Candle's Tensor::cumsum(0) internally allocates an [n,n] upper-triangular
matrix (9.3 GB for n=50K) causing OOM on GPUs ≤48 GB. Replace with a
block-parallel Hillis-Steele scan kernel that is O(n) in time and memory.
Additional fixes in this commit:
- Break autograd chain leak in loss/grad accumulation via .detach()
(was leaking ~32 MB/step across entire training run)
- Release features_raw_cuda/targets_raw_cuda after GPU experience
collection (~164 MB VRAM reclaimed)
- Use softmax eval (temp=0.3) in walk-forward backtest to prevent
action collapse causing trades=0 on early-stage models
Validated: 1286 tests pass (408 ml-dqn + 878 ml), 0 failures.
VRAM stable at 754 MB across 45K+ training steps on RTX 3050 Ti.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1d93b6e44d