInfo>> variable_infos =
      GatherVariableInfo(ctx, *result, 0);
  TF_RETURN_IF_ERROR(variable_infos.status());
  TF_RETURN_IF_ERROR(LockVariables(absl::MakeSpan(*variable_infos)));
  TF_RETURN_IF_ERROR(launch_context.PopulateOutputs(

#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/thread_annotations.h"

namespace tensorflow {

// Creates a list of updated resource variables.
absl::StatusOr<std::vector<VariableInfo>> GatherVariableInfo(
    OpKernelContext* ctx,
    const XlaCompiler::CompilationResult& compilation_result,
    int missing_ctx_input_prefix);

// Returns pointers to inputs stored in `ctx`.

                                                     : nullptr);
    }

    {
      absl::StatusOr<std::vector<VariableInfo>> updated_variables =
          GatherVariableInfo(ctx, *closure.compilation_result(),
                             closure.num_constant_args());
      OP_REQUIRES_OK(ctx, updated_variables.status());

  inputs = {inputs.begin() + constant_input_indices.size(), inputs.end()};
  {
    TF_ASSERT_OK_AND_ASSIGN(std::vector<VariableInfo> updated_variables,
                            GatherVariableInfo(context_.get(), *result,
                                               constant_input_indices.size()));
    TF_ASSERT_OK(LockVariables(absl::MakeSpan(updated_variables)));
    TF_ASSERT_OK(RunPjRtExecutable(

        *ptr = new Var(write.type);
        return absl::OkStatus();
      }));
  return variable;
}

absl::StatusOr<std::vector<VariableInfo>> GatherVariableInfo(
    OpKernelContext* ctx,
    const XlaCompiler::CompilationResult& compilation_result,
    int missing_ctx_input_prefix) {
  std::vector<VariableInfo> out;