



'''simple docstring'''





import math
from typing import Optional

import numpy as np

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__          =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__          =  {
    "facebook/encodec_24khz": "https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json",
    "facebook/encodec_48khz": "https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json",
}


class 					snake_case			(UpperCAmelCase_ ):
       lowerCAmelCase__	:Union[str, Any]     =       '''encodec'''



       def __init__(					self  ,UpperCAmelCase_=[1.5, 3.0, 6.0, 12.0, 24.0]  ,UpperCAmelCase_=24_000  ,UpperCAmelCase_=1  ,UpperCAmelCase_=False  ,UpperCAmelCase_=None  ,UpperCAmelCase_=None  ,UpperCAmelCase_=128  ,UpperCAmelCase_=32  ,UpperCAmelCase_=1  ,UpperCAmelCase_=[8, 5, 4, 2]  ,UpperCAmelCase_="weight_norm"  ,UpperCAmelCase_=7  ,UpperCAmelCase_=7  ,UpperCAmelCase_=3  ,UpperCAmelCase_=2  ,UpperCAmelCase_=True  ,UpperCAmelCase_="reflect"  ,UpperCAmelCase_=2  ,UpperCAmelCase_=2  ,UpperCAmelCase_=1.0  ,UpperCAmelCase_=1_024  ,UpperCAmelCase_=None  ,UpperCAmelCase_=True  ,**UpperCAmelCase_  ,)	->				List[str]:
           lowercase__									=    target_bandwidths
           lowercase__									=    sampling_rate
           lowercase__									=    audio_channels
           lowercase__									=    normalize
           lowercase__									=    chunk_length_s
           lowercase__									=    overlap
           lowercase__									=    hidden_size
           lowercase__									=    num_filters
           lowercase__									=    num_residual_layers
           lowercase__									=    upsampling_ratios
           lowercase__									=    norm_type
           lowercase__									=    kernel_size
           lowercase__									=    last_kernel_size
           lowercase__									=    residual_kernel_size
           lowercase__									=    dilation_growth_rate
           lowercase__									=    use_causal_conv
           lowercase__									=    pad_mode
           lowercase__									=    compress
           lowercase__									=    num_lstm_layers
           lowercase__									=    trim_right_ratio
           lowercase__									=    codebook_size
           lowercase__									=    codebook_dim if codebook_dim is not None else hidden_size
           lowercase__									=    use_conv_shortcut

           if self.norm_type not in ["weight_norm", "time_group_norm"]:
               raise ValueError(
                   F'''self.norm_type must be one of `"weight_norm"`, `"time_group_norm"`), got {self.norm_type}'''   )

           super().__init__(**lowerCamelCase__   )



       @property
       def 				_a   (					self   )	->				int:

           if self.chunk_length_s is None:
               return None
           else:
               return int(self.chunk_length_s * self.sampling_rate   )



       @property
       def 				_a   (					self   )	->				List[str]:

           if self.chunk_length_s is None or self.overlap is None:
               return None
           else:
               return max(1  ,int((1.0 - self.overlap) * self.chunk_length   )   )



       @property
       def 				_a   (					self   )	->				int:
           lowercase__									=    np.prod(self.upsampling_ratios   )
           return math.ceil(self.sampling_rate / hop_length   )







       @property
       def 				_a   (					self   )	->				Optional[int]:
           return int(1_000 * self.target_bandwidths[-1] // (self.frame_rate * 10)   )












from . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
    bert,
    bert_generation,
    bert_japanese,
    bertweet,
    big_bird,
    bigbird_pegasus,
    biogpt,
    bit,
    blenderbot,
    blenderbot_small,
    blip,
    blip_a,
    bloom,
    bridgetower,
    byta,
    camembert,
    canine,
    chinese_clip,
    clap,
    clip,
    clipseg,
    codegen,
    conditional_detr,
    convbert,
    convnext,
    convnextva,
    cpm,
    cpmant,
    ctrl,
    cvt,
    dataavec,
    deberta,
    deberta_va,
    decision_transformer,
    deformable_detr,
    deit,
    deprecated,
    deta,
    detr,
    dialogpt,
    dinat,
    distilbert,
    dit,
    donut,
    dpr,
    dpt,
    efficientformer,
    efficientnet,
    electra,
    encodec,
    encoder_decoder,
    ernie,
    ernie_m,
    esm,
    falcon,
    flaubert,
    flava,
    fnet,
    focalnet,
    fsmt,
    funnel,
    git,
    glpn,
    gpta,
    gpt_bigcode,
    gpt_neo,
    gpt_neox,
    gpt_neox_japanese,
    gpt_swa,
    gptj,
    gptsan_japanese,
    graphormer,
    groupvit,
    herbert,
    hubert,
    ibert,
    imagegpt,
    informer,
    instructblip,
    jukebox,
    layoutlm,
    layoutlmva,
    layoutlmva,
    layoutxlm,
    led,
    levit,
    lilt,
    llama,
    longformer,
    longta,
    luke,
    lxmert,
    mam_aaa,
    marian,
    markuplm,
    maskaformer,
    maskformer,
    mbart,
    mbartaa,
    mega,
    megatron_bert,
    megatron_gpta,
    mgp_str,
    mluke,
    mobilebert,
    mobilenet_va,
    mobilenet_va,
    mobilevit,
    mobilevitva,
    mpnet,
    mra,
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    musicgen,
    mvp,
    nat,
    nezha,
    nllb,
    nllb_moe,
    nystromformer,
    oneformer,
    open_llama,
    openai,
    opt,
    owlvit,
    pegasus,
    pegasus_x,
    perceiver,
    phobert,
    pixastruct,
    plbart,
    poolformer,
    prophetnet,
    qdqbert,
    rag,
    realm,
    reformer,
    regnet,
    rembert,
    resnet,
    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
    sew_d,
    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
    swinasr,
    swinva,
    switch_transformers,
    ta,
    table_transformer,
    tapas,
    time_series_transformer,
    timesformer,
    timm_backbone,
    transfo_xl,
    trocr,
    tvlt,
    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
    vilt,
    vision_encoder_decoder,
    vision_text_dual_encoder,
    visual_bert,
    vit,
    vit_hybrid,
    vit_mae,
    vit_msn,
    vivit,
    wavaveca,
    wavaveca_conformer,
    wavaveca_phoneme,
    wavaveca_with_lm,
    wavlm,
    whisper,
    x_clip,
    xglm,
    xlm,
    xlm_prophetnet,
    xlm_roberta,
    xlm_roberta_xl,
    xlnet,
    xmod,
    yolos,
    yoso,
)



