ENABLE_SINGLE_DIM_MM_FAMILY: opt-in DTensor strided sharding for mm-family ops#429
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ENABLE_SINGLE_DIM_MM_FAMILY: opt-in DTensor strided sharding for mm-family ops#429weifengpy wants to merge 3 commits into
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Summary: AP currently routes mm/addmm/bmm through the legacy register_op_strategy path (gen_einsum_strategies), which only emits plain Shard/Partial/Replicate placements. This misses the _StridedShard strategies that DTensor's single-dim mm path synthesizes when inputs carry _StridedShard — the natural output of view-flatten on multi-dim-sharded tensors. Changes: - Add _PREFER_SINGLE_DIM_OPS allowlist (mm, addmm, bmm, baddbmm, _scaled_mm) in shardings/dtensor_sharding_helpers.py; get_op_strategy routes those to the upstream single-dim path first. - Extend _try_single_dim_strategy's placeholder resolution to emit both Shard(d) and _StridedShard(d, sf) variants, with sf drawn from split_factors observed on upstream input strategies. Previous plain-Shard-only behavior is preserved when no input carries _StridedShard. - Fix _StridedShard miss in is_shard() call sites in apply_sharding.py (_localize_shape_arg) and cost_models/compute_estimation.py (_get_sharded_shape_stride) — _StridedShard-sharded dims were not being divided by mesh_size, causing over-counted FLOPs and wrong local shapes. Benchmarked on LLaMA3-8B at PR meta-pytorch#424-class config (dim=4096, seqlen=8192, 64-rank 8x8 fake-PG mesh): 2-layer: NATIVE solve 45.7s / objective 57576 vs EINSUM 76.1s / 57761 (-40% solve, -0.32% objective). 32-layer: NATIVE solve 29.5 min / objective 520184; EINSUM did not complete in 4h wall time. Test Plan: Three new unit tests in tests/test_propagation_rules.py: - test_mm_strategy_enumerates_strided_shard - test_mm_strategy_plain_shard_still_present - test_mm_strategy_backward_grad_weight_strided Authored with Claude.
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Extends the Phase 1 DTensor strided-shard work by consolidating the _StridedShard-aware sharded check behind a shared is_shard_like() helper in shardings/dtensor_sharding_helpers.py, then uses it at the remaining is_shard() call sites flagged during the plan audit: - propagation_rules.py:177 - strategy-shape validity check - propagation_rules.py:552 - LayerNorm forward reduction-axis check - propagation_rules.py:626 - LayerNorm backward reduction-axis check - propagation_rules.py:702 - aten.pad trailing-dim shard removal - placement_options.py:560 - flex_attention Q/KV dim validity check Also migrates the Phase 1 inline fixes in apply_sharding.py and cost_models/compute_estimation.py to the helper for consistency. These call sites aren't on the Linear view->mm->view critical path, so the fixes are defense-in-depth rather than bugs observed in LLaMA3 benchmarks. However, user code that exercises LayerNorm/pad/flex_attention with _StridedShard-carrying inputs would have silently accepted invalid strategies without these fixes. All existing tests pass with _APPLY_VIEW_MM_VIEW_PATTERN both True and False (tests/test_optimize_placement.py, 11/11 in each configuration; plus the three new tests/test_propagation_rules.py::test_mm_strategy_*). Authored with Claude.
…y torch Under the nightly torch that CI installs (>=2.13.0.dev20260421), DTensor's GraphPipelineStage no longer exposes the underscore-prefixed _validate_fwd_outputs attribute, so mypy flags the call at graph_passes/graph_pp_runner.py:511 with [attr-defined]. The same error appears on remote/main, so this is a pre-existing CI break not caused by the rest of this stack — but it blocks the lint job on every PR until main picks up a fix. Add a narrow `# type: ignore[attr-defined]` to unblock this PR's CI. The real fix (either restoring the attribute upstream or switching to whatever replaced it) is separate work and should happen independently. Authored with Claude.
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current usage of
einsum: AutoParallel rewrites PyTorch'sview → mm → viewdecomposition ofnn.LinearintoeinsumThis PR adds an opt-in toggle
ENABLE_SINGLE_DIM_MM_FAMILY(defaultFalse) that routesmm/addmm/bmm/baddbmm/_scaled_mmthrough single-dim path and enumerates_StridedShardvariants from observed inputsplit_factorsDefault behavior is unchanged. Flip the flag to opt in.
Headline Result
LLaMA3-8B at PR #424-class config (
dim=4096, seqlen=8192, 64-rank 8×8 fake-PG mesh,cost_model=nccl, single-H100, fake collectives):bsk,kn->bsnhas 4 axes vs. mmmk,kn->mnwith 3), making ILP scaling superlinearly worse at depth._StridedShardnever appears in the chosen strategies for the LLaMA3-8B configs tested. Phase 1's_StridedShardenumeration is correct when dormant and ready when exercised by other workloads.