o }oiZ@s|ddlmZmZddlZddlmZmZmZddlm Z Gddde Z Gddde Z Gd d d e Z Gd d d e ZdS) )OptionalTupleN)add_self_loopscompose_with_self_loopsintersect_with_self_loops)k2c @sheZdZdZddedfdedededed ejf d d Z d ejfd d Z dej dej ddfddZ dS)CtcTopologyCompilerzDefault graph compiler. It applies its topology to the input token sequence to compile the supervision graph. Based on https://github.com/k2-fsa/snowfall/blob/master/snowfall/training/ctc_graph.py defaultTcpu num_classesblank topo_typetopo_with_self_loopsdevicecCsT||_||_ddlm}t||tt||||j|_ t|j |_ dS)Nr) build_topo) r r(nemo.collections.asr.parts.k2.topologiesrrarc_sortlistrangeto base_graphinvert ctc_topo_inv)selfr r r rrrra/home/ubuntu/.local/lib/python3.10/site-packages/nemo/collections/asr/parts/k2/graph_compilers.py__init__-s zCtcTopologyCompiler.__init__cCs0|j||_|jdur|j||_||_dSN)rrrrrrrrrr>s  zCtcTopologyCompiler.totargetstarget_lengthsreturnk2.FsacCs^ddt||D}t||j}|j|_t|j |}t ||j}| d|S)NcSs g|] \}}|d|qSr)tolist).0tlrrr Es z/CtcTopologyCompiler.compile..F) zipr linear_fsarrlabelsclone aux_labelsrrrrequires_grad_)rrr token_ids_list label_graphsupervision_graphsrrrcompileDs   zCtcTopologyCompiler.compileN) __name__ __module__ __qualname____doc__torchrintstrboolrrTensorr1rrrrr&s$  rcszeZdZdZddeddfdededed ed ejd e d f fd d Z ddej dej d e d dd ffdd Z Z S)CtcNumGraphCompilerzGraph compiler with auxiliary graph to compose with the topology. The supervision graph contains the auxiliary graph information. r Tr Nr r r rr aux_graphr"csht||||||durt|jg|j|_dSt |j| |_ t |j |j|_ dSr) superrrcreate_fsa_vecrrrrdecoding_graphrinvert_rrrr r r rrr< __class__rrrUs   zCtcNumGraphCompiler.__init__rr r!csf|dur|jdurtd|d|j|dur,t|j||_t|j|j|_t ||S)Nz;At least one of aux_graph and self.base_graph must be set: , ) r ValueErrorrrrrrrrr=r1)rrr r<rBrrr1eszCtcNumGraphCompiler.compiler)r2r3r4r5r6rr7r8r9rrr:r1 __classcell__rrrBrr;Ps:r;cseZdZdZddeddfdededed ed ejd e d f fd d Z d ejffdd Z ddej dej d e d de dffdd ZZS)MmiGraphCompilerzGraph compiler for MMI loss. The decoding graph is a composition of the auxiliary graph and the topology. It is returned along with the supervision graph on every compile() call. r Tr Nr r r rrr<r"cs^t|||||||durt|jg|j|_dSt|j g|j|_dSr) r=rrr>rrrrr?rdetachrArBrrrxs   zMmiGraphCompiler.__init__cs(|jdur |j||_t|dSr)r?rr=rrBrrrs zMmiGraphCompiler.torr r!)r"r"csft|||}|dur|jdurtd|d|j|dur.t|jg|j |_||jfS)Nz?At least one of aux_graph and self.decoding_graph must be set: rD) r=r1r?rErr>rrHrr)rrr r<r0rBrrr1s zMmiGraphCompiler.compiler)r2r3r4r5r6rr7r8r9rrrr:rr1rFrrrBrrGrs< rGc sjeZdZdZddeddfdededed ed ejd ef fd d Z dej dej ddffdd Z Z S)RnntTopologyCompileraDefault graph compiler for RNNT loss. Each supervision graph is composed with the corresponding RNNT emission adapter. If max_adapter_length is provided, the maximum adapter length is limited. Note: The actual number of classes is `num_classes` + 1 with as the class 0. Warning: It is currently not recommended to use topologies other than "minimal". minimalTr rr r r rrmax_adapter_lengthcsP|dkrtdt|||||ddlm}||_|tt||||_dS)Ncompactz4This compiler does not support topo_type==`compact`.r)RnntEmissionAdapterBuilder) NotImplementedErrorr=rrrMrKrr_builder)rr r r rrrKrMrBrrrs   zRnntTopologyCompiler.__init__rr r!r"csltt|||jjd}||jdkr&|j|kr&t||jk|j|n|j |j d}t j ||ddS)Ninputr)rF)treat_epsilons_specially) rr=r1rOeps_numrKmaxr6whererrr intersect)rrr r0adaptersrBrrr1szRnntTopologyCompiler.compile) r2r3r4r5r6rr7r8r9rr:r1rFrrrBrrIs(&rI)typingrrr6#nemo.collections.asr.parts.k2.utilsrrrnemo.core.utils.k2_guardrobjectrr;rGrIrrrrs *"'