def test_mean_variance_normalize_converter(self): input_dim = (3,) output_dim = (3,) input = [('input', datatypes.Array(*input_dim))] output = [('output', datatypes.Array(*output_dim))] builder = NeuralNetworkBuilder(input, output) builder.add_mvn(name='MVN', input_name='input', output_name='output', epsilon=0) model_onnx = convert_coreml(builder.spec) self.assertTrue(model_onnx is not None)
def test_mean_variance_normalize_converter(self): input_dim = (3, ) output_dim = (3, ) input = [('input', datatypes.Array(*input_dim))] output = [('output', datatypes.Array(*output_dim))] builder = NeuralNetworkBuilder(input, output) builder.add_mvn(name='MVN', input_name='input', output_name='output', epsilon=0) context = ConvertContext() node = MeanVarianceNormalizeLayerConverter.convert( context, builder.spec.neuralNetwork.layers[0], ['input'], ['output']) self.assertTrue(node is not None)