…delSlimConfig (#7596)
### What this PR does / why we need it?
This PR refactors the `AscendModelSlimConfig` class to use **forward
mapping** instead of reverse mapping for quantization config key
transformation.
**Changes:**
1. Modified `apply_vllm_mapper()` to directly apply
`hf_to_vllm_mapper.apply_dict()` to transform `quant_description` keys
from HF format to vLLM format
2. Simplified `quant_prefix_mapper()` to return the prefix directly (no
longer needs mapping since keys are already in vLLM format)
3. Removed `QUANT_MODEL_PREFIX_MAPPINGS` dictionary (~50 lines) - no
longer needed
4. Removed `get_prefix_mapping()` function - no longer needed
5. Removed `vllm_to_hf_mapper` attribute - no longer needed
**Why this change is needed:**
The previous implementation used reverse mapping (vLLM → HF) which had
several issues:
- Some keys might not be used in the forward direction but would be
incorrectly used in reverse
- Empty values in the mapping would cause issues when reversed
- Required maintaining a separate `QUANT_MODEL_PREFIX_MAPPINGS` dict
that duplicated information already available in vLLM's model-specific
`WeightsMapper`
The new approach:
- Uses the forward mapping (HF → vLLM) directly from vLLM's
`WeightsMapper`
- Eliminates the need for duplicate mapping definitions
- Avoids issues with reverse mapping (unused keys, empty values)
- Aligns with how `compressed_tensors_config.py` handles the same
scenario
- vLLM version: v0.18.0
- vLLM main:
ed359c497a
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### What this PR does / why we need it?
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Signed-off-by: Matrix_K <zhangke144@huawei.com>
Signed-off-by: Feng-xiaosuo <tengchang1@huawei.com>
Co-authored-by: Matrix_K <zhangke144@huawei.com>
Co-authored-by: Wang Kunpeng <1289706727@qq.com>
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