o 㥵i8+ @sddlZddlmZddlmZddlZddlZddlmZddl m Z ddlm Z ddl m Z dd lmZdd lmZdd lmZdd lmZd dZGddde jZGddde jZGddde jZGddde jZGddde jZGddde e ZedkrFddlZddlmZedZ e !D]"\Z"Z#e#$Z%e&dde#'DZ(d d!Z)e*e#d"ee)e%e(d#qe+e e+d$e&d%de 'Dd&Z,e-dde,e j.Z/e/0d'e/1e e/d(Z2e+d)e/j3e+d*e2j3e4e2Z5de5dddde5j3d+d,f<e26e5e/j57dZ8e8dk&dZ8e8dk&Z9e+d-e9:ee-ddd.d/Z/e j;e jeZdZdgddfdededeffdd Zdd ZZS) Encoder@rrHd_modelstridesd_latentc sttd|dddg|_|D]}|d9}|jt||dg7_q|jt|t||dddg7_tj|j|_||_dS)Nrr r:r!r"r)r8) r#r$r r&r7r rr%enc_dim)r'rIrJrKr8r)rrr$As  zEncoder.__init__cCr?r@rArBrrrr/ZrCzEncoder.forward)r2r3r4r5listr$r/r6rrr)rrD@srDcs4eZdZd dededeffdd Zd d ZZS) DecoderBlockrrHr input_dim output_dimr8c sZttt|t||d||t|ddt|ddt|ddt|dd|_ dS)Nrr<rr9r:r;) r#r$rr%r r r=r>rr&)r'rPrQr8r)rrr$_s      zDecoderBlock.__init__cCr?r@rArBrrrr/orCzDecoderBlock.forward)rrHrr1rrr)rrO^srOcs.eZdZ ddeffdd ZddZZS)Decoderrd_outc stt||dddg}t|D]\}}|d|}|d|d} |t|| |g7}q|t| t| |dddtg7}tj||_ dS)Nr r:rLrr) r#r$r enumeraterOr rTanhr%model) r' input_channelchannelsratesrSlayersir8rPrQr)rrr$ts  zDecoder.__init__cCr?r@)rVrBrrrr/rCzDecoder.forward)rr1rrr)rrRss rRcseZdZdgdddgddddd d f d ed eed ededeedededeeefdedeffdd ZddZ d"de j defddZ de j fddZ  d#de j dedefd d!ZZS)$DACrErFNi)rHrHrGrr;irHFD encoder_dim encoder_rates latent_dim decoder_dim decoder_rates n_codebooks codebook_size codebook_dimquantizer_dropout sample_ratec st||_||_||_||_| |_|dur |dt|}||_t ||_ t ||||_ ||_||_||_t||||| d|_t||||_| |_|t||_dS)Nr)rPrcrdrerf)r#r$r^r_rarbrglenr`npprod hop_lengthrDencoderrcrdrer quantizerrRdecoderapplyr get_delaydelay) r'r^r_r`rarbrcrdrerfrgr)rrr$s:   z DAC.__init__cCsV|dur|j}||jksJ|jd}t||j|j|}tj|d|f}|S)Nr+r)rgr,r=r>rkr functionalr()r' audio_datarglength right_padrrr preprocesss zDAC.preprocessrs n_quantizerscCs.||}|||\}}}}}|||||fS)aeEncode given audio data and return quantized latent codes Parameters ---------- audio_data : Tensor[B x 1 x T] Audio data to encode n_quantizers : int, optional Number of quantizers to use, by default None If None, all quantizers are used. Returns ------- dict A dictionary with the following keys: "z" : Tensor[B x D x T] Quantized continuous representation of input "codes" : Tensor[B x N x T] Codebook indices for each codebook (quantized discrete representation of input) "latents" : Tensor[B x N*D x T] Projected latents (continuous representation of input before quantization) "vq/commitment_loss" : Tensor[1] Commitment loss to train encoder to predict vectors closer to codebook entries "vq/codebook_loss" : Tensor[1] Codebook loss to update the codebook "length" : int Number of samples in input audio )rlrm)r'rsrwzcodeslatentscommitment_loss codebook_lossrrrencodes "z DAC.encoderxcCr?)aDecode given latent codes and return audio data Parameters ---------- z : Tensor[B x D x T] Quantized continuous representation of input length : int, optional Number of samples in output audio, by default None Returns ------- dict A dictionary with the following keys: "audio" : Tensor[B x 1 x length] Decoded audio data. )rn)r'rxrrrdecodes z DAC.decodec CsT|jd}|||}|||\}}}}} ||} | dd|f||||| dS)a%Model forward pass Parameters ---------- audio_data : Tensor[B x 1 x T] Audio data to encode sample_rate : int, optional Sample rate of audio data in Hz, by default None If None, defaults to `self.sample_rate` n_quantizers : int, optional Number of quantizers to use, by default None. If None, all quantizers are used. Returns ------- dict A dictionary with the following keys: "z" : Tensor[B x D x T] Quantized continuous representation of input "codes" : Tensor[B x N x T] Codebook indices for each codebook (quantized discrete representation of input) "latents" : Tensor[B x N*D x T] Projected latents (continuous representation of input before quantization) "vq/commitment_loss" : Tensor[1] Commitment loss to train encoder to predict vectors closer to codebook entries "vq/codebook_loss" : Tensor[1] Codebook loss to update the codebook "length" : int Number of samples in input audio "audio" : Tensor[B x 1 x length] Decoded audio data. r+.N)audiorxryrzzvq/commitment_losszvq/codebook_loss)r,rvr}r~) r'rsrgrwrtrxryrzr{r|r-rrrr/ s (  z DAC.forwardr@)NN)r2r3r4r5rrrNboolr$rvtorchTensorr}r~r/r6rrr)rr\sb   2 (r\__main__)partialcpucCg|] }t|qSrrirjsize.0prrr MrcCs|d|dddS)N g.Az<.3fz M params.rorrrrNsr extra_reprrzTotal # of params: cCrrrrrrrrQriTrz Input shape:z Output shape:r+rzReceptive field: i_(r])verbose)=r=typingrrnumpyrir audiotoolsr audiotools.mlrrbaser dac.nn.layersr r r dac.nn.quantizer rModulerr7rDrOrRr\r2 functoolsrtorV named_modulesnrrrsum parametersrfnsetattrprintrtrandndevicer-requires_grad_ retain_gradoutr, zeros_likegradbackwardsqueezegradmaprfitem decompresscompressrrrrsb            3