code: def test_batch_predict(self):
      model = MLModel(self.spec)
      x = [
          {"feature_1": 1.0, "feature_2": 1.0},
          {"feature_1": 2.0, "feature_2": 2.0},
      ]
  
      y = model.predict(x)
  
      assert len(y) == 2
      assert y[0]["output"] == 3.1
      assert len(y[0].keys()) == 1
      assert y[1]["output"] == 6.1
      assert len(y[1].keys()) == 1
  
imports: import os
  import shutil
  import tempfile
  import numpy
  import pytest
  import coremltools
  from coremltools import ComputeUnit, utils
  from coremltools._deps import _HAS_TORCH
  from coremltools.converters.mil import Builder
  from coremltools.libmodelpackage import ModelPackage
  from coremltools.models import MLModel
  from coremltools.models.utils import _MLPACKAGE_AUTHOR_NAME, _WEIGHTS_DIR_NAME
  from coremltools.proto import Model_pb2
label_desc: Use image node_id 6 for calling the TestMLModel obj's underlying member method code with example usage: obj.test_batch_predict() without return types