sparse_attention_exclude is a comma separated denylist matched case insensitively against the architecture, the pipeline class and the denoiser class, so one entry works whichever name is to hand. It resolves once per model rather than per call and declines with a log line. Seeded with CosmosTransformer3DModel, the transformer Anima runs, which returns banded noise at every budget tested against a sound dense baseline; listing the class rather than the architecture covers the other models built on it, none of which have been checked.
install_layout_hook took transformer or unet and stopped, so a pipeline
with a second denoiser left that one unhooked and its forwards ran against
whatever the first had published. The slot list follows the denoiser names
in sd_offload_state; the aux components on that list pack no attention
sequence, and a publication from one would clear the layout.
Only the modular path had a per-forward kwargs hook, so a classic pipeline had
no layout and the selector sparsified its whole sequence, prompt conditioning
included. A denoiser pre-hook installed per generation now reads whichever
convention the model uses: the *_indices tensors, or the txt_ids and img_ids a
joint transformer is given.
Packing order is not derivable from the call and differs between architectures,
so only classes verified to pack text first publish; anything else falls back
as before rather than pinning the wrong half of the sequence dense.
A strided query or key changes what a backend's input prep costs, so the route trace records it and keeps strided and contiguous calls as separate routes. The trace also counts calls per route and logs the counts when a generation ends, so a per-step cost can be divided by the number of calls that paid it.
Sparse attention is a stage over the chain rather than a member of it:
one switch, and the router hands the selection to whichever active
backend advertises that it consumes a block mask, currently flex. A
backend declares that through a capability set, so the quantized kernel
joins later without touching the router.
The stage gates on the component role, self attention, a minimum
sequence length defaulting to the measured 8192 token crossover, and the
absence of a token mask or causal flag, which flex cannot combine with a
block only mask. Budgets follow a precomputed per step schedule with at
most two distinct values. Enabling the feature with no capable backend
in the chain warns and leaves attention dense rather than doing nothing
quietly.
The modular pre-forward hook now receives kwargs and publishes whatever
token layout the pipeline passes by name, so a packed sequence gets its
conditioning pinned without any model specific code. Without a layout
the whole sequence is sparsified and that is logged once per length.
A module-level context tells attention consumers what is running: the
component role (transformer, text encoder, vae), the index of the
denoiser forward about to run, the pass length, and the model. It is
opened and closed around process_images, reset per denoising pass beside
the callback setup, and advanced by both step sources: the classic
callback passes the completed step plus one, the modular pre-forward
hook counts forwards. Roles come from the existing text encoder and vae
hijacks and the modular phase hooks. The step also lives in a device
scalar updated in place, so a compiled reader keeps its graph across
steps.
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