ZjtSrSSKrSSKrSSKJr SSKJr SSKJ r \ "SS9\"S S \555r S /r g) zEnCodec model configurationN)strict)PreTrainedConfig)auto_docstringzfacebook/encodec_24khz) checkpointcZ^\rSrSr%SrSrSr\\\ \S4-\ S'Sr \ \ S'S r \ \ S 'S r\\ S 'S r\ \-S -\ S'S r\S -\ S'Sr\ \ S'Sr\ \ S'S r\ \ S'Sr\\ \ \ S4-\ S'Sr\\ S'Sr\ \ S'Sr\ \ S'Sr\ \ S'Sr\ \ S'S r\\ S!'S"r\\ S#'Sr\ \ S$'Sr\ \ S%'S&r \\ S''S(r!\ \ S)'S r"\ S -\ S*'S r#\\ S+'U4S,jr$S-r%\&S.\ S -4S/j5r'\&S.\ S -4S0j5r(\&S.\ 4S1j5r)\&S.\ 4S2j5r*\&S.\ 4S3j5r+\&S.\ 4S4j5r,S5r-U=r.$)6 EncodecConfiga target_bandwidths (`list[float]`, *optional*, defaults to `[1.5, 3.0, 6.0, 12.0, 24.0]`): The range of different bandwidths the model can encode audio with. normalize (`bool`, *optional*, defaults to `False`): Whether the audio shall be normalized when passed. chunk_length_s (`float`, *optional*): If defined the audio is pre-processed into chunks of lengths `chunk_length_s` and then encoded. overlap (`float`, *optional*): Defines the overlap between each chunk. It is used to compute the `chunk_stride` using the following formulae : `int((1.0 - self.overlap) * self.chunk_length)`. num_filters (`int`, *optional*, defaults to 32): Number of convolution kernels of first `EncodecConv1d` down sampling layer. num_residual_layers (`int`, *optional*, defaults to 1): Number of residual layers. upsampling_ratios (`Sequence[int]` , *optional*, defaults to `[8, 5, 4, 2]`): Kernel size and stride ratios. The encoder uses downsampling ratios instead of upsampling ratios, hence it will use the ratios in the reverse order to the ones specified here that must match the decoder order. norm_type (`str`, *optional*, defaults to `"weight_norm"`): Normalization method. Should be in `["weight_norm", "time_group_norm"]` kernel_size (`int`, *optional*, defaults to 7): Kernel size for the initial convolution. last_kernel_size (`int`, *optional*, defaults to 7): Kernel size for the last convolution layer. residual_kernel_size (`int`, *optional*, defaults to 3): Kernel size for the residual layers. dilation_growth_rate (`int`, *optional*, defaults to 2): How much to increase the dilation with each layer. use_causal_conv (`bool`, *optional*, defaults to `True`): Whether to use fully causal convolution. pad_mode (`str`, *optional*, defaults to `"reflect"`): Padding mode for the convolutions. compress (`int`, *optional*, defaults to 2): Reduced dimensionality in residual branches (from Demucs v3). num_lstm_layers (`int`, *optional*, defaults to 2): Number of LSTM layers at the end of the encoder. trim_right_ratio (`float`, *optional*, defaults to 1.0): Ratio for trimming at the right of the transposed convolution under the `use_causal_conv = True` setup. If equal to 1.0, it means that all the trimming is done at the right. use_conv_shortcut (`bool`, *optional*, defaults to `True`): Whether to use a convolutional layer as the 'skip' connection in the `EncodecResnetBlock` block. If False, an identity function will be used, giving a generic residual connection. Example: ```python >>> from transformers import EncodecModel, EncodecConfig >>> # Initializing a "facebook/encodec_24khz" style configuration >>> configuration = EncodecConfig() >>> # Initializing a model (with random weights) from the "facebook/encodec_24khz" style configuration >>> model = EncodecModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```encodec)g?g@g@g(@g8@.target_bandwidthsi] sampling_rateaudio_channelsF normalizeNchunk_length_soverlap hidden_size num_filtersnum_residual_layers)upsampling_ratios weight_norm norm_type kernel_sizelast_kernel_sizerresidual_kernel_sizerdilation_growth_rateTuse_causal_convreflectpad_modecompressnum_lstm_layers?trim_right_ratioi codebook_size codebook_dimuse_conv_shortcutc z>URb URO URUl[TU] "S0UD6 g)N)r,rsuper __post_init__)selfkwargs __class__s ڂ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/encodec/configuration_encodec.pyr1EncodecConfig.__post_init__os5151B1B1ND--TXTdTd ''cTURS;a[SUR35eg)zOPart of `@strict`-powered validation. Validates the architecture of the config.)rtime_group_normzIself.norm_type must be one of `"weight_norm"`, `"time_group_norm"`), got N)r ValueErrorr2s r5validate_architecture#EncodecConfig.validate_architecturess4 >>!C C[\`\j\j[kl  Dr7returncbURcg[URUR-5$N)rintr r;s r5 chunk_lengthEncodecConfig.chunk_length{s-    &t**T-?-??@ @r7cURb URcg[S[SUR- UR-55$)Nrr))rrmaxrArBr;s r5 chunk_strideEncodecConfig.chunk_strides@    &$,,*>q#sT\\1T5F5FFGH Hr7cT[[R"UR55$r@)rAnpprodrr;s r5 hop_lengthEncodecConfig.hop_lengths277411233r7cj[R"[R"UR55$r@)mathceillog2r+r;s r5codebook_nbitsEncodecConfig.codebook_nbitss yy4#5#5677r7c\[R"URUR- 5$r@)rNrOr rKr;s r5 frame_rateEncodecConfig.frame_rates yy++doo=>>r7cl[SURS-URUR--5$)Ni)rAr rTrQr;s r5num_quantizersEncodecConfig.num_quantizerss14$00444K^K^9^_``r7)r,)/__name__ __module__ __qualname____firstlineno____doc__ model_typer listfloattuple__annotations__r rArrboolrrrrrrrstrr r!r"r#r$r&r'r(r*r+r,r-r1r<propertyrBrFrKrQrTrX__static_attributes__ __classcell__)r4s@r5r r s7 rJ9TtE{U5#:%66TM3NCIt)-NC%K$&- GUT\ KK  5AtCy5c?2A"Is"Kc !#! !#! 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