code: def setup_method(self):
      self.dict_config = DictConfig(
          {
              "trainer": {
                  "devices": 1,
                  "num_nodes": 1,
                  "max_epochs": 50,
                  "max_steps": -1,
                  "accumulate_grad_batches": 1,
                  "precision": 32,
                  "accelerator": "gpu",
                  "strategy": "auto",
                  "log_every_n_steps": 1,
                  "val_check_interval": 1,
                  "enable_checkpointing": False,
                  "logger": False,
              },
              "model": {
                  "nemo_path": None,
                  "data_dir": "???",
                  "class_labels": {
                      "intent_labels_file": "intent_labels.csv",
                      "slot_labels_file": "slot_labels.csv",
                  },
                  "class_balancing": None,
                  "intent_loss_weight": 0.6,
                  "pad_label": -1,
                  "ignore_extra_tokens": False,
                  "ignore_start_end": True,
                  "train_ds": {
                      "prefix": "train",
                      "batch_size": 32,
                      "shuffle": True,
                      "num_samples": -1,
                      "num_workers": 2,
                      "drop_last": False,
                      "pin_memory": False,
                  },
                  "validation_ds": {
                      "prefix": "test",
                      "batch_size": 32,
                      "shuffle": False,
                      "num_samples": -1,
                      "num_workers": 2,
                      "drop_last": False,
                      "pin_memory": False,
                  },
                  "test_ds": {
                      "prefix": "test",
                      "batch_size": 32,
                      "shuffle": False,
                      "num_samples": -1,
                      "num_workers": 2,
                      "drop_last": False,
                      "pin_memory": False,
                  },
                  "tokenizer": {
                      "tokenizer_name": "bert-base-uncased",
                      "vocab_file": None,
                      "tokenizer_model": None,
                      "special_tokens": None,
                  },
                  "language_model": {
                      "max_seq_length": 50,
                      "pretrained_model_name": "bert-base-uncased",
                      "lm_checkpoint": None,
                      "config_file": None,
                      "config": None,
                  },
                  "head": {"num_output_layers": 2, "fc_dropout": 0.1},
                  "optim": {
                      "name": "adam",
                      "lr": 0.00002,
                      "args": {
                          "name": "auto",
                          "params": {"weight_decay": 0.01},
                      },
                      "sched": {
                          "name": "WarmupAnnealing",
                          "iters_per_batch": None,
                          "max_steps": -1,
                          "monitor": "val_loss",
                          "reduce_on_plateau": False,
                          "args": {
                              "name": "auto",
                              "params": {
                                  "warmup_steps": None,
                                  "warmup_ratio": 0.1,
                                  "last_epoch": -1,
                              },
                          },
                      },
                  },
              },
              "exp_manager": {
                  "exp_dir": None,
                  "name": "IntentSlot",
                  "create_tensorboard_logger": False,
                  "create_checkpoint_callback": False,
              },
              "hydra": {
                  "run": {"dir": "."},
                  "job_logging": {"root": {"handlers": None}},
              },
          }
      )
  
imports: import os
  import tempfile
  import onnx
  import pytest
  import pytorch_lightning
  import torch
  import wget
  from omegaconf import DictConfig, OmegaConf
  from nemo.collections import nlp
  from nemo.collections.nlp.models import IntentSlotClassificationModel
  from nemo.collections.nlp.modules.common import SequenceClassifier, SequenceRegression, SequenceTokenClassifier, TokenClassifier
label_desc: Use image node_id 6 for calling the TestExportableClassifiers obj's underlying member method code with example usage: obj.setup_method() without return types