code: def _define_model_mps(
      batch_size,
      num_features,
      num_classes,
      pred_win,
      seq_len,
      is_prediction_model,
  ):
      config = {
          "mode": _MpsLowLevelMode.kLowLevelModeTrain,
          "ac_pred_window": pred_win,
          "ac_seq_len": seq_len,
      }
  
      input_width = pred_win * seq_len
  
      if is_prediction_model:
          config["mode"] = _MpsLowLevelMode.kLowLevelModeInference
  
      model = _MpsLowLevelAPI(
          network_id=_MpsLowLevelNetworkType.kActivityClassifierNet
      )
      model.init(
          batch_size,
          num_features,
          1,
          input_width,
          num_classes,
          1,
          seq_len,
          updater=2,
          config=config,
      )
  
      return model
  
file_path: turicreate/src/python/turicreate/toolkits/activity_classifier/_mps_model_architecture.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from .._mps_utils import MpsLowLevelAPI, MpsLowLevelNetworkType, MpsLowLevelMode
label_desc: Use image node_id 1 for calling a global function with example usage: _define_model_mps(batch_size, num_features, num_classes, pred_win, seq_len, is_prediction_model) and returns: model