AxoSim

API reference

AxoSim CLI

Complete options and defaults for axosim.

Command contract

The tables include parser defaults, choices, required arguments, flag actions, and compatibility options hidden from ordinary help. Every command and subcommand accepts -h or --help. Flag defaults refer to their destination value: store_true sets it true, while store_false sets it false. For example, --blocking-transfer changes non_blocking from its default true to false. Named presets may override parser defaults; explicitly supplied options take precedence. Use the installed command’s --help when working with another revision.

axosim make-demo-data

write deterministic demo NPZ shards

Argument Type/action Default Required Choices
--output str / store None yes —
--samples int / store 8 no —
--shards int / store 1 no —
--time-steps int / store 32 no —
--input-dim int / store 64 no —
--seed int / store 0 no —

Parser source

axosim convert-neuronio

convert raw NeuronIO pickle files to deterministic shards

Argument Type/action Default Required Choices
--input str / store None yes —
--output str / store None yes —
--shard-size int / store 128 no —
--window-size int / store None no —
--window-stride int / store None no —
--ignore-start int / store 0 no —

Parser source

axosim repack-shards

repack shards as sliceable .npy arrays

Argument Type/action Default Required Choices
--input str / store None yes —
--output str / store None yes —
--input-dtype str / store 'int8' no ['int8', 'float32']

Parser source

axosim list-presets

list named train/evaluate presets

No additional arguments are required; this command prints the named recipes as JSON.

axosim evaluate

evaluate a model with the corrected full-trace metric path

Argument Type/action Default Required Choices
--preset str / store None no ['fulltrace-paper-metric', 'legacy-baseline-smoke']
--data str / store None yes —
--output str / store None yes —
--input-dim int / store 1278 no —
--memory-units int / store 30 no —
--branches int / store 32 no —
--model-kind str / store 'baseline' no ['baseline', 'official', 'axomamba', 'mamba-official', 'mamba-pytorch', 'branch-mamba-pytorch', 'branch-trace-rnn']
--model-config str / store 'configs/branch_elm_30_official.json' no —
--batch-size int / store 8 no —
--seed int / store 0 no —
--device str / store 'cpu' no —
--checkpoint str / store None no —
--window-size int / store None no —
--window-stride int / store None no —
--ignore-start int / store 0 no —
--cache-shards int / store 1 no —
--soma-units str / store 'millivolts' no ['millivolts', 'normalized']
--metric-ignore-start int / store 0 no —
--metric-mask-mode str / store 'ignore-start' no ['ignore-start', 'official-overlap']
--metric-stitch-burn-in int / store 150 no —
--soma-affine-calibration flag / store_true False no —
--pin-memory flag / store_true False no —
--blocking-transfer flag / store_false True no —
--registry str / store None no —
--no-registry flag / store_const None no —

--model-kind: use ‘official’ for the paper-style model, ‘axomamba’ for the promoted Mamba surrogate, ‘mamba-official’ for the generic official mamba-ssm backend, or ‘branch-trace-rnn’ for the RNN comparison path; ‘baseline’ is legacy/debug

--metric-mask-mode: Compatibility option hidden from default help.

--metric-stitch-burn-in: Compatibility option hidden from default help.

--registry: append a one-line JSONL record; defaults to /experiment-registry.jsonl

--no-registry: When selected, sets registry to 'off'.

Parser source

axosim diagnose

write biology-oriented surrogate fidelity diagnostics

Argument Type/action Default Required Choices
--preset str / store None no ['fulltrace-paper-metric', 'legacy-baseline-smoke']
--data str / store None yes —
--output-dir str / store None yes —
--input-dim int / store 1278 no —
--memory-units int / store 30 no —
--branches int / store 32 no —
--model-kind str / store 'baseline' no ['baseline', 'official', 'axomamba', 'mamba-official', 'mamba-pytorch', 'branch-mamba-pytorch', 'branch-trace-rnn']
--model-config str / store 'configs/branch_elm_30_official.json' no —
--batch-size int / store 8 no —
--seed int / store 0 no —
--device str / store 'cpu' no —
--checkpoint str / store None no —
--window-size int / store None no —
--window-stride int / store None no —
--ignore-start int / store 0 no —
--cache-shards int / store 1 no —
--metric-ignore-start int / store 0 no —
--metric-mask-mode str / store 'ignore-start' no ['ignore-start', 'official-overlap']
--metric-stitch-burn-in int / store 150 no —
--soma-affine-calibration flag / store_true False no —
--max-samples int / store None no —
--pin-memory flag / store_true False no —
--blocking-transfer flag / store_false True no —

--metric-mask-mode: Compatibility option hidden from default help.

--metric-stitch-burn-in: Compatibility option hidden from default help.

Parser source

axosim train

train a model with the current experiment workflow

Argument Type/action Default Required Choices
--preset str / store None no ['axomamba-probe', 'legacy-baseline-smoke', 'mamba-official-probe', 'mamba2-official-probe', 'official-fulltrace-reference', 'paper-random-fulltrace']
--data str / store None yes —
--checkpoint str / store None yes —
--metrics str / store None yes —
--input-dim int / store 1278 no —
--memory-units int / store 30 no —
--branches int / store 32 no —
--model-kind str / store 'baseline' no ['baseline', 'official', 'axomamba', 'mamba-official', 'mamba-pytorch', 'branch-mamba-pytorch', 'branch-trace-rnn']
--model-config str / store 'configs/branch_elm_30_official.json' no —
--epochs int / store 1 no —
--batch-size int / store 8 no —
--learning-rate float / store 0.0005 no —
--burn-in int / store 0 no —
--seed int / store 0 no —
--device str / store 'cpu' no —
--window-size int / store None no —
--window-stride int / store None no —
--ignore-start int / store 0 no —
--window-sampling str / store 'random-full-trace' no ['deterministic', 'random-full-trace', 'official-full-trace']
--epoch-samples int / store None no —
--shard-reuse-batches int / store 1 no —
--file-load-fraction float / store 0.3 no —
--full-trace-length int / store None no —
--sample-window-reads flag / store_true False no —
--shuffle-mode str / store 'shard' no ['sample', 'shard', 'none']
--cache-shards int / store 1 no —
--val-data str / store None no —
--val-batch-size int / store None no —
--val-cache-shards int / store 1 no —
--val-window-size int / store None no —
--val-window-stride int / store None no —
--val-ignore-start int / store 0 no —
--val-soma-units str / store 'millivolts' no ['millivolts', 'normalized']
--val-metric-ignore-start int / store 500 no —
--val-metric-mask-mode str / store 'ignore-start' no ['ignore-start', 'official-overlap']
--val-metric-stitch-burn-in int / store 150 no —
--val-soma-affine-calibration flag / store_true True no —
--no-val-soma-affine-calibration flag / store_false True no —
--best-checkpoint str / store None no —
--max-train-batches int / store None no —
--lr-schedule str / store 'constant' no ['constant', 'cosine']
--lr-schedule-steps int / store None no —
--optimizer str / store 'adam' no ['adam', 'adamw']
--weight-decay float / store 0.0 no —
--l1-lambda float / store 0.0 no —
--spike-loss-weight float / store 0.5 no —
--soma-loss-weight float / store 0.5 no —
--sparse-soma-loss-weight float / store 0.0 no —
--sparse-soma-high-voltage-quantile float / store 0.9 no —
--sparse-soma-high-dvdt-quantile float / store 0.9 no —
--sparse-soma-input-event-quantile float / store 0.95 no —
--sparse-soma-spike-window int / store 5 no —
--sparse-soma-post-event-window int / store 5 no —
--sera-soma-loss-weight float / store 0.0 no —
--sera-soma-min-weight float / store 0.05 no —
--sera-soma-relevance-power float / store 1.0 no —
--soma-slope-loss-weight float / store 0.0 no —
--grad-clip-norm float / store 0.0 no —
--train-update-log-interval int / store 0 no —
--train-update-log str / store None no —
--prefetch-batches int / store 0 no —
--pin-memory flag / store_true False no —
--blocking-transfer flag / store_false True no —
--registry str / store None no —
--no-registry flag / store_const None no —

--model-kind: use ‘official’ for the paper-style model, ‘axomamba’ for the promoted Mamba surrogate, ‘mamba-official’ for the generic official mamba-ssm backend, or ‘branch-trace-rnn’ for the RNN comparison path; ‘baseline’ is legacy/debug

--sample-window-reads: read random/official windows by sample instead of caching full compressed shards

--val-metric-mask-mode: Compatibility option hidden from default help.

--val-metric-stitch-burn-in: Compatibility option hidden from default help.

--registry: append a one-line JSONL record; defaults to /experiment-registry.jsonl

--no-registry: When selected, sets registry to 'off'.

Parser source

axosim benchmark

time model forward passes on random input

Argument Type/action Default Required Choices
--input-dim int / store 1278 no —
--memory-units int / store 30 no —
--branches int / store 32 no —
--model-kind str / store 'baseline' no ['baseline', 'official', 'axomamba', 'mamba-official', 'mamba-pytorch', 'branch-mamba-pytorch', 'branch-trace-rnn']
--model-config str / store 'configs/branch_elm_30_official.json' no —
--batch-size int / store 1 no —
--time-steps int / store 500 no —
--runs int / store 10 no —
--device str / store 'cpu' no —
--compile flag / store_true False no —
--output str / store None no —

--model-kind: use ‘official’ for the paper-style model, ‘mamba-official’ for the official mamba-ssm backend, or ‘branch-trace-rnn’ for the RNN comparison path; ‘baseline’ is legacy/debug

Parser source

axosim inference-benchmark

benchmark deployment-oriented inference throughput across batch and sequence scales

Argument Type/action Default Required Choices
--input-dim int / store 1278 no —
--memory-units int / store 30 no —
--branches int / store 32 no —
--model-kind str / store 'baseline' no ['baseline', 'official', 'axomamba', 'mamba-official', 'mamba-pytorch', 'branch-mamba-pytorch', 'branch-trace-rnn']
--model-config str / store 'configs/branch_elm_30_official.json' no —
--checkpoint str / store None no —
--batch-sizes str / store '1,8,32,128' no —
--time-steps str / store '500,1000,6000' no —
--runs int / store 20 no —
--warmup-runs int / store 5 no —
--precision str / store 'float32' no ['float32', 'float16', 'bfloat16']
--device str / store 'cpu' no —
--compile flag / store_true False no —
--accuracy-metrics str / store None no —
--output str / store None yes —

Parser source

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