llama : add adaptive-p sampler (#17927)

* initial commit for branch

* simplify constants

* add params to `struct common_params_sampling`, add reference to PR

* explicitly clamp `min_target` and `max_target` to `[0.0, 1.0]`

* add args, rename `queue_size` -> `window_size`

* improved comments

* minor

* remove old unused code from algorithm

* minor

* add power law case to `common_sampler_init`, add sampler name mappings

* clarify behaviour when `window_size = 0`

* add missing enums

* remove `target_range` param, make `target == 1` no-op, cleanup code

* oops, straggler

* add missing parameters in `server-task.cpp`

* copy from author

ref:
https://gist.github.com/MrJackSpade/9be99c7efbba7b95a41377e123b7b069

* remove old debug log, style nit

* fix compiler warning, add commented-out logging per token

* re-write + change parameters + simplify

* oops forgot args.cpp

* fix leftover `window_size`

* add missing values to `common_params_sampling::print()`

* with logging

* does this fix it?

* no, but does this?

* update default decay

* optimize

* fix bad merge

my git skills are lacking

* silence `missing initializer for member`

* update default decay to 0.9

* fix logging

* format (double)

* add power law to the new `samplers` vector

* log sampler init values

* improve logging messages in llama_sampler_power_law

* remove extraneous logging

* simplify target computation

last commit with debug logging!

* remove debug logging, explicitly clamp params at init

* add `use_power_law` flag + logic, minor cleanup

* update `power-law` -> `adaptive-p`

* fix cold start EMA

- `ctx->weighted_sum` is now initialized and reset to `target / (1.0f -
clamped_decay)`
- `ctx->total_weight` is now initialized and reset to `1.0f / (1.0f -
clamped_decay)`

this fixes a "cold start" problem with the moving average

* update `SHARPNESS` constant to `10.0f`

* minor style fixes

no functional changes

* minor style fixes cont.

* update `llama_sampler_adaptive_p_i` for backend sampling (ref: #17004)

* separate into `apply` + `accept` functions

* `pending_token_idx`: switch from `llama_token` to `int32`

functionally identical (`llama.h` has `typedef int32_t llama_token;`),
but its more correct now

* don't transform logits <= -1e9f

* fix masking in backend top-p, min-p

* address review comments

* typo in comments `RND` -> `RNG`

* add docs

* add recommended values in completion docs

* address PR feedback

* remove trailing whitespace (for CI `editorconfig`)

* add to adaptive-p to `common_sampler_types_from_chars`

tools/cli/README.md

@@ -113,6 +113,8 @@
 | `--top-k N` | top-k sampling (default: 40, 0 = disabled)<br/>(env: LLAMA_ARG_TOP_K) |
 | `--top-p N` | top-p sampling (default: 0.9, 1.0 = disabled) |
 | `--min-p N` | min-p sampling (default: 0.1, 0.0 = disabled) |
+| `--adaptive-target N` | adaptive-p: select tokens near this probability (valid range 0.0 to 1.0; negative = disabled) |
+| `--adaptive-decay N` | adaptive-p: EMA decay for adaptation; effective history length ≈ 1/(1-decay) tokens (valid range 0.0 - 0.99) |
 | `--top-nsigma N` | top-n-sigma sampling (default: -1.0, -1.0 = disabled) |
 | `--xtc-probability N` | xtc probability (default: 0.0, 0.0 = disabled) |
 | `--xtc-threshold N` | xtc threshold (default: 0.1, 1.0 = disabled) |