Class QuantizationSetting

ppq/api/setting.py:333–400

class QuantizationSetting():
    def __init__(self) -> None:
        # 子图切分与调度算法，可从 'pointwise', 'conservative', 'pursus', 'allin', 'pplnn' 中五选一，不区分大小写
        self.dispatcher                      = 'conservative'

        self.graph_format_setting            = GraphFormatSetting()

        # ssd with loss check equalization 相关设置
        # may take longer time(about 30min for default 3 iterations), but guarantee better result than baseline
        # should not be followed by a plain equalization when turned on
        self.ssd_equalization                = False
        self.ssd_setting                     = SSDEqualizationSetting()

        # layer wise equalizition 与相关配置
        self.equalization                    = False
        self.equalization_setting            = EqualizationSetting()

        self.weight_split                    = False
        self.weight_split_setting            = WeightSplitSetting()

        # OCS channel split configuration
        self.channel_split                   = False
        self.channel_split_setting           = ChannelSplitSetting()

        # Matrix Factorization Split. (Experimental method)
        self.matrix_factorization            = False
        self.matrix_factorization_setting    = MatrixFactorizationSetting()

        # activation 量化与相关配置
        self.quantize_activation             = True
        self.quantize_activation_setting     = ActivationQuantizationSetting()

        # 参数量化与相关配置
        self.quantize_parameter              = True
        self.quantize_parameter_setting      = ParameterQuantizationSetting()

        # 是否执行网络微调
        self.lsq_optimization                = False
        self.lsq_optimization_setting        = LSQSetting()


        self.blockwise_reconstruction         = False
        self.blockwise_reconstruction_setting = BlockwiseReconstructionSetting()

        # 是否启动 bias correction pass
        self.bias_correct                    = False
        self.bias_correct_setting            = BiasCorrectionSetting()

        # 量化融合相关配置
        self.fusion                          = True
        self.fusion_setting                  = QuantizationFusionSetting()

        # extension setting 只是一个空白的占位符，用来向你展示如何创建一个自定义的 setting 并传递参数。
        # extension setting shows you how to create a setting and pass parameter to passes.
        # see ppq.quantization.quantizer.base.py
        self.extension                       = False
        self.extension_setting               = TemplateSetting()