






"""simple docstring"""



import random
import unittest

import torch

from diffusers import IFSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin

@skip_mps
class 			a	(  a_,							a_,							unittest.TestCase      ):
    UpperCAmelCase_					:	Optional[int]      	=IFSuperResolutionPipeline
    UpperCAmelCase_					:	Optional[int]      	=TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {"width", "height"}
    UpperCAmelCase_					:	str      	=TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
    UpperCAmelCase_					:	List[str]      	=PipelineTesterMixin.required_optional_params - {"latents"}







    def      UpperCamelCase_ (     self			):
      return self._get_superresolution_dummy_components()







    def      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase=0			):
      if str(_lowerCamelCase			).startswith('mps'			):
        lowercase				       =			torch.manual_seed(_lowerCamelCase			)
      else:
        lowercase				       =			torch.Generator(device=_lowerCamelCase			).manual_seed(_lowerCamelCase			)

      lowercase				       =			floats_tensor((1, 3, 3_2, 3_2)				,						rng=random.Random(_lowerCamelCase			)			).to(_lowerCamelCase			)

      lowercase				       =			{
          'prompt': 'A painting of a squirrel eating a burger',
          'image': image,
          'generator': generator,
          'num_inference_steps': 2,
          'output_type': 'numpy',
      }

      return inputs







    @unittest.skipIf(
        torch_device != 'cuda' or not is_xformers_available()				,						reason='XFormers attention is only available with CUDA and `xformers` installed'				,						)
    def      UpperCamelCase_ (     self			):
      self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3			)







    def      UpperCamelCase_ (     self			):
      self._test_save_load_optional_components()







    @unittest.skipIf(torch_device != 'cuda'				,						reason='float16 requires CUDA'			)
    def      UpperCamelCase_ (     self			):
      # Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
      super().test_save_load_floataa(expected_max_diff=1e-1			)







    def      UpperCamelCase_ (     self			):
      self._test_attention_slicing_forward_pass(expected_max_diff=1e-2			)







    def      UpperCamelCase_ (     self			):
      self._test_save_load_local()







    def      UpperCamelCase_ (     self			):
      self._test_inference_batch_single_identical(
          expected_max_diff=1e-2				,						)




from __future__ import annotations
def lowerCamelCase_       (			A			:      list[int]						):




      """simple docstring"""
      if not list_of_ints:
            return []

      if min(A						) < 0:
            raise ValueError('''All numbers must be positive'''						)

      lowerCAmelCase_						=      max(len(bin(A						)[2:]						) for x in list_of_ints						)
      return _msd_radix_sort(A		,					A						)
def lowerCamelCase_       (			A			:      list[int]		,					A			:      int						):




      """simple docstring"""
      if bit_position == 0 or len(A						) in [0, 1]:
            return list_of_ints

      lowerCAmelCase_						=      []
      lowerCAmelCase_						=      []
      # Split numbers based on bit at bit_position from the right
      for number in list_of_ints:
            if (number >> (bit_position - 1)) & 1:
                  # number has a one at bit bit_position
                  ones.append(A						)
            else:
                  # number has a zero at bit bit_position
                  zeros.append(A						)

    # recursively split both lists further
      lowerCAmelCase_						=      _msd_radix_sort(A		,					bit_position - 1						)
      lowerCAmelCase_						=      _msd_radix_sort(A		,					bit_position - 1						)

      # recombine lists
      lowerCAmelCase_						=      zeros
      res.extend(A						)

      return res
def lowerCamelCase_       (			A			:      list[int]						):




      """simple docstring"""
      lowerCAmelCase_						=      len(A						)
      if not list_of_ints or length == 1:
            return

      if min(A						) < 0:
            raise ValueError('''All numbers must be positive'''						)

      lowerCAmelCase_						=      max(len(bin(A						)[2:]						) for x in list_of_ints						)
      _msd_radix_sort_inplace(A		,					A		,					0		,					A						)
def lowerCamelCase_       (			A			:      list[int]		,					A			:      int		,					A			:      int		,					A			:      int						):




      """simple docstring"""
      if bit_position == 0 or end_index - begin_index <= 1:
            return

      bit_position -= 1

      lowerCAmelCase_						=      begin_index
      lowerCAmelCase_						=      end_index - 1
      while i <= j:
            lowerCAmelCase_						=      False
            if not (list_of_ints[i] >> bit_position) & 1:
                  # found zero at the beginning
                  i += 1
                  lowerCAmelCase_						=      True
            if (list_of_ints[j] >> bit_position) & 1:
                  # found one at the end
                  j -= 1
                  lowerCAmelCase_						=      True

            if changed:
                  continue

            lowerCAmelCase_			,		lowerCAmelCase_						=      list_of_ints[j], list_of_ints[i]
            j -= 1
            if j != i:
                  i += 1

      _msd_radix_sort_inplace(A		,					A		,					A		,					A						)
      _msd_radix_sort_inplace(A		,					A		,					A		,					A						)


if __name__ == "__main__":
 import doctest

 doctest.testmod()



