'''simple docstring'''




import os
import re
import shutil
import sys
import tempfile
import unittest

import black


_a   :	Tuple 							=   os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
_a   :	Optional[int] 							=   "    \"\"\"\n    Output class for the scheduler's step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"\"\"\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n"






class 		__A       (unittest.TestCase   ):






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Any       				=		tempfile.mkdtemp()
              os.makedirs(os.path.join(self.diffusers_dir				,     "schedulers/"      )      )
              __UpperCAmelCase  :				List[str]       				=		self.diffusers_dir
              shutil.copy(
                  os.path.join(UpperCamelCase_				,     "src/diffusers/schedulers/scheduling_ddpm.py"      )				,     os.path.join(self.diffusers_dir				,     "schedulers/scheduling_ddpm.py"      )				,     )






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Optional[int]       				=		"src/diffusers"
              shutil.rmtree(self.diffusers_dir      )






       def 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_				,     UpperCamelCase_				,     UpperCamelCase_=None      ):
              __UpperCAmelCase  :				str       				=		comment + f"""\nclass {class_name}(nn.Module):\n""" + class_code
              if overwrite_result is not None:
                     __UpperCAmelCase  :				Any       				=		comment + f"""\nclass {class_name}(nn.Module):\n""" + overwrite_result
              __UpperCAmelCase  :				Dict       				=		black.Mode(target_versions={black.TargetVersion.PYaa}				,     line_length=1_19      )
              __UpperCAmelCase  :				Dict       				=		black.format_str(UpperCamelCase_				,     mode=UpperCamelCase_      )
              __UpperCAmelCase  :				Dict       				=		os.path.join(self.diffusers_dir				,     "new_code.py"      )
              with open(UpperCamelCase_				,     "w"				,     newline="\n"      ) as f:
                     f.write(UpperCamelCase_      )
              if overwrite_result is None:
                     self.assertTrue(len(check_copies.is_copy_consistent(UpperCamelCase_      )      ) == 0      )
              else:
                     check_copies.is_copy_consistent(f.name				,     overwrite=UpperCamelCase_      )
                     with open(UpperCamelCase_				,     "r"      ) as f:
                            self.assertTrue(f.read()				,     UpperCamelCase_      )






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Any       				=		check_copies.find_code_in_diffusers("schedulers.scheduling_ddpm.DDPMSchedulerOutput"      )
              self.assertEqual(UpperCamelCase_				,     UpperCamelCase_      )







       def 			_snake_case						(      self      ):
              # Base copy consistency
              self.check_copy_consistency(
                  "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"				,     "DDPMSchedulerOutput"				,     REFERENCE_CODE + "\n"				,     )

              # With no empty line at the end
              self.check_copy_consistency(
                  "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"				,     "DDPMSchedulerOutput"				,     UpperCamelCase_				,     )

              # Copy consistency with rename
              self.check_copy_consistency(
                  "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"				,     "TestSchedulerOutput"				,     re.sub("DDPM"				,     "Test"				,     UpperCamelCase_      )				,     )

              # Copy consistency with a really long name
              __UpperCAmelCase  :				int       				=		"TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason"
              self.check_copy_consistency(
                  f"""# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}"""				,     f"""{long_class_name}SchedulerOutput"""				,     re.sub("Bert"				,     UpperCamelCase_				,     UpperCamelCase_      )				,     )

              # Copy consistency with overwrite
              self.check_copy_consistency(
                  "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"				,     "TestSchedulerOutput"				,     UpperCamelCase_				,     overwrite_result=re.sub("DDPM"				,     "Test"				,     UpperCamelCase_      )				,     )







'''simple docstring'''




from collections import Counter

import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

_a   :	str 							=   datasets.load_iris()

_a   :	List[Any] 							=   np.array(data["data"])
_a   :	Optional[Any] 							=   np.array(data["target"])
_a   :	Dict 							=   data["target_names"]

_a							,					_a							,					_a							,					_a   :	Any 							=   train_test_split(X, y)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       Tuple:





       """simple docstring"""


       return np.linalg.norm(np.array(lowerCamelCase__						) - np.array(lowerCamelCase__						)						)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__=5						)					->       int:





       """simple docstring"""


       __UpperCAmelCase  :				List[Any]       				=		zip(lowerCamelCase__							,    lowerCamelCase__						)
       # List of distances of all points from the point to be classified
       __UpperCAmelCase  :				int       				=		[]
       for data_point in data:
              __UpperCAmelCase  :				Optional[Any]       				=		euclidean_distance(data_point[0]							,    lowerCamelCase__						)
              distances.append((distance, data_point[1])						)
       # Choosing 'k' points with the least distances.
       __UpperCAmelCase  :				Union[str, Any]       				=		[i[1] for i in sorted(lowerCamelCase__						)[:k]]
       # Most commonly occurring class among them
       # is the class into which the point is classified
       __UpperCAmelCase  :				Dict       				=		Counter(lowerCamelCase__						).most_common(1						)[0][0]
       return classes[result]


if __name__ == "__main__":
   print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))






