Support llama3 autoparallel + pipelining #1657
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so far just tested locally `LOG_RANK=4 CONFIG_FILE=././torchtitan/models/deepseek_v3/train_configs/debug_model.toml ./run_train.sh --model.name llama3_auto_parallel --parallelism.pipeline_parallel_degree 2 --training.steps 100` Runs and loss converges. Left one TODO about global-batch-size and gradient accumulation
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xmfan
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Aug 29, 2025
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| pp_degree = job_config.parallelism.pipeline_parallel_degree |
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unused pp degree config, should probably raise error when its not local world size
xmfan
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Aug 29, 2025
| spmd_dims.append("tp") | ||
| spmd_mesh = world_mesh[spmd_dims] | ||
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| dp_degree = 1 |
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same, config could specify dp_degree
xmfan
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Aug 29, 2025
fegin
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Aug 29, 2025
| inputs, target=targets, losses=losses, input_batch=inputs | ||
| # TODO: input_batch kwarg only needed for CP, but | ||
| # autoparallel doesn't accept kwargs in its forward | ||
| inputs, target=targets, losses=losses #, input_batch=inputs |
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Curious, why does CP need input_batch?
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I assumed you would know. Am I wrong?
wconstab
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Aug 30, 2025
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| pp_degree = job_config.parallelism.pipeline_parallel_degree | ||
| local_batch_size = job_config.training.local_batch_size | ||
| spmd_batch_size = local_batch_size |
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oops this is a bug for the non-pp case. should be local *dp degree and put in an 'else' branch
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so far just tested locally
LOG_RANK=4 CONFIG_FILE=././torchtitan/models/deepseek_v3/train_configs/debug_model.toml ./run_train.sh --model.name llama3_auto_parallel --parallelism.pipeline_parallel_degree 2 --training.steps 100Runs and loss converges.
Left one TODO about global-batch-size and gradient accumulation