Fix the predictions returned by Trainer.predict(..)#641
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sararb
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Mar 10, 2023
| def forward( | ||
| self, inputs: TensorOrTabularData, targets=None, training=False, testing=False, **kwargs | ||
| ): | ||
| def forward(self, inputs: TabularData, targets=None, training=False, testing=False, **kwargs): |
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T4Rec only supports a dictionary of tensors (i.e. TabularData) as inputs.
sararb
commented
Mar 10, 2023
| torch.nn.Linear(input_size[-1], 1, bias=False), | ||
| torch.nn.Sigmoid(), | ||
| LambdaModule(lambda x: x.view(-1)), | ||
| LambdaModule(lambda x: torch.squeeze(x, -1)), |
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In the case of sequential binary classification, we need to keep the second dimension (i.e. sequence length)
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|
rerun tests |
rnyak
approved these changes
Mar 14, 2023
Documentation previewhttps://nvidia-merlin.github.io/Transformers4Rec/review/pr-641 |
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Fixes #636
Goals ⚽
Trainer.predict().predict_top_kcan only be applied to NextItemPredictionTask.Implementation Details 🚧
Testing Details 🔍
test_sequential_binary_classification_modelto test a sequential model trained with a per-item binary classification task.test_trainer_music_streamingtest_trainer_trop_k_with_wrong_taskto ensure the BC task cannot be used withpredict_top_k > 0