def test_reorganize_data_converter(self): block_size = 2 input_dim = (3, 4 * block_size, 2 * block_size) output_dim = (3 * block_size * block_size, 4, 2) inputs = [('input', datatypes.Array(*input_dim))] outputs = [('output', datatypes.Array(*output_dim))] builder = NeuralNetworkBuilder(inputs, outputs) builder.add_reorganize_data(name='Reorg', input_name='input', output_name='output', mode='SPACE_TO_DEPTH', block_size=2) model_onnx = convert_coreml(builder.spec) self.assertTrue(model_onnx is not None)
def test_reorganize_data_converter(self): block_size = 2 input_dim = (3, 4 * block_size, 2 * block_size) output_dim = (3 * block_size * block_size, 4, 2) inputs = [('input', datatypes.Array(*input_dim))] outputs = [('output', datatypes.Array(*output_dim))] builder = NeuralNetworkBuilder(inputs, outputs) builder.add_reorganize_data(name='Reorg', input_name='input', output_name='output', mode='SPACE_TO_DEPTH', block_size=2) context = ConvertContext() node = ReorganizeDataLayerConverter.convert( context, builder.spec.neuralNetwork.layers[0], ['input'], ['output']) self.assertTrue(node is not None)