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)
