o Si @sddlmZmZddlmZmZmZddlZddl Z ddl m Z ddl m Z mZeGddde Z  dd ejdededededededejfddZ  dd e jdedededededede jfddZdS))asdict dataclass)OptionalTupleUnionN)AudioTransform)Secondsis_module_availablec @seZdZUdZdZeed<dZeed<dZeed<dZ eed <dZ eed <d Z e ed <d e ejejfdejfddZdedeededeeeeffddZdS) DereverbWPEz Dereverberation with Weighted Prediction Error (WPE). The implementation and default values are borrowed from `nara_wpe` package: https://github.com/fgnt/nara_wpe n_fft hop_length tapsdelay iterationsfullstatistics_modesamplesreturncOs.t|r |}t|fit|}|SN)torch is_tensorcpunumpydereverb_wpe_numpyr)selfrargskwargs augmentedr"K/home/ubuntu/.local/lib/python3.10/site-packages/lhotse/augmentation/wpe.py__call__s  zDereverbWPE.__call__offsetduration sampling_ratecCs||fSrr")rr%r&r'r"r"r#reverse_timestamps"szDereverbWPE.reverse_timestampsN)__name__ __module__ __qualname____doc__r int__annotations__rrrrrstrrnpndarrayrTensorr$rrrr(r"r"r"r#r s,        r r r rrraudior rrrrrrc Cstdstdddlm}|jdksJd|jt|}tjt |||d|d} | d dd } || ||||d } tj t |  d dd|||d  } | S) z Applies WPE-based dereverberation using nara_wpe's wpe_v8 function with numpy backend. The parameter defaults follow the ones in nara_wpe. nara_wpeVPlease install nara_wpe first using 'pip install git+https://github.com/fgnt/nara_wpe'r)wpe_v8zExpected 2D audio shape, got: Tr rreturn_complexwindowrrrrr rr:) r ImportError nara_wpe.wper6ndimshaperblackman_windowstft from_numpypermuteristft) r3r rrrrrr6r:YZzr"r"r#r(s>   rc Cstdstdddlm}|jdksJt|}tj|||d|d} | ddd} || ||||d } tj | ddd|||d } | S) z Applies WPE-based dereverberation using nara_wpe's wpe_v6 function with PyTorch backend. The parameter defaults follow the ones in nara_wpe. .. caution:: The PyTorch backend is known to sometimes be less stable than the numpy backend. r4r5r)wpe_v6r7Tr8r;r<r=) r r>nara_wpe.torch_wperJr@rrBrCrErF) r3r rrrrrrJr:rGrHrIr"r"r#dereverb_wpe_torchWs4  rL)r r rrrr) dataclassesrrtypingrrrrr0rlhotse.augmentation.transformr lhotse.utilsrr r r1r-r/rr2rLr"r"r"r#sl  1