a  d8 @sddlmZddlmZmZddlmZmZddlZddlm Z ddl m Z ddl m Z ddlmZmZmZererdd lmZn dZd gZerdd lmZdd lmZmZnd \ZZZd gZeddeeeeje dddZeddeeeeje dddZeddeeeeeejee e e e fdddZd0e eee dddZ e e e dddZ!d1e ee d d!d"Z"e e e e d#d$d%Z#d2e eeeeeee$e$e d* d+d Z%d3eeeeeee$e$dd-d.d/Z&dS)4) lru_cache)ceilpi)OptionalTupleN)Tensor)pad)rank_zero_warn)_GAMMATONE_AVAILABEL_TORCHAUDIO_AVAILABEL_TORCHAUDIO_GREATER_EQUAL_0_10)lfilter,speech_reverberation_modulation_energy_ratio) fft_gtgram) centre_freqsmake_erb_filters)NNNd)maxsize)low_freqfs n_filtersdevicereturncCs>d}d}d}t|||||||d|}tj||dS)Ng<;k"@g333338@r)rtorchtensor)rrrrZear_qZmin_bwordererbsrk/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torchmetrics/functional/audio/srmr.py _calc_erbs/s $r!)r num_freqscutoffrrcCs$t|||}t||}tj||dS)Nr)rrrr)rr"r#rcfsfcoefsrrr _make_erb_filters8s  r&)min_cfmax_cfnrqrrc s||d|d}tj|tjd}||d<td|D]}||d|||<q6tttdddtjfdd d t||Ddd } tttt ttfd d d} |j |d}| j |d} | ||\} } || | | fS)N?rdtyper)w0r*rcSszt|d}||}tj|d| gtjd}tjd||dd|ddd||dgtjd}tj||gddS)Nrr,rdim)rtanrfloat64stack)r.r*b0barrr _make_modulation_filterJs :zK_compute_modulation_filterbank_and_cutoffs.._make_modulation_filtercsg|]}|qSrr).0r.r8r*rr Qz>_compute_modulation_filterbank_and_cutoffs..r/r0)r$rr*rcSsRdt||}t|d|}|||dt}|||dt}||fS)Nr/)rrr2)r$rr*r.r5llrrrrr _calc_cutoffsSs zA_compute_modulation_filterbank_and_cutoffs.._calc_cutoffsr) rzerosr3rangerintr4rfloatrto) r'r(r)rr*rZspacing_factorr$kZmfbr?r=r>rr:r *_compute_modulation_filterbank_and_cutoffs?s*  rF)xr)rcCs|rtd|dur:|jd}|dr:t|dd}|dkrJtdtjj||dd}tj||j|jdd}|d dkrd |d<||d <d |d |d <nd |d<d |d |d d <tjj ||dd }|d d|jdfS) Nzx must be real.rzN must be positive.)r)r1F)r-rZ requires_gradr/rr0.) Z is_complex ValueErrorshaperrZfftr@r-rZifft)rGr)Zx_ffthyrrr _hilbertas"  rN)wavecoefsrcCs|j\}}|j|jd|d|}|d|jdd}|dddf}|dddf}|dddf}|ddd f}|ddd f}|ddd df} t|| |d d } t| | |d d } t| | |d d } t| | |d d } | |dddS)zTranslated from gammatone package. Args: wave: shape [B, time] coefs: shape [N, 10] Returns: Tensor: shape [B, N, time] r,rrHrN )rr)rr/rR)rrR)rrRT)batching)rKrDr-reshapeexpandr )rOrPn_batchtimeZgainZas1Zas2Zas3Zas4bsy1y2Zy3Zy4rrr _erb_filterbankzs r^>@)energydrangercCsbtj|dddjdddj}|jdddj}|d| d}t||k||}t||k||S)zNormalize energy to a dynamic range of 30 dB. Args: energy: shape [B, N_filters, 8, n_frames] drange: dynamic range in dB rTr1Zkeepdimr/rSg$@)rmeanmaxvalueswhere)r`raZ peak_energyZ min_energyrrr _normalize_energys rg)bw avg_energycutoffsrcCs|d|kr|d|krd}nV|d|kr<|d|kr>> import torch >>> from torchmetrics.functional.audio import speech_reverberation_modulation_energy_ratio >>> g = torch.manual_seed(1) >>> preds = torch.randn(8000) >>> speech_reverberation_modulation_energy_ratio(preds, 8000) tensor([0.3354], dtype=torch.float64) aspeech_reverberation_modulation_energy_ratio requires you to have `gammatone` and `torchaudio>=0.10` installed. Either install as ``pip install torchmetrics[audio]`` or ``pip install torchaudio>=0.10`` and ``pip install git+https://github.com/detly/gammatone``rrrrr'r(rsrtrrHTrbr+)r-rgMb?gMb?z:`fast=True` may slow down the speed of SRMR metric on GPU.gy@g{Gz?g{Gzd?rr0rNrlr/)r)rr*rF)clamprVZconstant)rmodevalue.rZ)rj)1r r r ModuleNotFoundError_srmr_arg_validaterKlenrWrZis_floating_pointrDr3Zfinfor-rdabsrerfrrr detachcpunumpyrArappendr4r&rNr^rrFrBZhamming_windowr Z unsqueezerXrZunfoldrmrgZflipudr!rcZflipZcumsumZnonzerorn)+rqrrrrr'r(rsrtrKrYrZZmax_valsZval_normZ w_length_sZw_inc_sZmfstempZpreds_npr6Zgt_env_bZgt_envr%Zw_lengthZw_inc_ZmfrjZn_frameswZmod_outpaddingZ mod_out_padZ mod_out_framer`rriZ total_energyZ ac_energyZac_percZac_perc_cumsumZ k90perc_idxrhZscorerrr rs7  (       F"&$  rw)rrrrr'r(rsrtrcCst|tr|dks td|t|tr2|dks@td|t|ttfrV|dksdtd|t|ttfrz|dkstd||durt|ttfr|dkstd|t|tstdt|tstd dS) a9Validate the arguments for speech_reverberation_modulation_energy_ratio. Args: fs: the sampling rate n_cochlear_filters: Number of filters in the acoustic filterbank low_freq: determines the frequency cutoff for the corresponding gammatone filterbank. min_cf: Center frequency in Hz of the first modulation filter. max_cf: Center frequency in Hz of the last modulation filter. If None is given, norm: Use modulation spectrum energy normalization fast: Use the faster version based on the gammatonegram. rz;Expected argument `fs` to be an int larger than 0, but got zKExpected argument `n_cochlear_filters` to be an int larger than 0, but got zBExpected argument `low_freq` to be a float larger than 0, but got z@Expected argument `min_cf` to be a float larger than 0, but got Nz@Expected argument `max_cf` to be a float larger than 0, but got z+Expected argument `norm` to be a bool valuez+Expected argument `fast` to be a bool value) isinstancerBrJrCboolrurrr r~Gs   r~)N)r_)rorprTNFF)rorprTrwFF)' functoolsrmathrrtypingrrrrZtorch.nn.functionalrZtorchmetrics.utilitiesr Ztorchmetrics.utilities.importsr r r Ztorchaudio.functional.filteringr Z__doctest_skip__Zgammatone.fftweightrZgammatone.filtersrrrCrBrr!r&rFrNr^rgrnrrr~rrrr s|      !