def test_padding_converter(self): input_dim = (1, 3, 4) output_dim = (1, 5, 6) input = [('input', datatypes.Array(*input_dim))] output = [('output', datatypes.Array(*output_dim))] builder = NeuralNetworkBuilder(input, output) builder.add_padding(name='Pad', left=2, right=0, top=2, bottom=0, input_name='input', output_name='output', padding_type='constant') model_onnx = convert_coreml(builder.spec) self.assertTrue(model_onnx is not None)
def test_padding_converter(self): input_dim = (1, 3, 4) output_dim = (1, 5, 6) input = [('input', datatypes.Array(*input_dim))] output = [('output', datatypes.Array(*output_dim))] builder = NeuralNetworkBuilder(input, output) builder.add_padding(name='Pad', left=2, right=0, top=2, bottom=0, input_name='input', output_name='output', padding_type='constant') context = ConvertContext() node = PaddingLayerConverter.convert( context, builder.spec.neuralNetwork.layers[0], ['input'], ['output']) self.assertTrue(node is not None)