



"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List

from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql  # noqa F401
from .text import text


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						str:







  '''simple docstring'''


  lowercase_								= []
  for line in lines:
    lowercase_								= re.sub(R"""#.*""" ,  """""" ,  __lowerCAmelCase							)  # remove comments
    if line:
      filtered_lines.append(__lowerCAmelCase							)
  lowercase_								= """\n""".join(__lowerCAmelCase							)

  # Make a hash from all this code
  lowercase_								= full_str.encode("""utf-8"""							)
  return shaaaa(__lowerCAmelCase							).hexdigest()


# get importable module names and hash for caching
UpperCAmelCase						:		Tuple			= {
    "csv": (csv.__name__, _hash_python_lines(inspect.getsource(csv).splitlines())),
    "json": (json.__name__, _hash_python_lines(inspect.getsource(json).splitlines())),
    "pandas": (pandas.__name__, _hash_python_lines(inspect.getsource(pandas).splitlines())),
    "parquet": (parquet.__name__, _hash_python_lines(inspect.getsource(parquet).splitlines())),
    "arrow": (arrow.__name__, _hash_python_lines(inspect.getsource(arrow).splitlines())),
    "text": (text.__name__, _hash_python_lines(inspect.getsource(text).splitlines())),
    "imagefolder": (imagefolder.__name__, _hash_python_lines(inspect.getsource(imagefolder).splitlines())),
    "audiofolder": (audiofolder.__name__, _hash_python_lines(inspect.getsource(audiofolder).splitlines())),
}

# Used to infer the module to use based on the data files extensions
UpperCAmelCase						:		str			= {
    ".csv": ("csv", {}),
    ".tsv": ("csv", {"sep": "\t"}),
    ".json": ("json", {}),
    ".jsonl": ("json", {}),
    ".parquet": ("parquet", {}),
    ".arrow": ("arrow", {}),
    ".txt": ("text", {}),
}
_EXTENSION_TO_MODULE.update({ext: ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext: ("audiofolder", {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ("audiofolder", {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
UpperCAmelCase						:		Dict			= {"imagefolder", "audiofolder"}

# Used to filter data files based on extensions given a module name
UpperCAmelCase						:		Dict[str, List[str]]			= {}
for _ext, (_module, _) in _EXTENSION_TO_MODULE.items():
       _MODULE_TO_EXTENSIONS.setdefault(_module, []).append(_ext)

_MODULE_TO_EXTENSIONS["imagefolder"].append(".zip")


_MODULE_TO_EXTENSIONS["audiofolder"].append(".zip")






"""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()

