



"""simple docstring"""
import math

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


UpperCAmelCase						:		Optional[int]			= logging.get_logger(__name__)

UpperCAmelCase						:		Dict			= {
    "facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}


class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase   ):
    lowercase__      =   "data2vec-audio"

    def __init__(				self			:				Tuple ,  lowerCAmelCase_			:				List[Any]=3_2 ,  lowerCAmelCase_			:				List[Any]=7_6_8 ,  lowerCAmelCase_			:				str=1_2 ,  lowerCAmelCase_			:				Optional[Any]=1_2 ,  lowerCAmelCase_			:				List[Any]=3_0_7_2 ,  lowerCAmelCase_			:				Optional[int]="gelu" ,  lowerCAmelCase_			:				List[Any]=0.1 ,  lowerCAmelCase_			:				List[str]=0.1 ,  lowerCAmelCase_			:				List[str]=0.1 ,  lowerCAmelCase_			:				Optional[Any]=0.0 ,  lowerCAmelCase_			:				Tuple=0.1 ,  lowerCAmelCase_			:				str=0.1 ,  lowerCAmelCase_			:				Union[str, Any]=0.02 ,  lowerCAmelCase_			:				Dict=1E-5 ,  lowerCAmelCase_			:				List[str]="gelu" ,  lowerCAmelCase_			:				List[str]=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2) ,  lowerCAmelCase_			:				Dict=(5, 2, 2, 2, 2, 2, 2) ,  lowerCAmelCase_			:				List[Any]=(1_0, 3, 3, 3, 3, 2, 2) ,  lowerCAmelCase_			:				Tuple=False ,  lowerCAmelCase_			:				Optional[Any]=1_6 ,  lowerCAmelCase_			:				Optional[Any]=1_9 ,  lowerCAmelCase_			:				int=5 ,  lowerCAmelCase_			:				Any=0.05 ,  lowerCAmelCase_			:				List[str]=1_0 ,  lowerCAmelCase_			:				int=2 ,  lowerCAmelCase_			:				Union[str, Any]=0.0 ,  lowerCAmelCase_			:				Optional[Any]=1_0 ,  lowerCAmelCase_			:				Dict=0 ,  lowerCAmelCase_			:				int="sum" ,  lowerCAmelCase_			:				str=False ,  lowerCAmelCase_			:				List[Any]=False ,  lowerCAmelCase_			:				Union[str, Any]=2_5_6 ,  lowerCAmelCase_			:				List[Any]=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0) ,  lowerCAmelCase_			:				Optional[int]=(5, 3, 3, 1, 1) ,  lowerCAmelCase_			:				int=(1, 2, 3, 1, 1) ,  lowerCAmelCase_			:				str=5_1_2 ,  lowerCAmelCase_			:				List[Any]=0 ,  lowerCAmelCase_			:				List[str]=1 ,  lowerCAmelCase_			:				Union[str, Any]=2 ,  lowerCAmelCase_			:				Tuple=False ,  lowerCAmelCase_			:				Union[str, Any]=3 ,  lowerCAmelCase_			:				List[Any]=2 ,  lowerCAmelCase_			:				Any=3 ,  lowerCAmelCase_			:				Dict=None ,  **lowerCAmelCase_			:				Tuple ,  ):







      """simple docstring"""







      super().__init__(**lowerCAmelCase_ ,  pad_token_id=lowerCAmelCase_ ,  bos_token_id=lowerCAmelCase_ ,  eos_token_id=lowerCAmelCase_)
      lowercase_								= hidden_size
      lowercase_								= feat_extract_activation
      lowercase_								= list(lowerCAmelCase_)
      lowercase_								= list(lowerCAmelCase_)
      lowercase_								= list(lowerCAmelCase_)
      lowercase_								= conv_bias
      lowercase_								= num_conv_pos_embeddings
      lowercase_								= num_conv_pos_embedding_groups
      lowercase_								= conv_pos_kernel_size
      lowercase_								= len(self.conv_dim)
      lowercase_								= num_hidden_layers
      lowercase_								= intermediate_size
      lowercase_								= hidden_act
      lowercase_								= num_attention_heads
      lowercase_								= hidden_dropout
      lowercase_								= attention_dropout
      lowercase_								= activation_dropout
      lowercase_								= feat_proj_dropout
      lowercase_								= final_dropout
      lowercase_								= layerdrop
      lowercase_								= layer_norm_eps
      lowercase_								= initializer_range
      lowercase_								= vocab_size
      lowercase_								= use_weighted_layer_sum

      if (
          (len(self.conv_stride) != self.num_feat_extract_layers)
          or (len(self.conv_kernel) != self.num_feat_extract_layers)
          or (len(self.conv_dim) != self.num_feat_extract_layers)
      ):
        raise ValueError(
            """Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="""
            """ `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="""
            F''' {len(self.conv_dim)}`, `len(config.conv_stride) = {len(self.conv_stride)}`,'''
            F''' `len(config.conv_kernel) = {len(self.conv_kernel)}`.''')

      # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
      lowercase_								= mask_time_prob
      lowercase_								= mask_time_length
      lowercase_								= mask_time_min_masks
      lowercase_								= mask_feature_prob
      lowercase_								= mask_feature_length
      lowercase_								= mask_feature_min_masks

      # ctc loss
      lowercase_								= ctc_loss_reduction
      lowercase_								= ctc_zero_infinity

      # adapter
      lowercase_								= add_adapter
      lowercase_								= adapter_kernel_size
      lowercase_								= adapter_stride
      lowercase_								= num_adapter_layers
      lowercase_								= output_hidden_size or hidden_size

      # SequenceClassification-specific parameter. Feel free to ignore for other classes.
      lowercase_								= classifier_proj_size

      # XVector-specific parameters. Feel free to ignore for other classes.
      lowercase_								= list(lowerCAmelCase_)
      lowercase_								= list(lowerCAmelCase_)
      lowercase_								= list(lowerCAmelCase_)
      lowercase_								= xvector_output_dim




    @property
    def 					_UpperCAmelCase	(				self			:				Dict):







      """simple docstring"""







      return math.prod(self.conv_stride)





"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union

import flax
import jax.numpy as jnp
from jax import random

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin


@flax.struct.dataclass
class    SCREAMING_SNAKE_CASE__ :
    # setable values
    lowercase__      =   None
    lowercase__      =   None
    lowercase__      =   None  # sigma(t_i)

    @classmethod
    def 					_UpperCAmelCase	(				cls			:				Any):







      """simple docstring"""







      return cls()







@dataclass
class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase   ):
    lowercase__      =   42
    lowercase__      =   42
    lowercase__      =   42







class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase      ,  __UpperCAmelCase   ):

    @property
    def 					_UpperCAmelCase	(				self			:				int):







      """simple docstring"""







      return True

    @register_to_config
    def __init__(				self			:				Union[str, Any] ,  lowerCAmelCase_			:				float = 0.02 ,  lowerCAmelCase_			:				float = 1_0_0 ,  lowerCAmelCase_			:				float = 1.007 ,  lowerCAmelCase_			:				float = 8_0 ,  lowerCAmelCase_			:				float = 0.05 ,  lowerCAmelCase_			:				float = 5_0 ,  ):







      """simple docstring"""







      pass

    def 					_UpperCAmelCase	(				self			:				Optional[int]):







      """simple docstring"""







      return KarrasVeSchedulerState.create()

    def 					_UpperCAmelCase	(				self			:				Union[str, Any] ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				int ,  lowerCAmelCase_			:				Tuple = ()):







      """simple docstring"""







      lowercase_								= jnp.arange(0 ,  lowerCAmelCase_)[::-1].copy()
      lowercase_								= [
          (
              self.config.sigma_max**2
              * (self.config.sigma_min**2 / self.config.sigma_max**2) ** (i / (num_inference_steps - 1))
          )
          for i in timesteps
      ]

      return state.replace(
          num_inference_steps=lowerCAmelCase_ ,  schedule=jnp.array(lowerCAmelCase_ ,  dtype=jnp.floataa) ,  timesteps=lowerCAmelCase_ ,  )

    def 					_UpperCAmelCase	(				self			:				Optional[int] ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				random.KeyArray ,  ):







      """simple docstring"""







      if self.config.s_min <= sigma <= self.config.s_max:
        lowercase_								= min(self.config.s_churn / state.num_inference_steps ,  2**0.5 - 1)
      else:
        lowercase_								= 0

      # sample eps ~ N(0, S_noise^2 * I)
      lowercase_								= random.split(lowerCAmelCase_ ,  num=1)
      lowercase_								= self.config.s_noise * random.normal(key=lowerCAmelCase_ ,  shape=sample.shape)
      lowercase_								= sigma + gamma * sigma
      lowercase_								= sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps)

      return sample_hat, sigma_hat

    def 					_UpperCAmelCase	(				self			:				Tuple ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				bool = True ,  ):







      """simple docstring"""







      lowercase_								= sample_hat + sigma_hat * model_output
      lowercase_								= (sample_hat - pred_original_sample) / sigma_hat
      lowercase_								= sample_hat + (sigma_prev - sigma_hat) * derivative

      if not return_dict:
        return (sample_prev, derivative, state)

      return FlaxKarrasVeOutput(prev_sample=lowerCAmelCase_ ,  derivative=lowerCAmelCase_ ,  state=lowerCAmelCase_)

    def 					_UpperCAmelCase	(				self			:				Dict ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				bool = True ,  ):







      """simple docstring"""







      lowercase_								= sample_prev + sigma_prev * model_output
      lowercase_								= (sample_prev - pred_original_sample) / sigma_prev
      lowercase_								= sample_hat + (sigma_prev - sigma_hat) * (0.5 * derivative + 0.5 * derivative_corr)

      if not return_dict:
        return (sample_prev, derivative, state)

      return FlaxKarrasVeOutput(prev_sample=lowerCAmelCase_ ,  derivative=lowerCAmelCase_ ,  state=lowerCAmelCase_)




    def 					_UpperCAmelCase	(				self			:				List[Any] ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				int ,  lowerCAmelCase_			:				Optional[int] ,  lowerCAmelCase_			:				List[Any]):







      """simple docstring"""







      raise NotImplementedError()

