





from dataclasses import dataclass
from typing import Optional, Tuple, Union

import numpy as np
import torch

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		torch.FloatTensor
   _UpperCamelCase   :		torch.FloatTensor
   _UpperCamelCase   :		Optional[torch.FloatTensor]			 =	None






class     SCREAMING_SNAKE_CASE       (UpperCAmelCase      ,     UpperCAmelCase				):
   _UpperCamelCase   :		Tuple			 =	2


   @register_to_config
   def __init__(   self      :    List[str]      ,					a      :    float = 0.02      ,					a      :    float = 100      ,					a      :    float = 1.007      ,					a      :    float = 80      ,					a      :    float = 0.05      ,					a      :    float = 50      ,					)->       Optional[int]:





     """simple docstring"""







     lowercase__           =  sigma_max

     # setable values
     lowercase__           =  None
     lowercase__           =  None
     lowercase__           =  None  # sigma(t_i)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    str      ,					a      :    torch.FloatTensor      ,					a      :    Optional[int] = None	)->       torch.FloatTensor:





     """simple docstring"""







     return sample


   def 	SCREAMING_SNAKE_CASE_							(   self      :    int      ,					a      :    int      ,					a      :    Union[str, torch.device] = None	)->       Optional[Any]:





     """simple docstring"""







     lowercase__           =  num_inference_steps
     lowercase__           =  np.arange(0      ,					self.num_inference_steps	)[::-1].copy()
     lowercase__           =  torch.from_numpy(a	).to(a	)
     lowercase__           =  [
         (
             self.config.sigma_max**2
             * (self.config.sigma_min**2 / self.config.sigma_max**2) ** (i / (num_inference_steps - 1))
         )
         for i in self.timesteps
     ]
     lowercase__           =  torch.tensor(a      ,					dtype=torch.floataa      ,					device=a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    str      ,					a      :    torch.FloatTensor      ,					a      :    float      ,					a      :    Optional[torch.Generator] = None	)->       Tuple[torch.FloatTensor, float]:





     """simple docstring"""







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

     # sample eps ~ N(0, S_noise^2 * I)
     lowercase__           =  self.config.s_noise * randn_tensor(sample.shape      ,					generator=a	).to(sample.device	)
     lowercase__           =  sigma + gamma * sigma
     lowercase__           =  sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps)

     return sample_hat, sigma_hat


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[Any]      ,					a      :    torch.FloatTensor      ,					a      :    float      ,					a      :    float      ,					a      :    torch.FloatTensor      ,					a      :    bool = True      ,					)->       Union[KarrasVeOutput, Tuple]:





     """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)

     return KarrasVeOutput(
         prev_sample=a      ,					derivative=a      ,					pred_original_sample=a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]      ,					a      :    torch.FloatTensor      ,					a      :    float      ,					a      :    float      ,					a      :    torch.FloatTensor      ,					a      :    torch.FloatTensor      ,					a      :    torch.FloatTensor      ,					a      :    bool = True      ,					)->       Union[KarrasVeOutput, Tuple]:





     """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)

     return KarrasVeOutput(
         prev_sample=a      ,					derivative=a      ,					pred_original_sample=a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]      ,					a      :    Union[str, Any]      ,					a      :    Optional[Any]      ,					a      :    Union[str, Any]	)->       Union[str, Any]:





     """simple docstring"""







     raise NotImplementedError()







from datasets.utils.patching import _PatchedModuleObj, patch_submodule

from . import _test_patching




def       __UpperCamelCase  ()    ->       str:
  import os as original_os
  from os import path as original_path
  from os import rename as original_rename
  from os.path import dirname as original_dirname
  from os.path import join as original_join

  assert _test_patching.os is original_os
  assert _test_patching.path is original_path
  assert _test_patching.join is original_join

  assert _test_patching.renamed_os is original_os
  assert _test_patching.renamed_path is original_path
  assert _test_patching.renamed_join is original_join

  lowercase__           =  '__test_patch_submodule_mock__'
  with patch_submodule(_test_patching		,						'os.path.join'		,						_SCREAMING_SNAKE_CASE		):
    # Every way to access os.path.join must be patched, and the rest must stay untouched

    # check os.path.join
    assert isinstance(_test_patching.os		,						_PatchedModuleObj		)
    assert isinstance(_test_patching.os.path		,						_PatchedModuleObj		)
    assert _test_patching.os.path.join is mock

    # check path.join
    assert isinstance(_test_patching.path		,						_PatchedModuleObj		)
    assert _test_patching.path.join is mock

    # check join
    assert _test_patching.join is mock

    # check that the other attributes are untouched
    assert _test_patching.os.rename is original_rename
    assert _test_patching.path.dirname is original_dirname
    assert _test_patching.os.path.dirname is original_dirname

    # Even renamed modules or objects must be patched

    # check renamed_os.path.join
    assert isinstance(_test_patching.renamed_os		,						_PatchedModuleObj		)
    assert isinstance(_test_patching.renamed_os.path		,						_PatchedModuleObj		)
    assert _test_patching.renamed_os.path.join is mock

    # check renamed_path.join
    assert isinstance(_test_patching.renamed_path		,						_PatchedModuleObj		)
    assert _test_patching.renamed_path.join is mock

    # check renamed_join
    assert _test_patching.renamed_join is mock

    # check that the other attributes are untouched
    assert _test_patching.renamed_os.rename is original_rename
    assert _test_patching.renamed_path.dirname is original_dirname
    assert _test_patching.renamed_os.path.dirname is original_dirname

  # check that everthing is back to normal when the patch is over

  assert _test_patching.os is original_os
  assert _test_patching.path is original_path
  assert _test_patching.join is original_join

  assert _test_patching.renamed_os is original_os
  assert _test_patching.renamed_path is original_path
  assert _test_patching.renamed_join is original_join




def       __UpperCamelCase  ()    ->       Any:
  assert _test_patching.open is open

  lowercase__           =  '__test_patch_submodule_builtin_mock__'
  # _test_patching has "open" in its globals
  assert _test_patching.open is open
  with patch_submodule(_test_patching		,						'open'		,						_SCREAMING_SNAKE_CASE		):
    assert _test_patching.open is mock

  # check that everthing is back to normal when the patch is over

  assert _test_patching.open is open




def       __UpperCamelCase  ()    ->       List[str]:
  # pandas.read_csv is not present in _test_patching
  lowercase__           =  '__test_patch_submodule_missing_mock__'
  with patch_submodule(_test_patching		,						'pandas.read_csv'		,						_SCREAMING_SNAKE_CASE		):
    pass




def       __UpperCamelCase  ()    ->       List[str]:
  # builtin should always be mocked even if they're not in the globals
  # in case they're loaded at one point
  lowercase__           =  '__test_patch_submodule_missing_builtin_mock__'
  # _test_patching doesn't have "len" in its globals
  assert getattr(_test_patching		,						'len'		,						_SCREAMING_SNAKE_CASE		) is None
  with patch_submodule(_test_patching		,						'len'		,						_SCREAMING_SNAKE_CASE		):
    assert _test_patching.len is mock
  assert _test_patching.len is len




def       __UpperCamelCase  ()    ->       List[str]:
  lowercase__           =  '__test_patch_submodule_start_and_stop_mock__'
  lowercase__           =  patch_submodule(_test_patching		,						'open'		,						_SCREAMING_SNAKE_CASE		)
  assert _test_patching.open is open
  patch.start()
  assert _test_patching.open is mock
  patch.stop()
  assert _test_patching.open is open




def       __UpperCamelCase  ()    ->       Optional[int]:
  from os import rename as original_rename
  from os.path import dirname as original_dirname
  from os.path import join as original_join

  lowercase__           =  '__test_patch_submodule_successive_join__'
  lowercase__           =  '__test_patch_submodule_successive_dirname__'
  lowercase__           =  '__test_patch_submodule_successive_rename__'
  assert _test_patching.os.path.join is original_join
  assert _test_patching.os.path.dirname is original_dirname
  assert _test_patching.os.rename is original_rename

  with patch_submodule(_test_patching		,						'os.path.join'		,						_SCREAMING_SNAKE_CASE		):
    with patch_submodule(_test_patching		,						'os.rename'		,						_SCREAMING_SNAKE_CASE		):
      with patch_submodule(_test_patching		,						'os.path.dirname'		,						_SCREAMING_SNAKE_CASE		):
        assert _test_patching.os.path.join is mock_join
        assert _test_patching.os.path.dirname is mock_dirname
        assert _test_patching.os.rename is mock_rename

    # try another order
  with patch_submodule(_test_patching		,						'os.rename'		,						_SCREAMING_SNAKE_CASE		):
    with patch_submodule(_test_patching		,						'os.path.join'		,						_SCREAMING_SNAKE_CASE		):
      with patch_submodule(_test_patching		,						'os.path.dirname'		,						_SCREAMING_SNAKE_CASE		):
        assert _test_patching.os.path.join is mock_join
        assert _test_patching.os.path.dirname is mock_dirname
        assert _test_patching.os.rename is mock_rename

  assert _test_patching.os.path.join is original_join
  assert _test_patching.os.path.dirname is original_dirname
  assert _test_patching.os.rename is original_rename




def       __UpperCamelCase  ()    ->       Optional[Any]:
  lowercase__           =  '__test_patch_submodule_doesnt_exist_mock__'
  with patch_submodule(_test_patching		,						'__module_that_doesn_exist__.__attribute_that_doesn_exist__'		,						_SCREAMING_SNAKE_CASE		):
    pass
  with patch_submodule(_test_patching		,						'os.__attribute_that_doesn_exist__'		,						_SCREAMING_SNAKE_CASE		):
    pass


