Comments (4)
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"I would like to know the training cycle and training time of DLRM, but I'm having difficulty finding relevant information (papers). If you could let me know via email ([email protected]), I would appreciate it."
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from dlrm.
The training time depends on the data set you are using. It's usually a few hours for Criteo DAC dataset and a few days for Criteo Terabyte dataset on a single machine.
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Related Issues (20)
- RuntimeError: [enforce fail at embedding_lookup_idx.cc:215] current == index_size. 0 vs -1. Your input seems to be incorrect: the sum of lengths values should be the size of the indices tensor, but it appears not. HOT 2
- How does pytorch handle backward pass in a multi-GPU setting? HOT 2
- how to train dlrm with multi-gpu HOT 1
- torchrec: Super slow allreduce in multi-node multi-gpu setting HOT 3
- Embedding_bag operator on GPU HOT 1
- fail to run dlrm_s_pytorch.py on single node multiple GPUs with nccl HOT 1
- python3 HOT 1
- how to inference ./dlrm_s_criteo_kaggle.sh HOT 1
- Getting Nan loss when training dlrm with Kaggle Criteo dataset HOT 7
- Question regarding the pooling in QR trick HOT 1
- Issue with Activating UVM Function in torchrec_dlrm
- Size of embedding tables in MLPerf checkpoint
- Segmentation Fault on M1 Mac. HOT 1
- Help with installation. No module named caffe2
- Docker Build failing HOT 1
- Unable to preprocess Criteo Kaggle Display Advertising Challenge Dataset
- What's the purpose of torchrec_dlrm/?
- Correctly changing precision in DLRM HOT 1
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