Added model wrapper for DLRM #3128
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Summary: * Added model wrapper for DLRM. 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: D77167717
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Summary: Pull Request resolved: pytorch#3128 * Added model wrapper for DLRM. 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: D77167717
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Summary: * Added model wrapper for DLRM. 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: D77167717
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Summary: * Added model wrapper for DLRM. 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 Reviewed By: aliafzal Differential Revision: D77167717
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Summary: Pull Request resolved: pytorch#3128 * Added model wrapper for DLRM. 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 Reviewed By: aliafzal Differential Revision: D77167717
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Summary: * Added model wrapper for DLRM. 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 Reviewed By: aliafzal Differential Revision: D77167717
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Summary: Pull Request resolved: pytorch#3128 * Added model wrapper for DLRM. 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 Reviewed By: aliafzal Differential Revision: D77167717
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Summary: * Added model wrapper for DLRM. 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 Reviewed By: aliafzal Differential Revision: D77167717
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Summary: Pull Request resolved: pytorch#3128 * Added model wrapper for DLRM. 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 Reviewed By: aliafzal Differential Revision: D77167717
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Summary:
Differential Revision: D77167717