o }oi"@sddlmZddlmZmZmZddlZddlmZddl m Z m Z ddl m Z mZddlmZmZddlmZGd d d ejjZGd d d ee ZGd ddeeZdS))abstractmethod)AnyOptionalTupleN) DictConfig)CtcTopologyCompilerRnntTopologyCompiler) CtcK2Mixin RnntK2Mixin)get_tot_objf_and_finite_maskinvert_permutation)k2cseZdZdZe   ddedededeed ed e f fd d Z d e j de j de j de j de dee j ff ddZdddede j de e j e j ffddZd e j de j de j de j de e j e j ff ddZZS)MLLossa Maximum Likelihood criterion. It implements Connectionist Temporal Classification (CTC) loss, but can be extended to support other loss functions (ASG, HMM, RNNT, ...). Based on https://github.com/k2-fsa/snowfall/blob/master/snowfall/objectives/ctc.py cfg takes precedence over all optional parameters We keep explicit parameter setting to be able to create an instance without the need of a config. NdefaultT num_classesblank reductioncfg topo_typetopo_with_self_loopscs\t|dur|d|}|d|}||_||_||_||_||_|dk|_d|_ dS)Nrrcompact) super__init__getrrrrr pad_fsavecgraph_compilerselfrrrrrr __class__Y/home/ubuntu/.local/lib/python3.10/site-packages/nemo/collections/asr/parts/k2/ml_loss.pyr5s     zMLLoss.__init__ log_probstargets input_lengthstarget_lengthsreturnzk2.DenseFsaVecc Cs|||||\}}}}|||dddfjtjd}|||}~|j|jjkr2|j|j|dddfjtjd}|j||||}|||fS)zConverts input tensors to FST graphs: log_probs to supervision_graphs (DenseFsaVec) targets to supervision_graphs Can be overridden. Ndtyper) _prepare_log_probs_and_targets_maybe_normalize_gradientstotorchlong_prepare_emissions_graphsdevicercompile) rr"r#r$r% supervisionsemissions_graphsordersupervision_graphsr r r! _prepare_graphs_for_intersectionKs  "  z'MLLoss._prepare_graphs_for_intersectionr3r5r2cCst||ttjjd}~|jddd}~|t|dddfjtj d}t ||j \}}|j dkr<|| |fS| |fS) zvIntersects emissions_graphs with supervision_graphs and calculates lattice scores. Can be overridden. TF) log_semiringuse_double_scoresNrr(none) r intersect_denser-finfofloat32maxget_tot_scoresr r,r.r r)rr3r5r2latsnum_tot_scores tot_scores valid_maskr r r!_intersect_calc_scoreses""zMLLoss._intersect_calc_scoresc Cs>|jdusJ|||||\}}}||||\}} || fS)N)rr6rD) rr"r#r$r%r3r5r2scoresmaskr r r!forwardts  zMLLoss.forwardNrT)__name__ __module__ __qualname____doc__rintstrrrboolrr-Tensorrrr6rDrG __classcell__r r rr!r)sd   rc sFeZdZdZ   d dedededeed ed ef fd d Z Z S)CtcLossaRegular CTC loss with custom topologies. Available topologies: - `default`, with or without self-loops - `compact`, with or without self-loops - `shared_blank`, with or without self-loops - `minimal`, without self-loops cfg takes precedence over all optional parameters We keep explicit parameter setting to be able to create an instance without the need of a config. NrTrrrrrrcs4tj||||||dt|j|j|j|j|_dS)Nrrrrrr)rrrrrrrrrrr r!rs  zCtcLoss.__init__rH) rIrJrKrLrMrNrrrOrrQr r rr!rRs$rRcseZdZdZ     ddeded ed eed ed ed edeffdd Z de j de j de j de j de e j e j ff fdd Z ZS)RnntLossaRNNT loss with the `minimal` topology. If predictor_window_size is not provided, this loss works as regular RNNT. With predictor_window_size provided, it applies uniform pruning when compiling Emission FSAs to reduce memory and compute consumption. cfg takes precedence over all optional parameters We keep explicit parameter setting to be able to create an instance without the need of a config. NminimalTrrrrrrrpredictor_window_sizepredictor_step_sizec stj||||||d|dur"|d|}|d|}|d|}|dkr*td||_||_t|j|j|j |j |jd|_ dS)NrSrrWrXrUz4Only topo_type=`minimal` is supported at the moment.)max_adapter_length) rrrNotImplementedErrorrWrXrrrrrr) rrrrrrrrWrXrr r!rs.     zRnntLoss.__init__r"r#r$r%r&cs6|jdks|d|jdksJtj||||dS)NrrV)r"r#r$r%)rWsizerrG)rr"r#r$r%rr r!rGs"zRnntLoss.forward)NrUTrrV)rIrJrKrLrMrNrrrOrr-rPrrGrQr r rr!rTsF  #rT)abcrtypingrrrr- omegaconfr-nemo.collections.asr.parts.k2.graph_compilersrr)nemo.collections.asr.parts.k2.loss_mixinsr r #nemo.collections.asr.parts.k2.utilsr r nemo.core.utils.k2_guardr nnModulerrRrTr r r r!s   [!