code: def bag_config():
      return {
          "name": "bag_feature",
          "type": "bag",
          "encoder": {
              "max_len": 5,
              "vocab_size": 10,
              "embedding_size": EMBEDDING_SIZE,
              "vocab": VOCAB,
          },
      }
  
file_path: ludwig/tests/ludwig/features/test_bag_feature.py
imports: from random import choice
  from string import ascii_lowercase, ascii_uppercase, digits
  from typing import Dict
  import pytest
  import torch
  from ludwig.constants import ENCODER, ENCODER_OUTPUT
  from ludwig.features.bag_feature import BagInputFeature
  from ludwig.schema.features.bag_feature import BagInputFeatureConfig
  from ludwig.schema.utils import load_config_with_kwargs
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 1 for calling a global function with example usage: bag_config() and returns: dict