Added model wrappers for DeepFM and DLRM#3115
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SSYernar wants to merge 1 commit intometa-pytorch:mainfrom
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Added model wrappers for DeepFM and DLRM#3115SSYernar wants to merge 1 commit intometa-pytorch:mainfrom
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Summary: Pull Request resolved: meta-pytorch#3115 * Added model wrappers for DeepFM and DLRM. The wrapper will take ModelInput as an only parameter in the forward method. * Added the unit tests to cover the models' wrappers Differential Revision: D76916471
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Summary: * Added model wrappers for DeepFM and DLRM. The wrapper will take ModelInput as an only parameter in the forward method. * Added the unit tests to cover the models' wrappers Differential Revision: D76916471
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Summary: Pull Request resolved: meta-pytorch#3115 * Added model wrappers for DeepFM and DLRM. The wrapper will take ModelInput as an only parameter in the forward method. * Added the unit tests to cover the models' wrappers Differential Revision: D76916471
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Summary: * Added model wrapper for DeepFM. The wrapper will take ModelInput as an only parameter in the forward method. * Added the unit tests to cover the model's wrapper Differential Revision: D76916471
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Summary: * Added model wrapper for DeepFM. The wrapper will take ModelInput as an only parameter in the forward method. * Added the parameterized unit tests to cover the model's wrapper Differential Revision: D76916471
Summary: * Added model wrapper for DeepFM. The wrapper will take ModelInput as an only parameter in the forward method. The forward method will return just the prediction if it's in inference mode and losses with prediction if it's in training mode. (Because training pipeline expects loss and prediction. See https://github.com/pytorch/torchrec/blob/main/torchrec/distributed/train_pipeline/train_pipelines.py#L670) * Added the parameterized unit tests to cover the model's wrapper Differential Revision: D76916471
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Differential Revision: D76916471