GitLab

Signed-off-by: Chendi Xue <Chendi.Xue@intel.com>

Signed-off-by: Kyuyeun Kim <kyuyeunk@google.com>

Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>

Signed-off-by: simon-mo <simon.mo@hey.com>

Signed-off-by: Siyuan Liu <lsiyuan@google.com>
Co-authored-by: Hossein Sarshar <hossein.sarshar@gmail.com>
Co-authored-by: Chengji Yao <chengjiyao@google.com>

[LoRA] Support dynamically initialize `packed_modules_mapping` for VLM with arbitrary components (#18987)
Signed-off-by: isotr0py <2037008807@qq.com>
Signed-off-by: Isotr0py <2037008807@qq.com>

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**

commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:18:24 2025 -0500

    Add SPDX license headers to python source files
    
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
    also be easily used by tools to help manage license compliance.
    
The Linux Foundation runs license scans against the codebase to help
ensure
    we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
    
    More information can be found on the SPDX site:
    
    - https://spdx.dev/learn/handling-license-info/

Signed-off-by: Russell Bryant <rbryant@redhat.com>

commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:36:32 2025 -0500

    Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>

---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>

Signed-off-by: youkaichao <youkaichao@gmail.com>

Signed-off-by: wangshuai09 <391746016@qq.com>

TP/quantization/weight loading refactor part 2 - Refactor quantized linear logic and extend quantization support to all models (#1622)

Refactor the tensor parallelism, quantization, and weight-loading codes.

Summary of the new features enabled by this PR:
- **All models** are able to be quantized with AWQ and SqueezeLLM, and [soon GPTQ](https://github.com/vllm-project/vllm/pull/1580).
- Model loading code became much simpler.
- Support model parallelism for all MQA/GQA models when the number of key/value heads is smaller than the tensor parallel size.