Intern s2 preview lite awq fix bug

[43758726]

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[Copilot]

Pull request overview

This PR updates LMDeploy Lite quantization/calibration paths to better support Qwen3.5 / InternS2Preview architectures and to improve AWQ usability (including a “data-free” mode), alongside a small VLM utility update and a batch-splitting fix.

Changes:

• Add InternS2Preview/Qwen3.5 model build support in the VLM wrapper and fix batch splitting for Qwen3.5 position_embeddings.
• Introduce lmdeploy.lite.model registry-based per-architecture helpers to drive skip patterns (and some MoE parameter rewrites), and propagate skip lists into quantization_config.
• Refactor calibration loading to return the resolved HF architecture and add calib_samples=0 flow for data-free AWQ.

Reviewed changes

Copilot reviewed 12 out of 12 changed files in this pull request and generated 7 comments.

Show a summary per file

File	Description
lmdeploy/vl/model/qwen3_5.py	Adds build_model() handling for Qwen3.5 and InternS2Preview VLM variants.
lmdeploy/lite/utils/batch_split.py	Adjusts splitting logic for Qwen3.5 position_embeddings tuple layout.
lmdeploy/lite/quantization/awq.py	Adds new skip-pattern plumbing and changes skip logic; extends layernorm mapping for Qwen3 MoE.
lmdeploy/lite/model/base.py	Introduces MODELS registry base helper for model-specific quantization support.
lmdeploy/lite/model/qwen.py	Registers Qwen3/Qwen3.5/InternS2Preview skip patterns and MoE conversion helper.
lmdeploy/lite/model/mixtral.py	Registers Mixtral helper and version-dependent skip patterns.
lmdeploy/lite/model/init.py	Initializes Lite model registry and imports registered helpers.
lmdeploy/lite/apis/smooth_quant.py	Threads trust_remote_code, consumes new calibrate return shape, and writes modules_to_not_convert.
lmdeploy/lite/apis/calibrate.py	Refactors model/tokenizer loading, expands supported model maps, and returns arch.
lmdeploy/lite/apis/auto_awq.py	Adds calib_samples=0 data-free mode and uses per-arch helpers/skip list propagation.
lmdeploy/cli/utils.py	Updates CLI help text to document --calib-samples 0.
lmdeploy/archs.py	Removes workspace (TurboMind converted model) shortcut from get_task().

Comments suppressed due to low confidence (1)

lmdeploy/archs.py:146

• get_task() no longer handles local TurboMind converted/workspace model directories (typically containing triton_models/weights). Without this short-circuit, calling get_task() on a converted TurboMind model path will fall through to get_model_arch() and likely fail because there is no HF config to load. Please restore the workspace detection (or add equivalent handling in get_model_arch()) so converted TurboMind models continue to be recognized correctly.

def get_task(backend: str, model_path: str, trust_remote_code: bool = False):
    """Get pipeline type and pipeline class from model config."""
    from lmdeploy.serve.core import AsyncEngine

    _, config = get_model_arch(model_path, trust_remote_code=trust_remote_code)
    if check_vl_llm(backend, config.to_dict()):
        from lmdeploy.serve.core import VLAsyncEngine
        return 'vlm', VLAsyncEngine

    # default task, pipeline_class
    return 'llm', AsyncEngine

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