Install NNCF

* remove JambaConfig and use official one from transformers

* changes in Jamba modeling file to align with official HF format

enable fused topK_softmax kernel for hip path

0612 kernel of FP8 on A100

Summary:
  Add benchmarking scripts and utils.
 Things to note : 
   - All files are stored in `neuralmagic` folder.
- neuralmagic/benchmarks/scripts/* : Actual benchmarking scripts that
interact with vllm engine.
- neuralmagic/benchmarks/configs/* : JSON config files that define what
benchmark commands to run.
- neuralmagic/benchmarks/run_*.py : Scripts that consume some config
file and run the benchmark scripts.
   - neuralmagic/tools : Add tools 

Testing:
Local testing

---------

Co-authored-by: Varun Sundar Rabindranath <varun@neuralmagic.com>
Co-authored-by: rsnm2 <rshaw@neuralmagic.com>

a fix follow up [MRotaryEmbedding
change](vllm-project@bf3b79e#diff-6bc44986c91bf0876240dec03d56c748403691c7fcd90f7a22e7affff7b033ecR839)

Signed-off-by: z00897138 <zhaorifa@huawei.com>
Co-authored-by: z00897138 <zhaorifa@huawei.com>

setup sparse attention backend

…pSeek-v2 (vllm-project#28101) (vllm-project#14)

Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>
Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Co-authored-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>

… update perf measurement to decode multiple tokens

Signed-off-by: Salar Hosseini <skhorasgani@tenstorrent.com>

[Model] Add end2end example and documentation for qwen2.5-omni

…-project#7)

Adds five new fields to LoRAConfig in vllm/config/lora.py to support
runtime dynamic resizing of GPU LoRA adapter slots:

  - min_loras (int, ge=1): floor for dynamic slot shrinking
  - dynamic_lora_slots (bool): enables automatic watermark-driven scaling
  - lora_mem_high_watermark (float, 0<x<1): scale-down threshold
  - lora_mem_low_watermark (float, 0<x<1): scale-up threshold
  - lora_slot_resize_cooldown_s (float, ge=0): anti-thrash cooldown

Cross-field validation added to _validate_lora_config():
  - min_loras <= max_loras (when dynamic_lora_slots=True)
  - lora_mem_low_watermark < lora_mem_high_watermark (when dynamic=True)

Field-level bounds (ge/gt/lt) enforced by Pydantic at construction time.

dynamic_lora_slots added to compute_hash() as it affects the CudaGraph
specialization path (disables LoRA cudagraph when True, see issue vllm-project#14).

All new fields default to safe values so existing configs are unaffected
when dynamic_lora_slots=False (the default).

Includes 16 unit tests in tests/lora/test_lora_config_dynamic.py
covering defaults, valid configs, all validation error paths, and
compute_hash() behavior.

Closes vllm-project#7
Closes vllm-project#18

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Signed-off-by: Chen Wang <Chen.Wang1@ibm.com>

…e_hash

- Clarify min_loras docstring: <= max_loras is only enforced when
  dynamic_lora_slots=True, not unconditionally.
- Clarify dynamic_lora_slots docstring: remove reference to unimplemented
  POST /v1/scale_max_loras endpoint; note operator-triggered scaling will
  be handled via plugin (issue vllm-project#16).
- Fix compute_hash() comment with TODO(vllm-project#14) reference.
- Add specialize_active_lora to compute_hash() factors — it controls which
  CUDA graphs are captured and must be part of the computation graph hash.
- Add test_compute_hash_differs_with_specialize_active_lora to cover above.

Co-authored-by: Claude
Signed-off-by: Chen Wang <Chen.Wang1@ibm.com>

…-section-12

Expand README Section 12 experimental results and add Section 13 Algorithmic Efficiency analysis