
'''simple docstring'''


from ...utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_torch_available,
    is_transformers_available,
)


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
   from .multicontrolnet import MultiControlNetModel
   from .pipeline_controlnet import StableDiffusionControlNetPipeline
   from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
   from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
   from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline







'''simple docstring'''


import math
from typing import Optional

import numpy as np

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


snake_case_ :  Dict     =					logging.get_logger(__name__)

snake_case_ :  Union[str, Any]     =					{
    '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 						lowercase__	(  snake_case_   ):






   '''simple docstring'''







   _snake_case		   =							'''encodec'''







   def __init__(			self ,   lowerCamelCase__=[1.5, 3.0, 6.0, 12.0, 24.0] ,   lowerCamelCase__=2_4_0_0_0 ,   lowerCamelCase__=1 ,   lowerCamelCase__=False ,   lowerCamelCase__=None ,   lowerCamelCase__=None ,   lowerCamelCase__=1_2_8 ,   lowerCamelCase__=3_2 ,   lowerCamelCase__=1 ,   lowerCamelCase__=[8, 5, 4, 2] ,   lowerCamelCase__="weight_norm" ,   lowerCamelCase__=7 ,   lowerCamelCase__=7 ,   lowerCamelCase__=3 ,   lowerCamelCase__=2 ,   lowerCamelCase__=True ,   lowerCamelCase__="reflect" ,   lowerCamelCase__=2 ,   lowerCamelCase__=2 ,   lowerCamelCase__=1.0 ,   lowerCamelCase__=1_0_2_4 ,   lowerCamelCase__=None ,   lowerCamelCase__=True ,   **lowerCamelCase__ ,   ):

      '''simple docstring'''







      UpperCamelCase       =  target_bandwidths
      UpperCamelCase       =  sampling_rate
      UpperCamelCase       =  audio_channels
      UpperCamelCase       =  normalize
      UpperCamelCase       =  chunk_length_s
      UpperCamelCase       =  overlap
      UpperCamelCase       =  hidden_size
      UpperCamelCase       =  num_filters
      UpperCamelCase       =  num_residual_layers
      UpperCamelCase       =  upsampling_ratios
      UpperCamelCase       =  norm_type
      UpperCamelCase       =  kernel_size
      UpperCamelCase       =  last_kernel_size
      UpperCamelCase       =  residual_kernel_size
      UpperCamelCase       =  dilation_growth_rate
      UpperCamelCase       =  use_causal_conv
      UpperCamelCase       =  pad_mode
      UpperCamelCase       =  compress
      UpperCamelCase       =  num_lstm_layers
      UpperCamelCase       =  trim_right_ratio
      UpperCamelCase       =  codebook_size
      UpperCamelCase       =  codebook_dim if codebook_dim is not None else hidden_size
      UpperCamelCase       =  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       UpperCAmelCase				(			self   ):

      '''simple docstring'''







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







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      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       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  np.prod(self.upsampling_ratios   )
      return math.ceil(self.sampling_rate / hop_length   )







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      return int(1_0_0_0 * self.target_bandwidths[-1] // (self.frame_rate * 1_0)   )





