o h @sdZddlZddlZddlmZddlmZddlm Z gdgdgddZ d e d e fd d Z d e d e fd dZddZedkrGedSdS)zB Utils for training and evaluating multiple models simultaneously N)main)DEFAULT_BATCH_SIZE) @i) )i,iiXfull) lstm_layer upos_emb_dim training_size num_models base_pathc Cs|jdkr-tddD]!}t|D]}tj||d|d}||_||_t |dqq |jdkrZtddD]"}t|D]}tj|d|d|d}||_||_ t |dq=q7|jdkrtddD].}t|D]'}tj||d|d}tjtj t d d d }||_||_ t |dqkqe|jd krt|D]1}tj|d |d}||_d|_t |d|jsd|_tj|d|d}||_t |dq|jdkrt|D]}tj|d|d}||_t |dq|jdkrt|D]}tj|d|d}||_t |dq|jdkr/t|D]}tj|d|d}||_t |dq|jdkrTt|D]}tj|d|jd|d}||_t |dq9dSdS)Nr_.ptpredefined_argsrdim_r _examples_dataprocessed_ud_encombined_train.txtbase lstm_model_FTlstm_model_wloss_ base_charlm lstm_charlm_base_charlm_uposlstm_charlm_upos_ base_upos lstm_upos_ attn_model attn_model__heads_) change_paramchange_params_mapgetrangeospathjoin save_name hidden_dimtrain_lstm_mainrdirname__file__ train_file weighted_loss num_heads) rrargs num_layersi new_save_nameupos_dimsizenew_train_filer?d/var/www/html/env_mimamsha/lib/python3.10/site-packages/stanza/models/lemma_classifier/train_many.pytrain_n_modelssv                       rAcCs|jdkrot|D]g}|jdkr=tj|d|d}||_d|_t|dtj|d|d}||_d|_t|dq |jd krntj|d |d}||_d|_t|dtj|d |d}||_d|_t|dq dSdS) Ntfmrbertbert_rcer bert_wloss_ weighted_bcerobertaroberta_roberta_wloss_) multi_train_typer,r)r-r.r/r0loss_fntrain_tfmr_main)rrr8r:r;r?r?r@ train_n_tfmrsSs.        rNc Cst}|jdtddd|jdttjtjt dddd|jd d d d d d|jdtddd|jdttjtjt dddd|jdttjtjt dddd|jdtddd|jdd dd dd|jdtdd d|jd!ttjtjt d"d#d$d|jd%t d&d'd|jd(t d)d*d|jd+tt d,d|jd-ttjtjt d.d/d0d1d|jd2d d3d d4d|jd5ttjtjt d.d/d6d7d|jd8td9d:d|jd;tddd?d|jd@tdAdBd|jdCtdDdEd|jdFtddGd|jdHtddId| }|j dAkr)t|j|j|dJdS|j dKkr:t|j|j|dJdStdL|j )MNz --hidden_dimrzSize of hidden layer)typedefaulthelpz--wordvec_pretrain_filepretrainzglove.ptz'Exact name of the pretrain file to readz--charlm store_true use_charlmFz(Whether not to use the charlm embeddings)actiondestrPrQz--charlm_shorthandz=Shorthand for character-level language model training corpus.z--charlm_forward_file charlm_filesz1billion_forward.ptzPath to forward charlm filez--charlm_backward_filez1billion_backwards.ptzPath to backward charlm filez--upos_emb_dimr z'Dimension size for UPOS tag embeddings.z --use_attnattnz3Whether to use multihead attention instead of LSTM.z --num_headsrz/Number of heads to use for multihead attention.z --save_name saved_modelsz2lemma_classifier_model_weighted_loss_charlm_new.ptzPath to model save filez--lrgMbP?z learning ratez --num_epochsr zNumber of training epochsz --batch_sizez+Number of examples to include in each batchz --train_filerrrzFull path to training filez--weighted_lossr6z-Whether to use weighted loss during training.z --eval_filezcombined_dev.txtz1Path to dev file used to evaluate model for savesz --model_typerHz.Which transformer to use ('bert' or 'roberta')z --bert_modelz>Use a specific transformer instead of the default bert/robertaz --loss_fnrGz?Which loss function to train with (e.g. 'ce' or 'weighted_bce')z--multi_train_typelstmz@Whether you are attempting to multi-train an LSTM or transformerz--multi_train_countr zNumber of each model to buildz --base_pathz(Path to start generating model type for.z--change_paramz,Which hyperparameter to change when training)rrr8rBzImproper input )argparseArgumentParser add_argumentintstrr-r.r/r3r4floatr parse_argsrKrAmulti_train_countrrN ValueError)parserr8r?r?r@rpsH&&&&((   r__main__)__doc__r[r-/stanza.models.lemma_classifier.train_lstm_modelrr26stanza.models.lemma_classifier.train_transformer_modelrM(stanza.models.lemma_classifier.constantsrr*r^r_rArN__name__r?r?r?r@s    @*