class_docstr: Unit test class for testing scikit-learn converter.
class_docstr_tok: ["Unit","test","class","for","testing","scikit-learn","converter","."]
code: def test_unsupported_variational_deconv(self):
      from keras.layers import Input, Lambda, Conv2D, Flatten, Dense
  
      x = Input(shape=(8, 8, 3))
      conv_1 = Conv2D(4, (2, 2), padding="same", activation="relu")(x)
      flat = Flatten()(conv_1)
      hidden = Dense(10, activation="relu")(flat)
      z_mean = Dense(10)(hidden)
      z_log_var = Dense(10)(hidden)
  
      def sampling(args):
          z_mean, z_log_var = args
          return z_mean + z_log_var
  
      z = Lambda(sampling, output_shape=(10,))([z_mean, z_log_var])
      model = Model([x], [z])
      spec = keras.convert(model, ["input"], ["output"]).get_spec()
  
imports: import unittest
  from coremltools._deps import _HAS_KERAS2_TF
  from coremltools.proto import Model_pb2
  from coremltools.proto import FeatureTypes_pb2
  from coremltools.proto import NeuralNetwork_pb2
  import pytest
label_desc: Use image node_id 23 for calling the KerasSingleLayerTest obj's underlying member method code with example usage: obj.test_unsupported_variational_deconv() and returns: unknown