o y“©ià ã @s´ddlmZmZmZddlmZmZddlmZdee ee fdee ee fdeeeeffdd„Z d ed ed edefd d „Z dee ee fdee ee fdefdd„Z dS)é)ÚListÚTupleÚUnion)ÚTensorÚtensor)Ú_edit_distanceÚpredsÚtargetÚreturnc Cs®t|tƒr|g}t|tƒr|g}tdƒ}tdƒ}tdƒ}tdƒ}t||ƒD]*\}}| ¡}| ¡} |t|| ƒ7}|t| ƒ7}|t|ƒ7}|tt| ƒt|ƒƒ7}q%||||fS)a½Update the wip score with the current set of references and predictions. Args: preds: Transcription(s) to score as a string or list of strings target: Reference(s) for each speech input as a string or list of strings Returns: Number of edit operations to get from the reference to the prediction, summed over all samples Number of words overall references Number of words overall prediction g)Ú isinstanceÚstrrÚzipÚsplitrÚlenÚmax) rr ÚtotalÚerrorsÚ target_totalÚ preds_totalÚpredÚtgtÚ pred_tokensÚ target_tokens©rúT/home/ubuntu/.local/lib/python3.10/site-packages/torchmetrics/functional/text/wip.pyÚ _wip_updates    rrrrcCs||||S)aNCompute the Word Information Perserved. Args: errors: Number of edit operations to get from the reference to the prediction, summed over all samples target_total: Number of words overall references preds_total: Number of words overall prediction Returns: Word Information Perserved score r)rrrrrrÚ _wip_compute7s rcCst||ƒ\}}}t|||ƒS)abWord Information Preserved rate is a metric of the performance of an automatic speech recognition system. This value indicates the percentage of characters that were incorrectly predicted. The lower the value, the better the performance of the ASR system with a Word Information preserved rate of 0 being a perfect score. Args: preds: Transcription(s) to score as a string or list of strings target: Reference(s) for each speech input as a string or list of strings Returns: Word Information preserved rate Examples: >>> from torchmetrics.functional import word_information_preserved >>> preds = ["this is the prediction", "there is an other sample"] >>> target = ["this is the reference", "there is another one"] >>> word_information_preserved(preds, target) tensor(0.3472) )rr)rr rÚreference_totalÚprediction_totalrrrÚword_information_preservedEs rN) ÚtypingrrrÚtorchrrÚ#torchmetrics.functional.text.helperrr rrrrrrrÚs$  ÿþ  ý"ÿþý