gndZddlZddlZddlmZddlmZeje Z GddeZ dS)zDac model configurationN)PretrainedConfig)loggingc \eZdZdZdZdgdddddd d d d f fd ZedefdZxZ S) DacConfigaW This is the configuration class to store the configuration of an [`DacModel`]. It is used to instantiate a Dac model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the [descript/dac_16khz](https://huggingface.co/descript/dac_16khz) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: encoder_hidden_size (`int`, *optional*, defaults to 64): Intermediate representation dimension for the encoder. downsampling_ratios (`List[int]`, *optional*, defaults to `[2, 4, 8, 8]`): Ratios for downsampling in the encoder. These are used in reverse order for upsampling in the decoder. decoder_hidden_size (`int`, *optional*, defaults to 1536): Intermediate representation dimension for the decoder. n_codebooks (`int`, *optional*, defaults to 9): Number of codebooks in the VQVAE. codebook_size (`int`, *optional*, defaults to 1024): Number of discrete codes in each codebook. codebook_dim (`int`, *optional*, defaults to 8): Dimension of the codebook vectors. If not defined, uses `encoder_hidden_size`. quantizer_dropout (`bool`, *optional*, defaults to 0): Whether to apply dropout to the quantizer. commitment_loss_weight (float, *optional*, defaults to 0.25): Weight of the commitment loss term in the VQVAE loss function. codebook_loss_weight (float, *optional*, defaults to 1.0): Weight of the codebook loss term in the VQVAE loss function. sampling_rate (`int`, *optional*, defaults to 16000): The sampling rate at which the audio waveform should be digitalized expressed in hertz (Hz). Example: ```python >>> from transformers import DacModel, DacConfig >>> # Initializing a "descript/dac_16khz" style configuration >>> configuration = DacConfig() >>> # Initializing a model (with random weights) from the "descript/dac_16khz" style configuration >>> model = DacModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```dac@)r i ir rg?g?i>c  f||_||_||_|ddd|_||_||_||_||_| |_|dt|zz|_ ttj ||_||_| |_t#jdi| dS)Nr )encoder_hidden_sizedownsampling_ratiosdecoder_hidden_sizeupsampling_ratios n_codebooks codebook_size codebook_dimquantizer_dropout sampling_ratelen hidden_sizeintnpprod hop_lengthcommitment_loss_weightcodebook_loss_weightsuper__init__) selfrrrrrrrr r!rkwargs __class__s e/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/models/dac/configuration_dac.pyr#zDacConfig.__init__Ls$7 #6 #6 !4TTrT!:&*(!2*.!s;N7O7O2OPbg&9::;;&<#$8!""6"""""returncltj|j}tj|j|z S)N)rrrmathceilr)r$rs r' frame_ratezDacConfig.frame_ratels,WT344 y+j8999r() __name__ __module__ __qualname____doc__ model_typer#propertyrr- __classcell__)r&s@r'rrs+ + ZJ(LL # ######@:C:::X:::::r(r) r1r+numpyrconfiguration_utilsrutilsr get_loggerr.loggerrrr(r'r:s 333333  H % %S:S:S:S:S: S:S:S:S:S:r(