o Ti-9 @sddlZddlmZmZmZmZmZmZddlTddl m Z zddl m Z Wney:ZzdZ WYdZ[ndZ[wwddZd d Zdd d Zdd dZddZdddZddZddZddZdejjfddZdS) N)Embedding_CompressLinearLayer_CompressConv2dLayer_CompressBNLayer_CompressColumnParallelLinear_CompressRowParallelLinear_Compress)*)logger)prunercCs&|d}|}|D]}t||}q |S)z Recursively get the attribute of a module. Args: model (`torch.nn.Module`) The model to get the attribute from. module_name (`str`) The name of the module to get the attribute from. .)splitgetattr)model module_name split_listoutputnamerP/home/ubuntu/.local/lib/python3.10/site-packages/deepspeed/compression/helper.pyrecursive_getattrs  rcCs>|d}|}|ddD]}t||}q ||d|dS)a: Recursively set the attribute of a module. Args: model (`torch.nn.Module`) The model to set the attribute in. module_name (`str`) The name of the module to set the attribute in. module (`torch.nn.Module`) The module to set the attribute to. r N)r r __setattr__)rrmodulerrrrrrrecursive_setattr!s  rc Cs^t||}d}t|dr|jdurd}t|tst|tjjrJt|tr(|}nUt|j|j |dj |j j |j j d}|j j|j _|rH|jj|j_n3t|tsVt|tjjrt|tr_|}nt|j|j|j|j|j|j|j||j j |j j |j j d}|j j|j _|r|jj|j_nt|tjjrt|j|j|j|j|j |j j |j j }|j j|j _|r|jj|j_|j j|j _|j!j|j!_nt|t"st|tjj#rt|t"r|}nt"|j$|j%|j&|j'|j(|j)|j*j |j j |j j d}|j j|j _n|dur9t|t+s t||j,r9t|t+r|}nkt+||j-|j.|j/|j0|dj |j j |j j d}|j j|j _|r8|jj|j_nD|dur{t|t1sKt||j2r{t|t1rT|}n)t1||j-|j.|j3|j0|dj |j j |j j d}|j j|j _|rz|jj|j_nd}|dur'|4D]\}}|t5kr|t6r|7|t8|t9q|t:kr|t;r|<|t=|t>q|t?kr|t@r|A|tB|tC|tDq|tEkr|tFr|G|tH|tI|tJq|tKkr |tLr|M|tN|tO|tP|tQ|tR|tSq|tTkr |tUr|V|tW|tXqtYd Z|t[|||dS) a; Replace a module with a new module. Args: model (`torch.nn.Module`) The model to replace the module in. module_name (`str`) The name of the module to replace. compression_technique (`str`) The compression technique to use for the new module. FbiasNTr)devicedtype) gather_output skip_bias_addr)input_is_parallelr rz+Compression technique {} is not implemented)\rhasattrr isinstancertorchnnLinear in_features out_featurestoweightrrdatarConv2d in_channels out_channels kernel_sizestridepaddingdilationgroups padding_mode BatchNorm2dr num_featuresepsmomentumaffinetrack_running_stats running_mean running_varr Embeddingnum_embeddings embedding_dim padding_idxmax_norm norm_typescale_grad_by_freqsparserColumnParallelLinear input_size output_sizerr rRowParallelLinearr!itemsSPARSE_PRUNINGSPARSE_PRUNING_ENABLEDenable_sparse_pruningSPARSE_PRUNING_DENSE_RATIOSPARSE_PRUNING_METHOD ROW_PRUNINGROW_PRUNING_ENABLEDenable_row_pruningROW_PRUNING_DENSE_RATIOROW_PRUNING_METHOD HEAD_PRUNINGHEAD_PRUNING_ENABLEDenable_head_pruningHEAD_PRUNING_DENSE_RATIOHEAD_PRUNING_METHODHEAD_PRUNING_NUM_HEADSACTIVATION_QUANTIZATIONACTIVATION_QUANTIZATION_ENABLEDenable_activation_quantizationACTIVATION_QUANTIZE_BITSACTIVATION_QUANTIZE_TYPEACTIVATION_QUANTIZE_RANGEWEIGHT_QUANTIZATIONWEIGHT_QUANTIZE_ENABLEDenable_weight_quantizationWEIGHT_QUANTIZE_START_BITSWEIGHT_QUANTIZE_TARGET_BITSWEIGHT_QUANTIZATION_PERIOD"WEIGHT_QUANTIZE_IN_FORWARD_ENABLEDWEIGHT_QUANTIZE_TYPEWEIGHT_QUANTIZE_GROUPSCHANNEL_PRUNINGCHANNEL_PRUNING_ENABLEDenable_channel_pruningCHANNEL_PRUNING_DENSE_RATIOCHANNEL_PRUNING_METHODNotImplementedErrorformatr) rrcompression_techniquempu old_module need_bias new_modulekvrrrmodule_replacement3s                                    rwcCs`t|tjjpt|tjjpt|tjjpt|tjj}|dur.|p-t||jp-t||j}|SN) r#r$r%r&r,r=r5rHrE)rrqretrrris_module_compressibles   rzc Cs^|D]\}}t||rt|||dq|D]\}}}|D] }|D]}t|||q"qq|S)a+ Prepare the compression techniques of a model. Args: model (`torch.nn.Module`) The model to prepare the compression techniques of. compression_technique_list (`list`) The list of compression techniques to prepare the model to. list[] )rq) named_modulesrzrw) rcompression_technique_listrqrrmodule_name_lists_rpmnlrrrcompression_preparations rFcCst||}|D]f\}}|tkr|tr|tr|S|tkr-|tr-|S|t krB|t s9|durB|j ||dS|t krZ|t sN|durZ|j||t|dS|tkro|tsf|duro|j||dSq dS)aa Fix the compression technique of a module. Args: model (`torch.nn.Module`) The model to fix the compression technique of. module_name (`str`) The name of the module to fix the compression technique of. compression_technique (`str`) The compression technique to fix the module to. N) dim_reduction)rrIr`rfrafix_weight_quantizationrJrKfix_sparse_pruning_helperrOrPfix_row_col_pruning_helperrTrUfix_head_pruning_helperrYrirjfix_channel_pruning_helper)rrrpmaskrrrurvrrrfix_compressions   rcCst|dr |j}n|}|D]F\}}t||rUt||}tjj|jj d|jj d|j dur3dndd}|jj |j_ |j durO|j j d|j _ t|||q|S) zZ This is a help function to convert conv1d to linear (e.g., convert GPT2 from HF) rrrNTFrr)r"rr{r#rr$r%r&r*r+sizert contiguousviewr)r convert_typec_modelrrrrrtrrrconvert_conv1d_to_linears      rc CstdusJdddlm}m}ddlm}t|tjj sJ||}g}|D]0}|||}|ikr7t d| |||dd| D|d <t|d |d <t |q'|S) zGenerate pruners. Args: config (`neural_compressor.WeightPruningConfig`) The object to the class WeightPruningConfig. model (`torch.nn.module`) The torch module object to be pruned. Nzplease ensure the neural_compressor python package is installed by pip or conda if user wants to use snip_momentum sparse pruningr)process_configparse_to_prune) get_prunerz/one pruner hooks no layers, please have a checkcSsg|]}|qSrr).0keyrrr sz$generate_pruners..moduleslen_of_modules) nc_prunernc_pruner.utilsrrnc_pruner.prunersrr#r$r%Moduler warningappendkeysleninfo) configrrrr pruners_infoprunersrrrrrgenerate_prunerss    rcCsdd}||}|S)zMount on_step_begin to the model. Args: model (`torch.nn.module`) The torch module object to be pruned. cSs|jD]}|dqdS)Nr)r on_step_begin)rinputr rrrhook"s  z$register_on_step_begin..hook)register_forward_pre_hook)rr hook_handlerrrregister_on_step_begins roptcCs,ddd}|j|_ddl}||||_|S)zMount on_before/after_optimizer_step to the optimizer. Args: model (`torch.opt.Optimizer`) The torch optimizer object to be hooked. NcSs\t|dr|jD]}|q|dur||}n|}t|dr,|jD]}|q%|S)Nr)r"ron_before_optimizer_step orig_stepon_after_optimizer_step)selfclosurer resrrrnew_step1s       z(rewrite_optimizer_step..new_steprrx)steprtypes MethodType)rrrrrrrewrite_optimizer_step*s r)NNrx)NF)r$ basic_layerrrrrrr constantsdeepspeed.utilsr neural_compressor.compressionr r ImportErrorerrrwrzrrrrroptim Optimizerrrrrrs(    z