- ml-explainability/integrated_gradients.rs: the GPU IG path is a
stub that returns an error so callers fall through to CPU. Drop
the three TODO markers and describe the situation declaratively —
the reference CUDA source is kept as a follow-up anchor.
- ml-supervised/mamba/mod.rs: dropout in both inference and training
paths is simulated via the `1 - dropout_rate` scalar bake-in; no
dedicated GPU dropout kernel is wired on the supervised path. The
hidden-state carry-over in the SSD scan requires a 3-D narrow the
GpuTensor API does not expose, and inference only consumes the
last timestep, so the update is intentionally elided.
- ml-core/cuda_autograd/gpu_tensor.rs: the `cat` docstring claimed a
host round-trip; the implementation is already fully DtoD via
`memcpy_dtod` for dim=0 and per-row DtoD for dim>0. Rewrite the
comment to describe the real implementation.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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