Welcome to the TorchRec documentation!

TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale recommender systems (RecSys). It allows authors to train models with large embedding tables sharded across many GPUs.

For installation instructions, visit

https://github.com/pytorch/torchrec#readme

Tutorial

In this tutorial, we introduce the primary torchRec API called DistributedModelParallel, or DMP. Like pytorch’s DistributedDataParallel, DMP wraps a model to enable distributed training.

• Tutorial Source

• Open in Google Colab

TorchRec API

Contents:

• torchrec.datasets
  • torchrec.datasets.criteo
  • torchrec.datasets.movielens
  • torchrec.datasets.random
  • torchrec.datasets.utils
• torchrec.datasets.scripts
  • torchrec.datasets.scripts.contiguous_preproc_criteo
  • torchrec.datasets.scripts.npy_preproc_criteo
• torchrec.distributed
  • torchrec.distributed.collective_utils
  • torchrec.distributed.comm
  • torchrec.distributed.comm_ops
  • torchrec.distributed.dist_data
  • torchrec.distributed.embedding
  • torchrec.distributed.embedding_lookup
  • torchrec.distributed.embedding_sharding
  • torchrec.distributed.embedding_types
  • torchrec.distributed.embeddingbag
  • torchrec.distributed.grouped_position_weighted
  • torchrec.distributed.model_parallel
  • torchrec.distributed.quant_embeddingbag
  • torchrec.distributed.train_pipeline
  • torchrec.distributed.types
  • torchrec.distributed.utils
  • torchrec.distributed.mc_modules
  • torchrec.distributed.mc_embeddingbag
  • torchrec.distributed.mc_embedding
• torchrec.distributed.planner
  • torchrec.distributed.planner.constants
  • torchrec.distributed.planner.enumerators
  • torchrec.distributed.planner.partitioners
  • torchrec.distributed.planner.perf_models
  • torchrec.distributed.planner.planners
  • torchrec.distributed.planner.proposers
  • torchrec.distributed.planner.shard_estimators
  • torchrec.distributed.planner.stats
  • torchrec.distributed.planner.storage_reservations
  • torchrec.distributed.planner.types
  • torchrec.distributed.planner.utils
• torchrec.distributed.sharding
  • torchrec.distributed.sharding.cw_sharding
  • torchrec.distributed.dist_data
  • torchrec.distributed.sharding.dp_sharding
  • torchrec.distributed.sharding.rw_sharding
  • torchrec.distributed.sharding.tw_sharding
  • torchrec.distributed.sharding.twcw_sharding
  • torchrec.distributed.sharding.twrw_sharding
• torchrec.fx
  • torchrec.fx.tracer
  • Module contents
• torchrec.inference
  • torchrec.inference.model_packager
  • torchrec.inference.modules
  • Module contents
• torchrec.models
  • torchrec.models.deepfm
  • torchrec.models.dlrm
  • Module contents
• torchrec.modules
  • torchrec.modules.activation
  • torchrec.modules.crossnet
  • torchrec.modules.deepfm
  • torchrec.modules.embedding_configs
  • torchrec.modules.embedding_modules
  • torchrec.modules.feature_processor
  • torchrec.modules.lazy_extension
  • torchrec.modules.mlp
  • torchrec.modules.utils
  • torchrec.modules.mc_modules
  • torchrec.modules.mc_embedding_modules
• torchrec.optim
  • torchrec.optim.clipping
  • torchrec.optim.fused
  • torchrec.optim.keyed
  • torchrec.optim.warmup
  • Module contents
• torchrec.quant
  • torchrec.quant.embedding_modules
  • Module contents
• torchrec.sparse
  • torchrec.sparse.jagged_tensor
  • Module contents

Indices and tables

• Index

• Module Index

• Search Page