group Configuration Reference¶

1. Configuration Overview¶

Processor combiner configuration.

Item	Content
Config Class	`GroupProcessorConfig`
Source	group.py

2. Parameter List¶

2.1 GroupProcessorConfig

Field Path	Type	Required/Optional	Default	Value Range or Format	Description	Referenced Config
`type`	`string`	Required	None	`group`	Processor type, fixed to `group`.	None
`configs`	`list[object]`	Required	None	—	List of processor configurations to combine, executed in order; each element is a processor configuration dispatched by `type`.	This page §2.2

Configuration Constraints

Every sub-processor inside configs must have the same type (combining like with like, for example all linear_quant); for different type values, split them into separate process items instead of mixing them in one group.

2.2 AutoProcessorConfig

Derived Classes

Config Class	`type`	Description	Document
`AdaptRotationProcessorConfig`	`adapt_rotation`	Adaptive rotation (adapt_rotation) processor configuration.	adapt_rotation Configuration Reference
`AutoroundProcessorConfig`	`autoround_quant`	AutoRound quantization processor configuration.	autoround_quant Configuration Reference
`AWQProcessorConfig`	`awq`	AWQ (Activation-aware Weight Quantization) processor configuration.	awq Configuration Reference
`BinaryAnalysisProcessorConfig`	`binary_analysis`	Binary (quantized/non-quantized) sensitivity analysis processor configuration.	binary_analysis Configuration Reference
`BinaryOperatorLayerWiseProcessorConfig`	`binary_operator_layer_wise`	Layer-wise sensitivity analysis processor configuration (compares per-block floating-point and quantized outputs).	binary_operator_layer_wise Configuration Reference
`BinaryOperatorModelWiseProcessorConfig`	`binary_operator_model_wise`	Model-level sensitivity analysis configuration (compares final model outputs, using the MSE metric)	binary_operator_model_wise Configuration Reference
`DynamicCacheProcessorConfig`	`dynamic_cache`	KV cache quantization processor configuration.	dynamic_cache Configuration Reference
`FA3QuantProcessorConfig`	`fa3_quant`	FA3 (FlashAttention-3) quantization processor configuration.	fa3_quant Configuration Reference
`FlatQuantProcessorConfig`	`flatquant`	FlatQuant processor configuration: defines quantization training parameters, strategy, mixed precision, and more	flatquant Configuration Reference
`FlexAWQSSZProcessorConfig`	`flex_awq_ssz`	Flex AWQ SSZ outlier suppression processor configuration.	flex_awq_ssz Configuration Reference
`FlexSmoothQuantProcessorConfig`	`flex_smooth_quant`	FlexSmoothQuant smooth quantization processor configuration.	flex_smooth_quant Configuration Reference
`FloatSparseProcessorConfig`	`float_sparse`	Floating-point sparsity processor configuration.	float_sparse Configuration Reference
`GroupProcessorConfig`	`group`	Processor combiner configuration.	This page §2.1
`IterSmoothProcessorConfig`	`iter_smooth`	Iterative smooth (IterativeSmooth) processor configuration.	iter_smooth Configuration Reference
`KVSmoothProcessorConfig`	`kv_smooth`	KV cache smoothing processor configuration.	kv_smooth Configuration Reference
`LinearProcessorConfig`	`linear_quant`	Linear layer quantization processor configuration.	linear_quant Configuration Reference
`LoadProcessorConfig`	`load`	Module load/unload processor configuration.	load Configuration Reference
`OASQProcessorConfig`	`oasq`	OASQ (Outlier-Aware Smooth Quantization) processor configuration.	oasq Configuration Reference
`OnlineQuaRotProcessorConfig`	`online_quarot`	Online QuaRot rotation processor configuration.	online_quarot Configuration Reference
`QuaRotProcessorConfig`	`quarot`	QuaRot (offline rotation) processor configuration.	quarot Configuration Reference
`QuantSaveProcessorConfig`	`saver`	Unified save processor configuration.	saver Configuration Reference
`SmoothQuantProcessorConfig`	`smooth_quant`	SmoothQuant smooth quantization processor configuration.	smooth_quant Configuration Reference
`SVDResidualProcessorConfig`	`svd_res`	SVD residual (low-rank compensation) processor configuration.	svd_res Configuration Reference
`TrainableLinearQuantProcessorConfig`	`trainable_linear_quant`	Trainable linear quantization (TLQ) processor configuration.	trainable_linear_quant Configuration Reference
`UnaryAnalysisProcessorConfig`	`unary_analysis`	Unary (non-quantized) sensitivity analysis processor configuration.	unary_analysis Configuration Reference

3. Complete Configuration Reference¶

apiversion: modelslim_v1
spec:
  process:
  - type: group
    configs:
    - type: linear_quant
      qconfig:
        act:
          dtype: int8
          scope: per_tensor
          symmetric: false
          method: minmax
        weight:
          dtype: int8
          scope: per_channel
          symmetric: true
          method: minmax
      include:
      - '*self_attn*'
    - type: linear_quant
      qconfig:
        act:
          dtype: int8
          scope: per_token
          symmetric: true
          method: minmax
        weight:
          dtype: int8
          scope: per_channel
          symmetric: true
          method: minmax
      include:
      - '*mlp*'
      exclude:
      - '*gate*'