autoxlstm
Automatic architecture configuration for xLSTM models — analogous to Hugging Face's AutoConfig, but for xLSTM.
autoxlstm picks the sLSTM/mLSTM block ratio, head count, and per-head matrix dimension automatically based on:
- Task type: coding/math need sLSTM's sequential state tracking; text-generation/time-series favor mLSTM's parallel throughput.
- Live GPU memory profiling: an empirical stress-test (sacrificial tensor allocation, catching
torch.cuda.OutOfMemoryError) finds the largest safe matrix dimension before building the config, instead of guessing from a static formula.
Install
pip install -e .
## usage
```python
from autoxlstm import AutoXLSTMConfig
config = AutoXLSTMConfig().create(
task_type="coding",
context_length=2048,
embedding_dim=512,
)
from xlstm import xLSTMBlockStack
model = xLSTMBlockStack(config)
Package Layout
| File | Responsibility |
|---|---|
| engine.py | AutoXLSTMConfig orchestrator |
| profiler.py | GPU inspection + OOM stress-test |
| policies.py | task type → block-ratio (xlstm[N:1]) → slstm_at |
| dims.py | pure num_heads/head_dim resolution |
| validators.py | fail-fast input validation |
| exceptions.py | custom error hierarchy |
| constants.py | all tunable defaults |
1 maintainer
Release files for autoxlstm 0.1.0
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|---|---|---|---|---|
| autoxlstm-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:25.8 kB
Release files / autoxlstm-0.1.0.tar.gz
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|---|---|
| Size | 12.9 kB |
| Tags | Python 3 |
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