troyyyyy
3 years ago
1 changed files with 3 additions and 4 deletions
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-
+3 -4abl/framework_hed.py
+ 3
- 4
abl/framework_hed.py
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| @@ -52,9 +52,9 @@ def result_statistics(pred_Z, Z, Y, logic_forward, char_acc_flag): | |||||
| def filter_data(X, abduced_Z): | def filter_data(X, abduced_Z): | ||||
| finetune_Z = [] | finetune_Z = [] | ||||
| finetune_X = [] | finetune_X = [] | ||||
| for abduced_x, abduced_z in zip(X, abduced_Z): | |||||
| if abduced_z is not []: | |||||
| finetune_X.append(abduced_x) | |||||
| for x, abduced_z in zip(X, abduced_Z): | |||||
| if len(abduced_z) > 0: | |||||
| finetune_X.append(x) | |||||
| finetune_Z.append(abduced_z) | finetune_Z.append(abduced_z) | ||||
| return finetune_X, finetune_Z | return finetune_X, finetune_Z | ||||
| @@ -84,7 +84,6 @@ def train(model, abducer, train_data, test_data, epochs=50, sample_num=-1, verbo | |||||
| for epoch_idx in range(epochs): | for epoch_idx in range(epochs): | ||||
| X, Z, Y = block_sample(train_X, train_Z, train_Y, sample_num, epoch_idx) | X, Z, Y = block_sample(train_X, train_Z, train_Y, sample_num, epoch_idx) | ||||
| preds_res = predict_func(X) | preds_res = predict_func(X) | ||||
| # input() | |||||
| abduced_Z = abduce_func(preds_res, Y) | abduced_Z = abduce_func(preds_res, Y) | ||||
| if ((epoch_idx + 1) % verbose == 0) or (epoch_idx == epochs - 1): | if ((epoch_idx + 1) % verbose == 0) or (epoch_idx == epochs - 1): | ||||