attention() takes (q, k, v, attention_bias, layer_past, to_compute_mask) and
has no use_cache parameter. Three of the four call sites still pass
use_cache=, which raises TypeError; only LLaDALlamaBlock's non-checkpointed
branch -- the path the shipped block_type=llama config takes -- is correct.
dc4c58d0 replaced the vendored RIFE with Practical-RIFE v4.25 and gave
warp() an explicit (tenFlow_div, backwarp_tenGrid) signature, but left
refine.py behind: its four warp(x, flow) calls no longer match, and
nothing imports the module. loss.py holds the EPE/SOBEL training
scaffolding the same commit says it dropped, and is likewise unused.
Two tables decide the native path: one says which architectures may take
it, the other says which loader they get. An entry in the second without
one in the first is a loader nothing can reach, and nothing checked that.
The seventeen lines that rebuild w1 and w2 from whatever the file stored
were copied into all three lokr variants, character for character. They
move to the base class; each variant keeps only the part that differs,
which is how it addresses the product.
The base class keeps its conv branch, which the two chunk variants
deliberately lack: those address 2-d fused weights.
Hosting asked select_candidate whether it could take a layer, and that
function reads the host rank, so each mechanism was gated through the
other one's name. The shared conditions move into channel_candidate,
which says what they actually test: the layer is quantized, a loaded
network covers it, and there is a rank budget to spend on it.
The rules the walk depends on were spread across the comments that
happened to need them, and the attributes it keeps on the model's modules
were written from four files with the ownership recorded nowhere. Both
are stated once in the module docstring, including the identity the
factor cache keys its pass entry on and the three writers that share the
svd tensors.
Deactivate carried its own shorter copy of the component list, missing
text_encoder_4 and transformer_2. Nothing depends on the difference
today: layer names are stamped only on text_encoder, text_encoder_2,
unet, transformer and llm_adapter, so modules in the other components
are skipped by both passes. Sharing the list keeps the two from drifting
apart if that stamping ever widens.
The mode shown in the load and unload lines was derived at print time
from the live fuse setting, so a set applied under one setting was
reported under whatever the setting said later, and the unload line
described the pass that was about to replace it rather than the one
being removed. The pass records the mode it actually used.
last_backup_size was created on lora_common by assignment from
networks.py and read back through a getattr default; both fields are
declared where they live now.
The error limiter halts a pass by raising, and nothing between the raise
and the caller put the model back. A halted pass left group offload hooks
stripped from every component the walk had reached, left a sequential
model on the cpu with offload disabled, and left the counters other
modules read describing the pass before it.
The epilogue moves into finish_pass under a finally, so the model returns
to its offload mode and the counters describe the pass that just ran. The
abort still reaches the caller.
Pass state is reset in one place in lora_sdnq now. Two of the six
accumulators were not being cleared at the start of a pass, and a stale
routed layer suppresses the fallback count for that layer next time.
The per-module walk carried four mechanisms inline, each repeating the
same tail: count the layer, stamp the pair that marks it current, advance
the bar, continue. Five copies of that tail and three of the backup probe
put the deepest arm nine levels in.
Each mechanism is now a function that either takes the layer or declines
to the next, and the walk reads as the four of them in order. The pass
state they share moves onto one object built before the walk starts, with
the accept tail, the stamp and the bar tick as its methods. That takes
network_activate from 218 lines to 55, none of it deeper than the module
loop.
Two shapes are deliberately not folded into that tail: the weight path
counts weights and bias separately and tracks what the module refused,
and the factor-strip restore stamps without counting. Hosting hands a
declined delta back rather than leaving it in a flag, so a pair of Nones
still reads as assembled and no layer is calculated twice.
Both passes opened with the same four steps written twice: bring the
model into a writable state, enumerate the components to walk, open a
progress bar, and probe a weight backup before restoring it. Pull each
into a helper and call it from both entry points. The component
collector keeps the two lists it is given, so deactivate still walks its
own shorter set, and promotion now clears the staged config it consumed.
The restore field had no writer and add() had no caller. Deactivate
assigned its elapsed time where activate accumulates, so a generation
that unloaded more than once reported only the last pass; both are
zeroed together when the generation ends.
The ramp read 1.5 when the option was absent while the option itself
defaults to 0.0, so a config without the key ran a ramp the settings
page said was off. Only reachable where the options registry is not
loaded, which is where the offline suites run.
The keys that mark a degradation as reported lived for the life of the
process, so a user who saw "flip=skipped weight=offloaded", changed the
offload mode and hit the same wall again was told nothing the second
time. Tie the set to the settings the warnings speak about: the stack
signature, the offload mode, the host rank and the checkpoint. Repeating
under one context still says it once.
The generic loader never offered a file to the boft type, so butterfly
OFT adapters reached the oft type instead, which claims any oft_blocks
key without checking its rank and then reads the block count as the lora
dim. Register boft ahead of oft; files with 3-d blocks still land on oft.
The nunchaku path replaced the loaded network list with the on-disk
entries it composed from, so reading a loaded network back hit an object
without the fields it expects: choosing the reported method reads
len(net.modules) and raised on every set change, costing that generation
its infotext and trigger tags. The adapter was already composed by then,
so the image was unaffected. Wrap the composed set in Network objects
and mutate the list in place.
The mechanism gate tests assert select_candidate declines under
requantize, and the apply-method hint names the cache option among
those the requantize choice disables.
The in-place weight installs, the promote-after-deactivate fuse
ordering, and the dynamo reset at model unload live in the shared
loader code; their regression pins belong in the campaign suite beside
the paths they protect.
String axis rewriting every lora tag in the prompt: an existing lbw=
argument is replaced, None removes it for a clean baseline cell. Choices
list the preset names; raw vectors go through csv mode with escaped
commas. Long values truncate in the grid legend.
Vladimir Mandic
nan
Anai-Guo
CalamitousFelicitousness