auto& attr = iter.second;
    if (attr.has_func()) {
      try_use_original_func_name(attr.mutable_func()->mutable_name());
    } else if (attr.has_list()) {
      for (auto& func_attr : *attr.mutable_list()->mutable_func()) {
        try_use_original_func_name(func_attr.mutable_name());
      }
    }
  }
}

Status Exporter::AddInstructionNode(Operation* inst) {
  std::unique_ptr<NodeDef> node_def;

    auto& attr = iter.second;
    if (attr.has_func()) {
      try_use_original_func_name(attr.mutable_func()->mutable_name());
    } else if (attr.has_list()) {
      for (auto& func_attr : *attr.mutable_list()->mutable_func()) {
        try_use_original_func_name(func_attr.mutable_name());
      }
    }
  }
}

Status Exporter::AddInstructionNode(Operation* inst) {
  std::unique_ptr<NodeDef> node_def;

    OptionalAttr<F32Attr>:$quantization_config_low,
    OptionalAttr<F32Attr>:$quantization_config_high,
    OptionalAttr<I64Attr>:$quantization_config_num_buckets,
    StrAttr:$table_name
  );

  let results = (outs
    TF_Float32Tensor:$activations
  );
}

def TF_XlaSparseDenseMatmulGradWithSgdAndCsrInputOp : TF_Op<"XlaSparseDenseMatmulGradWithSgdAndCsrInput", [Pure]> {

                absl::StrCat(node_def.name(), "@", func_name));
          }
        }
      }
    }
  }

  // Upgrade nodes in the GraphDef.
  for (auto& node_def : *gdef.mutable_node()) {
    const OpDef* op_def = nullptr;
    TF_RETURN_IF_ERROR(flib_def->LookUpOpDef(node_def.op(), &op_def));
    // TODO(b/197144710): improve the shared_name attr, each op may use the
    // shared_name differently.

			}); err != nil {
				return err
			}
		}
	}

	return nil
}

// GetTables returns tables
func (m Migrator) GetTables() (tableList []string, err error) {
	err = m.DB.Raw("SELECT TABLE_NAME FROM information_schema.tables where TABLE_SCHEMA=?", m.CurrentDatabase()).
		Scan(&tableList).Error
	return
}

// CreateTable create table in database for values

// ordered.
void SortControlInputs(GraphDef* gdef) {
  int64_t num_nodes = gdef->node_size();
  for (int64_t i = 0; i < num_nodes; ++i) {
    NodeDef* node = gdef->mutable_node(i);
    // Stable sort control inputs and leave the order of data inputs unchanged.
    std::stable_sort(node->mutable_input()->begin(),
                     node->mutable_input()->end(),

    Arg<TF_Float32Tensor, [{Value of velocities used in the ADAM optimization algorithm.}]>:$velocities,

    DefaultValuedOptionalAttr<I64Attr, "-1">:$table_id,
    DefaultValuedOptionalAttr<StrAttr, "\"\"">:$table_name,
    I64Attr:$num_shards,
    I64Attr:$shard_id,
    DefaultValuedOptionalAttr<StrAttr, "\"\"">:$config
  );

  let results = (outs);
}

// - Replacing LegacyFedInput nodes with Placeholder nodes if
//   convert_legacy_fed_inputs option is enabled.
Status PreprocessGraphDef(const GraphImportConfig* specs, GraphDef* graph_def) {
  for (auto& node_def : *graph_def->mutable_node()) {
    // TODO(hinsu): Completely deprecate support for LegacyFedInput ops. One
    // solution could be have a tool to let users upgrade old serialized graphs.
    if (specs && specs->convert_legacy_fed_inputs &&