code: def get_logits(
      context,
      model_snapshot,
      test_path,
      use_cuda,
      output_path,
      field_names,
      dump_raw_input,
      batch_size,
      ndigits_precision,
      output_columns,
      use_gzip,
      device_id,
  ):
      """print logits from  a trained model snapshot to output_path"""
  
      model_snapshot, use_cuda, _ = _get_model_snapshot(
          context, model_snapshot, use_cuda, False
      )
      if output_columns:
          output_columns = [int(x) for x in output_columns.split(",")]
  
      print("\n=== Starting get_logits...")
      workflow_get_logits(
          model_snapshot,
          use_cuda,
          output_path,
          test_path,
          field_names,
          dump_raw_input,
          batch_size,
          ndigits_precision,
          output_columns,
          use_gzip,
          device_id,
      )
  
imports: import json
  import pprint
  import sys
  import tempfile
  from importlib import import_module
  from pydoc import locate
  from typing import Dict, List, Optional, Union
  import click
  import torch
  from pytext import create_predictor
  from pytext.builtin_task import add_include
  from pytext.common.utils import eprint
  from pytext.config import ExportConfig, LATEST_VERSION, PyTextConfig
  from pytext.config.component import register_tasks
  from pytext.config.config_adapter import upgrade_to_latest
  from pytext.config.serialize import config_from_json, config_to_json, parse_config, pytext_config_from_json
  from pytext.config.utils import find_param, replace_param
  from pytext.data.data_handler import CommonMetadata
  from pytext.metric_reporters.channel import Channel, TensorBoardChannel
  from pytext.PreprocessingMap.ttypes import ModelType
  from pytext.task import load
  from pytext.utils.documentation import find_config_class, get_subclasses, pretty_print_config_class, replace_components, ROOT_CONFIG
  from pytext.utils.file_io import PathManager
  from pytext.workflow import export_saved_model_to_caffe2, export_saved_model_to_torchscript, get_logits, prepare_task_metadata, save_pytext_snapshot, test_model_from_snapshot_path, train_model
  from torch.multiprocessing.spawn import spawn
label_desc: Use image node_id 17 for calling a global function with example usage: get_logits(context, model_snapshot, test_path, use_cuda, output_path, field_names, dump_raw_input, batch_size, ndigits_precision, output_columns, use_gzip, device_id) without return types