(self, out_data, error=1e-4)
| 536 | roi = np.load(roi_path) |
| 537 | |
| 538 | def check_correct(self, out_data, error=1e-4): |
| 539 | out_data = out_data.flatten() |
| 540 | |
| 541 | config = LiteConfig() |
| 542 | net = LiteNetwork(config) |
| 543 | net.load(self.model_path) |
| 544 | input_tensor = net.get_io_tensor("data") |
| 545 | input_tensor.set_data_by_share(self.data) |
| 546 | roi_tensor = net.get_io_tensor("roi") |
| 547 | roi_tensor.set_data_by_share(self.roi) |
| 548 | output_name = net.get_output_name(0) |
| 549 | output_tensor = net.get_io_tensor(output_name) |
| 550 | net.forward() |
| 551 | net.wait() |
| 552 | |
| 553 | correct_data = output_tensor.to_numpy().flatten() |
| 554 | assert correct_data.size == out_data.size |
| 555 | for i in range(out_data.size): |
| 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) |
no test coverage detected