ёi'SS/S//SS/S//SS/S//SS/S//SS/S//SS/S//S.r0SSS/S//_SSS/S//_S SS/S//_S S/S//_S SS/S//_S S/S//_S S/S//_SS/S//_SS/S//_SSS/S//_SS/S//_SSS/S//_SSS/S//_SSS/S//_SSS/S//_SS/S//_SSS/S//_0SS/S//_SS/S//_SS/S//_SS/S//_SS/S//_SS/S//_SS/S//_SSS/S//_S S/S//_S!S/S//_S"S/S//_S#SS$/S//_S%S/S//_S&S/S//_S'S/S//_S(S/S//_S)S/S//_E0S*S/S//_S+SS/S//_S,SS/S//_S-S/S//_S.S/S//_S/SS0/S1//_S2SS0/S1//_S3S/S//_S4S/S//_S5S/S//_S6S/S//_S7S/S//_S8S/S//_S9S/S//_S:S/S//_S;S/S//_SS/S//_S?S/S//_S@S/S//_SAS/S//_SBS/S//_SCS/S//_SDSE/SF//_SGS/S//_SHS/S//_SIS/S//_SJS/S//_SK/S//_SLS/S//_SMS/S//_SNSOSP/S//_SQSOSP/S//_E0SRS/SS//_STS/S//_SUS/S//_SVS/S//_SWS/S//_SXS/SSY//_SZSS/S//_S[S/S//_S\S/S//_S]SS^/S//_S_S/S//_S`/SaQS//_SbSSc/S//_SdS/S//_SeS//SfQ/_SgS/S//_ShS/S//_ES/S//S/S//S/S//S/S//Si.Er\R5r\R \5 "SjSk5r"SlSm\5r"SnSo\5rgp)qInputFilterOutputXYOut)conv2ddepthwise_conv2dconv2d_transposemulmatmul matmul_v2r r r pool2delementwise_addconcatsoftmaxargmax transposeequalgather greater_equal greater_than less_equal less_thanmean not_equalreshapereshape2 transpose2nearest_interptrilinear_interpslicesqueezeelementwise_subrelurelu6 leaky_relupreluAlphatanhswishdropout batch_norm layer_normsigmoidelementwise_mulelementwise_pow hard_swish hard_sigmoidgruWeightHiddenlstmpad2dpad3dflattenflatten2 unsqueeze2flatten_contiguous_rangesplitsqueeze2nearest_interp_v2bilinear_interpbilinear_interp_v2fill_constant_batch_size_likearg_maxabsassigncastclip box_coderPriorBox OutputBoxcropcumsum expand_v2 fill_any_like fill_constantgelu instance_norm lookup_tableWIdslookup_table_v2normNormp_normpow reduce_meanstacktop_k_v2Indices logical_and logical_notmeshgrid roi_alignROIs strided_slicewhere) Conditionrr grid_samplerGridtile group_norm)rMeanVariance reduce_sumsquare)softplusshuffle_channel reduce_maxscalecV\rSrSrSr/S4Sjr\S5r\S5r\S5r Sr g ) BaseQuantizera[ Basic quantization configuration class, which configures some hyperparameters required for quantization, including the list of op types to be quantized, quantization bit number for weight and activation and the range of quantization values. Args: quantizable_op_type(list[str], optional): List the type of ops that will be quantized. Default is []. If quantizable_op_type is [], it will use the default quantization op type of the qunat config in the current Quantizer. quant_bits(int, optional): Quantization bit number for weight and activation. Default is 8. c8XlX lSUlSUlgNirt)_quantizable_op_type _quant_bits _quant_min _quant_max)selfquantizable_op_type quant_bitss g/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/static/quantization/quant_config.py__init__BaseQuantizer.__init__s %8!%c[[R55nUR(a//nURHnX1;dM UR U5 M U$U$)z{ Operation type list which should support weight quantization. And before these ops, quant dequant nodes will be inserted. )list#SUPPORT_WEIGHT_QUANTIZATION_OP_DICTkeysrxappend)r|base_weight_op_type_list weight_list_op_types rweight_quant_operation_types*BaseQuantizer.weight_quant_operation_typess] $( / 4 4 6$    $ $K 557&&x06 + +rc[[R55n/nUR(a-URHnX1;dM UR U5 M U$/SQnU$) Operation type list which should support activation quantization. And before these ops, quant dequant nodes will be inserted. )r r r )r SUPPORT_ACT_QUANTIZATION_OP_DICTrrxr)r|base_act_op_type_listact_quant_op_listrs r activation_quant_operation_types.BaseQuantizer.activation_quant_operation_typessd !%%E%J%J%L M  $ $ 554%,,X66! !  ! rc<[[R55$)a- Operation type list for observer in quantization. These nodes only count the calibration boundary scale and do not participate in the fake quantization. In order to facilitate the deployment of the prediction engine, quant and dequant nodes will be inserted after these ops when exporting the model. )rrrr|s robserver_operation_types&BaseQuantizer.observer_operation_typess499;<[TU]5 XlX lSUlSUlgrwsuperrrxryrzr{r|r}r~ __class__s rrTensorRTQuantizer.__init__* $7!%rc /SQ$)r)!rrr#r/r0rrrrr$r%r&r)r*rnrPr2r1r.r-r r=r@rr r?r@rArGrYrZrlrprrs rr2TensorRTQuantizer.activation_quant_operation_typess " " rr) rrrrrrrrr __classcell__rs@rrrs)  ' ' rrc4^\rSrSrSr/S4U4SjjrSrU=r$)ARMCPUQuantizeri a ARM CPU with Paddle Lite quantization configuration class. Args: quantizable_op_type(list[str], optional): List the type of ops that will be quantized. Default is []. If quantizable_op_type is [], it will use the default quantization op type of the qunat config in the current Quantizer. quant_bits(int, optional): Quantization bit number for weight and activation. 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