(logdir1, logdir2)
| 23 | |
| 24 | |
| 25 | def eval(logdir1, logdir2): |
| 26 | # Load graph |
| 27 | model = Net2() |
| 28 | |
| 29 | # dataflow |
| 30 | df = Net2DataFlow(hp.test2.data_path, hp.test2.batch_size) |
| 31 | |
| 32 | ckpt1 = tf.train.latest_checkpoint(logdir1) |
| 33 | ckpt2 = tf.train.latest_checkpoint(logdir2) |
| 34 | session_inits = [] |
| 35 | if ckpt2: |
| 36 | session_inits.append(SaverRestore(ckpt2)) |
| 37 | if ckpt1: |
| 38 | session_inits.append(SaverRestore(ckpt1, ignore=['global_step'])) |
| 39 | pred_conf = PredictConfig( |
| 40 | model=model, |
| 41 | input_names=get_eval_input_names(), |
| 42 | output_names=get_eval_output_names(), |
| 43 | session_init=ChainInit(session_inits)) |
| 44 | predictor = OfflinePredictor(pred_conf) |
| 45 | |
| 46 | x_mfccs, y_spec, _ = next(df().get_data()) |
| 47 | summ_loss, = predictor(x_mfccs, y_spec) |
| 48 | |
| 49 | writer = tf.summary.FileWriter(logdir2) |
| 50 | writer.add_summary(summ_loss) |
| 51 | writer.close() |
| 52 | |
| 53 | |
| 54 | def get_arguments(): |
no test coverage detected