auto builder = OpBuilder::atBlockTerminator(&main_graph_op.GetBody());
  // Create an IslandOp that will wrap the IdentityOp. Add a control dependency
  // for the newly copied save function.
  auto wrapper_island_op = builder.create<IslandOp>(
      name_loc, TypeRange{main_file_prefix_arg.getType()},
      tf_executor::ControlType::get(&ctx), ValueRange(control_inputs));

      }
    }
  });
}

// Creates an instance of the default quant parameters pass.
std::unique_ptr<OperationPass<func::FuncOp>> CreateImportQuantStatsPass(
    OperationToName op_to_name, const std::string &stats_str) {
  auto pass = std::make_unique<ImportQuantStatsPass>(op_to_name);
  if (pass->ParseQuantStats(stats_str)) return nullptr;
  return pass;
}

  }
  void runOnOperation() override;
};

// Creates a call to function `func` in region `caller_region`. Use `args` as
// the call arguments, and terminate the region with a yield. The arguments are
// cast to the required type before the call. `use_region_args` control whether
// the input arguments are used as is (for IfOp) or block arguments of the same
// type as the input arguments are created and then used as call arguments (for
// While).

    return tokens[0];
  } else {
    return builder.create<AfterAllOp>(loc, original_token.getType(), tokens)
        .getResult();
  }
}

// Replaces `tf._XlaHostComputeMlir` with individual `mhlo.send` and `mhlo.recv`
// ops per operand and result. Unique Channel IDs are assigned per transfer.
// Sink tokens are created across all `mhlo.send` ops first and then by
// all `mhlo.recv` ops.

// Caches a XlaDeviceAllocator per <backend, device ordinal> pair. A
// XlaDeviceAllocator is created on demand and is associated with a
// XlaDevice. It outlives the device itself (for instance, the buffer
// backing a tensor holds a pointer to the allocator for book-keeping,
// and this buffer can outlast the device).
class XlaDeviceAllocatorState {
 public:
  // Creates or returns a cached XlaDeviceAllocator for a given
  // backend and device_ordinal.

}

// Wraps block in a Launch. External uses of ops in the block will be return
// values of the Launch and remapped to the Launch results. If `before` is set
// to true, the Launch is created before `op`. Otherwise the Launch is created
// after `op`.
mlir::tf_device::LaunchOp CreateLaunchForBlock(OpBuilder* builder,
                                               Operation* op, bool before,

    };
    auto del_dealloc = [&](int pos) {
      deltas.emplace_back(pos + 1, tensor.size);
    };

    if (global.first_use < remat.begin) {
      // The tensor is created before the source range.
      if (global.last_use < remat.insert) {
        // It currently gets deallocated before the newly inserted range, so we
        // need to extend its lifetime: It will now be deallocated at its last

  if (sub_op) {
    sub_op->replaceAllUsesWith(island.getOutputs());
    sub_op->moveBefore(block, block->begin());
    island_builder.create<tf_executor::YieldOp>(loc, sub_op->getResults());
  } else {
    island_builder.create<TF::NoOp>(island.getLoc(), TypeRange{}, ValueRange{});
    island_builder.create<tf_executor::YieldOp>(loc, ValueRange{});
  }
  return island;
}

    const Type expressed_type = value.getType();
    // The value needs to be requantized. A Quantize op will be created to use
    // it as the operand and replace its uses.
    const Type new_type = state.params.castFromExpressedType(expressed_type);
    if (!new_type) return;
    auto requantize_op =
        builder_.create<quantfork::QuantizeCastOp>(loc, new_type, value);
    value.replaceAllUsesWith(requantize_op);

  OpBuilder builder(merged_island.insert_point);
  auto new_island = builder.create<IslandOp>(
      merged_island.insert_point->getLoc(), result_types, operands);
  new_island.getBody().push_back(new Block);
  return new_island;
}

// Creates respective YieldOp for the new merged island.
YieldOp CreateNewIslandYieldOp(IslandOp new_island,