o پi @sdZddlZddlmZmZddlZeeZdej j de fddZ dej j de fdd Z e fd ej j d e d eefd dZdS)z Common utilities for torchao. N)CallableOptionalmodulefqncCsd|vS)z1Filter function for quantizing projection layers.projrrrrS/home/ubuntu/.local/lib/python3.10/site-packages/sglang/srt/layers/torchao_utils.py proj_filter sr cCs,t|tjjrtd|ddSd|vS)NzQuantize: skipping z because it's a Conv3dFr) isinstancetorchnnConv3dloggerwarningrrrr proj_filter_conv3dsrmodeltorchao_config filter_fncCsN|dks|dur |Sddlm}m}m}m}m}m}ddlm} m } d|vr0|||t d|Sd|vr>||||d|Sd |vrbt | d d } | d vsVJd | |||| d|d|Sd|vrp|||t d|Sd|vr| d d } | | d} | | vsJd| d| |||| | dt d|Std|)a[Quantize a modelwith torchao quantization specified by torchao_config Args: `model`: a model to be quantized based on torchao_config `torchao_config` (str): type of quantization and their arguments we want to use to quantize the model, e.g. int4wo-128 means int4 weight only quantization with group_size 128 Nr)'float8_dynamic_activation_float8_weightfloat8_weight_onlyint4_weight_only#int8_dynamic_activation_int8_weightint8_weight_only quantize_)PerRow PerTensorint8wo)rint8dqint4wo-) @z?int4wo groupsize needs to be one of [32, 64, 128, 256] but got ) group_sizefp8wofp8dq)per_row per_tensorzSupported granularity are: z, got ) granularityzUnexpected config: )torchao.quantizationrrrrrrtorchao.quantization.observerrrrintsplitkeys ValueError)rrrrrrrrrrrr'r,GRANULARITY_MAPrrr apply_torchao_config_to_model sJ  #!   r4)__doc__loggingtypingrrr getLogger__name__rr Modulestrr rr4rrrr s.