o }oi'w@sddlZddlZddlmZmZmZmZmZddlZ ddl Z ddl m m Zddl mZmZgdZGdddeZGdddeZGd d d eZdS) N)AnyListOptionalTupleUnion)DatasetIterableDataset) ConcatDatasetConcatMapDatasetCodeSwitchedDatasetcseZdZdZ        ddeed ed ed ed ed ee de ededeffdd Z ddZ ddZ ddZeddZeddZeddZZS) r a A dataset that accepts as argument multiple datasets and then samples from them based on the specified sampling technique. Args: datasets (list): A list of datasets to sample from. shuffle (bool): Whether to shuffle individual datasets. Only works with non-iterable datasets. Defaults to True. sampling_technique (str): Sampling technique to choose which dataset to draw a sample from. Defaults to 'temperature'. Currently supports 'temperature', 'random' and 'round-robin'. sampling_temperature (int): Temperature value for sampling. Only used when sampling_technique = 'temperature'. Defaults to 5. sampling_scale: Gives you the ability to upsample / downsample the dataset. Defaults to 1. sampling_probabilities (list): Probability values for sampling. Only used when sampling_technique = 'random'. seed: Optional value to seed the numpy RNG. global_rank (int): Worker rank, used for partitioning map style datasets. Defaults to 0. world_size (int): Total number of processes, used for partitioning map style datasets. Defaults to 1. T temperatureNrdatasetsshufflesampling_techniquesampling_temperaturesampling_scalesampling_probabilitiesseed global_rank world_sizec stgd} ||_dgt||_||_||_| |_i|_||_ |dkr6t j |_ ||jd<||jd<n1|dkrVt j |_ |rB|n dt|gt||jd<||jd<n|dkr_t j|_ ntd| d d |_t|d trud |_nd |_t|D]5\} } t| t} | r|jd kr| s|jd krtd |jd kr|jt| | 7_q||jt| 7_q||j dkrt|j|j |_td|d|jdSdS)N)r random round-robinr rrrprz1Currently we only support sampling techniques in .riterablemapzIAll datasets in ConcatDataset must be of the same kind (Iterable or Map).z applying z sampling scale, concat ds len: )super__init__rlen iterablesrrrsampling_kwargsrr temperature_generatorindex_generatorrandom_generatorround_robin_generator ValueErrorlength isinstancerkind enumerateintlogginginfo)selfrrrrrrrrrsupported_sampling_techniquesidxdataset isiterable __class__X/home/ubuntu/.local/lib/python3.10/site-packages/nemo/collections/common/data/dataset.pyr/sH        zConcatDataset.__init__cCs:t|tr |Stt|}|jrtj|t|SN) r)r__iter__nparanger rriter)r/r2indicesr6r6r7 get_iterableis  zConcatDataset.get_iterableccst}|dur|j}d}d}n|j}|j}tt||j|}|jdkrktt|jD]>}t|j||j |j }|t|j||j }|j |j dkrVt|j|}t||||}t |j|||j|<q,t |jD]\}} | | } | |j|<qpd} |j|jfi|j} | |kr| d7} zt| } Wn tyYdSwzt|j| }|jdkr|j| |}|VWnty| |j| |j| <| d8} Ynw| |ksdSdSNrrr)pt_dataget_worker_infor(id num_workersr ranger*rrrSubsetr+r>r!r$r"next StopIteration)r/ worker_info max_elementswidwnumr1 start_idxend_idxr=r2rnind_genindvalr6r6r7r9rsN         zConcatDataset.__iter__cC|jSr8r(r/r6r6r7__len__zConcatDataset.__len__c ks|d}|s td|dd}tj|}g}t|}|D] }|t|q t|t|}t |d|}|t|} |j t ||d} | VqD)Nr z?Temperature generator expects a 'temperature' keyword argument.rrTr) getr'r:r RandomStater appendarraysumpowerchoicer;) rkwargstemprnp_rnglengthsnumr2rrPr6r6r7r#s"   z#ConcatDataset.temperature_generatorcks"t|} t|D]}|Vq qr8)r rD)rr_rcir6r6r7r&s  z#ConcatDataset.round_robin_generatorcksj|d}|s td|dd}tj|}t|}t||kr&td |jt||d}|Vq')NrzKRandom generator expects a 'p' keyowrd argument for sampling probabilities.rzELength of probabilities list must be equal to the number of datasets.TrW)rXr'r:rrYr r^r;)rr_rrrarcrPr6r6r7r%s    zConcatDataset.random_generator)Tr r rNNrr)__name__ __module__ __qualname____doc__rrboolstrr,floatrrr>r9rU staticmethodr#r&r% __classcell__r6r6r4r7r sL  : )  r c s`eZdZdZ    ddeedededeee d eef fd d Z d d Z ddZ Z S)r a A dataset that accepts as argument multiple datasets and then samples from them based on the specified sampling technique. Args: datasets (list): A list of datasets to sample from. sampling_technique (str): Sampling technique to choose which dataset to draw a sample from. Defaults to 'temperature'. Currently supports 'temperature', 'random' and 'round-robin'. sampling_temperature (int): Temperature value for sampling. Only used when sampling_technique = 'temperature'. Defaults to 5. sampling_probabilities (list): Probability values for sampling. Only used when sampling_technique = 'random'. seed: Optional value to seed the numpy RNG. r r Nrrrrrcst|_ddjD_|_|_|_tj |_ g_ dgt j}fddjD}jdkrt jt j}t|t j} | D]7} || } || | } j | | f|| d7<|| t || krd|| <j t j| || <qQdSjdkr|dust |t jkrtdt jd |durt |d tj} n!jd krtd djD} t| dj} ntd || t| } tt j}t}t |t jkrGj j|| d} j| }|| } || | } j | | f|| d7<|| t |kr<j t ||| <d|| <|| t |t jksdSdS)NcSg|]}t|qSr6r .0xr6r6r7 z-ConcatMapDataset.__init__..rcsg|] }jt|qSr6)ra permutationr rprTr6r7rsrrrzNeed z probabilities; got Noner cSrnr6rorpr6r6r7rsrtz'Couldn't interpret sampling technique: )ar)rrrrbrrrr:rrYrar=r maxr;rZrur'r[r]r\setr^add)r/rrrrrdataset_positionsshuffled_indices total_length dataset_ids dataset_idpositionindexrchoicesexhausted_datasetsr2r4rTr7rsj        zConcatMapDataset.__init__cCs t|jSr8)r r=rTr6r6r7rU!s zConcatMapDataset.__len__cCs|j|\}}|j||Sr8)r=r)r/r1r dataset_indexr6r6r7 __getitem__$szConcatMapDataset.__getitem__)r r NN)rerfrgrhrrrjr,rrkrrUrrmr6r6r4r7r s& Gr c(seZdZdZ              d.d eed eeedede de dedede de de dee eeefdee de de dededede dedf&fd d! Z d"d#Z d$d%Z d&d'Zd(d)Zd*d+Zd,d-ZZS)/r a A dataset that accepts as argument multiple sub-datasets (usually from different languages, but that's not required) and then samples from them in order to create synthetic code-switched samples of up to N different sub-datasets Args: datasets (list): A list of datasets lang_probs (list): A list of probabilities (which must sum to 1) corresponding to the sampling probability for each dataset shuffle (bool): Whether to shuffle individual datasets. Only works with non-iterable datasets. Defaults to True. min_duration (int): the minimum duration (secs) of each synthetic code-switched sample. Will draw randomly until this is hit. Defaults to 4 max_duration (int): the maximum duration (secs) of each synthetic code-switched sample. Defaults to 20 min_monolingual (float): this percentage of the dataset will be original monolingual samples Defaults to 0.3 - means 30% db_norm (float): will normalise the composite CS sample to this DB level Defaults to -25.0 pause_start (int): inserts silence equal to this value (msecs) at the start of each CS sample Defaults to 0 pause_join (int): inserts silence equal to this value (msecs) between all language changes in the CS sample Defaults to 0 pause_end (int): terminates all CS samples with silence equal to this value (msecs) Defaults to 0 sampling_scales (list or float): gives you the ability to upsample/downsample each individual dataset seed: Optional value to seed the numpy RNG. global_rank (int): Worker rank, used for partitioning map style datasets. Defaults to 0. world_size (int): Total number of processes, used for partitioning map style datasets. Defaults to 1. pure_random (bool): If true, then always draw random sample from lang_probs. If false, you only draw from those datasets which you haven't sampled from yet for the composite sample force_monochannel (bool): If true, then all output audio will be mono-channel infinity_mode (bool): If true, then the dataset iterable will generate an infinite amount of samples sample_rate (int): the sample rate of all audio being sent to this Dataset augmentor (AudioAugmentor): The any perturbations you wish to have applied on the CS samples NT333333?9rrF>r lang_probsr min_duration max_durationmin_monolingualdb_norm pause_start pause_join pause_endsampling_scalesrrr pure_randomforce_monochannel infinity_mode sample_rate augmentorAudioAugmentorcstt|dkrtd|_ttt|_tj_ ddjD_ ddjD_ |_ |_ |_|_|_|_| _| _|_|_|_| _|_|_|_d_dursfddjD_ntjtksJdfddjD_ttj_ durt!tsfd djD_"n(durt!trttjkrd dt#jD_"n d djD_"t$jD]8\}}t!|t%}|rd j |<jt&t|j"|7_qd j |<jt&t||j"|7_q| durtj'(| t)jjddr4jjdj*_*dSt)jjddryt!jjdjtrytjjdjdkryt)jjdjddryjjdjdj*_*dSt)jjddrt!jjdjtrtjjdjdkrt)jjdjddrt!jjdjdjtrtjjdjdjdkrt)jjdjdjddrjjdjdjdj*_*dSt+d)NrzGCodeSwitchedDataset must receive a non-zero length datasets dict objectcSi|]}|dqSr8r6rqkr6r6r7 kz0CodeSwitchedDataset.__init__..cSrr8r6rr6r6r7rlrcsi|] }|dtjqS)g?)r langsrqlrTr6r7r~rvzKSize mismatch between languages and respective probs in CodeSwitchedDatasetcsi|]}||qSr6r6r)rr6r7rcsi|]}|qSr6r6r)rr6r7rrcSsi|]\}}||qSr6r6)rqrvr6r6r7rrcSr)rr6rr6r6r7rrrr collate_fnrzJCodeSwitchedDataset could not locate a valid dataset collate_fn to bind to),rrr r'rlistrDrrz langs_setlang_iterables lang_kindrrrrrrrrrrrrrrrr( prob_dictr:r[valuesrr)rzipr+rr,rrhasattrr RuntimeError)r/rrrrrrrrrrrrrrrrrrrlangr2r3r4)rrr/r7rMs      " &  " $zCodeSwitchedDataset.__init__cCsD|j|}t|tr|Stt|}|jrtj|t |Sr8) rr)rr9r:r;r rrr<)r/rr2r=r6r6r7get_iterable_by_langs   z(CodeSwitchedDataset.get_iterable_by_langc Cstg}d}g}g}tj|jk}||jkr|jr|r0tt |dks0tt |t|j kr;tjj |j |j d}n(t tt|jjt|jt |}||}tjj t|jt ||d}||^}} } } } |dkrvqt||j} || |jkrq|j| jkr|| j}|jdkr|jr|jdd}|| 7}|||| tj!|| gdd}|rn||jkstt dd|D}t|dkrt"d|ddk}|rtj#t$|j%|jd |dj&df|dj'd }ntj#t$|j%|jd f|dj'd }t(|D]m\}}|st)|}|d |j*d t+d |djddd}|t|dkrt|r]tj|tj#t$|j,|jd |dj&df|j'd dd}ntj|tj#t$|j,|jd f|j'd dd}tj||dd}q|rtj|tj#t$|j-|jd |dj&df|j'd dd}ntj|tj#t$|j-|jd f|j'd dd}|j.durddl/}ddl0m1}t23}|j4|||jdd|5d|j6||jd}|j.7||j8}tj9||j'|jdtj9t|| jd:|tj9t|| jd:fS)NrrWr)dimcSsg|]}|jqSr6)ndim)rqsr6r6r7rsrz>CodeSwitchedDataset.build_single_CS_sample..zxMixture of audios with different number of channels in CodeSwitchedDataset. 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