test(gap9): run the fine-tuning experiments in CI - #66
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Adds 19 training cases in a job of their own, gap9-training-experiments, covering
four families:
channel-wise every convolution halved along a channel axis, one half trained
qlora int8 weight storage with an fp32 compute type
lora low-rank adapters
layerwise the last N weighted layers trained, N swept
Every case was run end-to-end on gvsoc against this commit and reported "Errors: 0";
the cycle counts in the config are from those runs.
channel-wise ResNet8SplitBlock 42.66 MobileNetV1SplitAlt 38.53
qlora CCT 53.89 MobileNetV1 42.28
lora ResNet8 PEFT 56.52 MobileNetV1 51.13
layerwise ResNet8 last1/2/4/6 16.23 / 19.71 / 29.58 / 38.64
MobileNetV1 last1..24 18.73 / 22.14 / 24.83 / 26.60 / 28.72 /
32.92 / 36.60 / 39.70 / 44.28
Two candidates were tried on this same tree and are NOT registered, with the reason
recorded beside the table so a later fix has something to check against:
ResNet8_QLORA faults on device, cluster PE7 LSU "Invalid access"
ResNet8_PEFT_QLORA tiler assert in minimizeRectangle -- per-channel transfers
with the channel index written into the batch offset, the
same defect a channel split with a doubly-read half hits
Its own job rather than more entries in l3-singlebuffer: that job already runs close
to an hour, and an experiment going red should not gate the mainline configurations.
The per-model overrides carry the settings the verification runs actually used
(CC_STACK_SIZE=4096, SLAVESTACKSIZE=512), not the tuned values of the base models
these graphs derive from. Registering settings nobody exercised would mean CI runs a
configuration that was never measured.
Assets follow the existing convention -- network.onnx, inputs.npz and outputs.npz per
training directory plus the optimizer's network.onnx, nothing else. 22 MB.
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What
19 training cases in a job of their own,
gap9-training-experiments, covering four families of parameter-efficient fine-tuning.Every one was run end-to-end on gvsoc against this commit and reported
Errors: 0. The cycle counts above are from those runs and are recorded next to each entry in the config.What is deliberately absent
Two candidates were tried on this same tree and fail, so they are not registered. The reason sits beside the table so a later fix has something to check against:
ResNet8_QLORAInvalid accessResNet8_PEFT_QLORAminimizeRectangle: per-channel transfers with the channel index written into the batch offsetThe second is the same defect that a channel split whose halves are read twice runs into, which is why the channel-wise graphs here are built to read each half once. It is worth fixing on its own.
Why a separate job
gap9-training-tiled-l3-singlebufferalready runs close to an hour. Adding 19 cases to it would roughly double that, and an experiment going red would gate the mainline configurations. The new job runs in parallel and gates nothing.Overrides
The per-model overrides carry what the verification runs actually used —
CC_STACK_SIZE=4096,SLAVESTACKSIZE=512— rather than the tuned values of the base models these graphs derive from (MobileNetV1 is tuned tocc_stack8192). Registering settings nobody exercised would put a configuration into CI that was never measured.Assets
Existing convention only:
network.onnx,inputs.npz,outputs.npzper training directory plus the optimizer'snetwork.onnx. Intermediate build output is not included. 22 MB total;check-added-large-filespasses.🤖 Generated with Claude Code