(self, network, times=1)
| 556 | assert abs(out_data[i] - correct_data[i]) < error |
| 557 | |
| 558 | def do_forward(self, network, times=1): |
| 559 | data_name = network.get_input_name(1) |
| 560 | datas = [] |
| 561 | datas.append(network.get_discrete_tensor(data_name, 0)) |
| 562 | datas.append(network.get_discrete_tensor(data_name, 1)) |
| 563 | datas.append(network.get_discrete_tensor(data_name, 2)) |
| 564 | |
| 565 | datas[0].set_data_by_share(self.data0) |
| 566 | datas[1].set_data_by_share(self.data1) |
| 567 | datas[2].set_data_by_share(self.data2) |
| 568 | roi_tensor = network.get_io_tensor("roi") |
| 569 | roi_tensor.set_data_by_share(self.roi) |
| 570 | out_name = network.get_output_name(0) |
| 571 | out_tensor = network.get_io_tensor(out_name) |
| 572 | for i in range(times): |
| 573 | network.forward() |
| 574 | network.wait() |
| 575 | |
| 576 | out_data = out_tensor.to_numpy() |
| 577 | self.check_correct(out_data) |
| 578 | |
| 579 | |
| 580 | class TestDiscreteInput(TestDiscreteInputNet): |
nothing calls this directly
no test coverage detected