





'''simple docstring'''







import math
class 				__SCREAMING_SNAKE_CASE  :






				"""simple docstring"""







				def   UpperCamelCase__   (  self     :					List[str]					,				__a     :					list[list[float]]					,				__a     :					list[int]					):
								_a								= 0.0
								_a								= 0.0
								for i in range(len(__a					)					):
												da += math.pow((sample[i] - weights[0][i])					,				2					)
												da += math.pow((sample[i] - weights[1][i])					,				2					)
												return 0 if da > da else 1
								return 0




				def   UpperCamelCase__   (  self     :					List[Any]					,				__a     :					list[list[int | float]]					,				__a     :					list[int]					,				__a     :					int					,				__a     :					float					):
								for i in range(len(__a					)					):
												weights[j][i] += alpha * (sample[i] - weights[j][i])
								return weights






def  _lowerCamelCase				( )	->	None:
				# Training Examples ( m, n )
				_a								= [[1, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 0, 1, 1]]

				# weight initialization ( n, C )
				_a								= [[0.2, 0.6, 0.5, 0.9], [0.8, 0.4, 0.7, 0.3]]

				# training
				_a								= SelfOrganizingMap()
				_a								= 3
				_a								= 0.5

				for _ in range(lowercase						):
								for j in range(len(lowercase						)						):
												# training sample
												_a								= training_samples[j]

												# Compute the winning vector
												_a								= self_organizing_map.get_winner(lowercase    ,							lowercase						)

												# Update the winning vector
												_a								= self_organizing_map.update(lowercase    ,							lowercase    ,							lowercase    ,							lowercase						)

    # classify test sample
				_a								= [0, 0, 0, 1]
				_a								= self_organizing_map.get_winner(lowercase    ,							lowercase						)

				# results
				print(F'Clusters that the test sample belongs to : {winner}'						)
				print(F'Weights that have been trained : {weights}'						)


# running the main() function
if __name__ == "__main__":
					main()







'''simple docstring'''







import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class 				__SCREAMING_SNAKE_CASE  (unittest.TestCase      ):






				"""simple docstring"""







				def   UpperCamelCase__   (  self     :					str					):
								_a								= [
								    "safety_checker/pytorch_model.bin",
								    "safety_checker/model.safetensors",
								    "vae/diffusion_pytorch_model.bin",
								    "vae/diffusion_pytorch_model.safetensors",
								    "text_encoder/pytorch_model.bin",
								    "text_encoder/model.safetensors",
								    "unet/diffusion_pytorch_model.bin",
								    "unet/diffusion_pytorch_model.safetensors",
								]
								self.assertTrue(is_safetensors_compatible(__a					)					)




				def   UpperCamelCase__   (  self     :					List[str]					):
								_a								= [
								    "unet/diffusion_pytorch_model.bin",
								    "unet/diffusion_pytorch_model.safetensors",
								]
								self.assertTrue(is_safetensors_compatible(__a					)					)




				def   UpperCamelCase__   (  self     :					List[str]					):
								_a								= [
								    "safety_checker/pytorch_model.bin",
								    "safety_checker/model.safetensors",
								    "vae/diffusion_pytorch_model.bin",
								    "vae/diffusion_pytorch_model.safetensors",
								    "text_encoder/pytorch_model.bin",
								    "text_encoder/model.safetensors",
								    "unet/diffusion_pytorch_model.bin",
								    # Removed: 'unet/diffusion_pytorch_model.safetensors',
								]
								self.assertFalse(is_safetensors_compatible(__a					)					)




				def   UpperCamelCase__   (  self     :					List[str]					):
								_a								= [
								    "text_encoder/pytorch_model.bin",
								    "text_encoder/model.safetensors",
								]
								self.assertTrue(is_safetensors_compatible(__a					)					)




				def   UpperCamelCase__   (  self     :					Optional[Any]					):
								_a								= [
								    "safety_checker/pytorch_model.bin",
								    "safety_checker/model.safetensors",
								    "vae/diffusion_pytorch_model.bin",
								    "vae/diffusion_pytorch_model.safetensors",
								    "text_encoder/pytorch_model.bin",
								    # Removed: 'text_encoder/model.safetensors',
								    "unet/diffusion_pytorch_model.bin",
								    "unet/diffusion_pytorch_model.safetensors",
								]
								self.assertFalse(is_safetensors_compatible(__a					)					)




				def   UpperCamelCase__   (  self     :					str					):
								_a								= [
								    "safety_checker/pytorch_model.fp16.bin",
								    "safety_checker/model.fp16.safetensors",
								    "vae/diffusion_pytorch_model.fp16.bin",
								    "vae/diffusion_pytorch_model.fp16.safetensors",
								    "text_encoder/pytorch_model.fp16.bin",
								    "text_encoder/model.fp16.safetensors",
								    "unet/diffusion_pytorch_model.fp16.bin",
								    "unet/diffusion_pytorch_model.fp16.safetensors",
								]
								_a								= "fp16"
								self.assertTrue(is_safetensors_compatible(__a					,				variant=__a					)					)




				def   UpperCamelCase__   (  self     :					Any					):
								_a								= [
								    "unet/diffusion_pytorch_model.fp16.bin",
								    "unet/diffusion_pytorch_model.fp16.safetensors",
								]
								_a								= "fp16"
								self.assertTrue(is_safetensors_compatible(__a					,				variant=__a					)					)




				def   UpperCamelCase__   (  self     :					Any					):
								# pass variant but use the non-variant filenames
								_a								= [
								    "unet/diffusion_pytorch_model.bin",
								    "unet/diffusion_pytorch_model.safetensors",
								]
								_a								= "fp16"
								self.assertTrue(is_safetensors_compatible(__a					,				variant=__a					)					)




				def   UpperCamelCase__   (  self     :					Optional[Any]					):
								_a								= [
								    "safety_checker/pytorch_model.fp16.bin",
								    "safety_checker/model.fp16.safetensors",
								    "vae/diffusion_pytorch_model.fp16.bin",
								    "vae/diffusion_pytorch_model.fp16.safetensors",
								    "text_encoder/pytorch_model.fp16.bin",
								    "text_encoder/model.fp16.safetensors",
								    "unet/diffusion_pytorch_model.fp16.bin",
								    # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
								]
								_a								= "fp16"
								self.assertFalse(is_safetensors_compatible(__a					,				variant=__a					)					)




				def   UpperCamelCase__   (  self     :					Dict					):
								_a								= [
								    "text_encoder/pytorch_model.fp16.bin",
								    "text_encoder/model.fp16.safetensors",
								]
								_a								= "fp16"
								self.assertTrue(is_safetensors_compatible(__a					,				variant=__a					)					)




				def   UpperCamelCase__   (  self     :					List[str]					):
								# pass variant but use the non-variant filenames
								_a								= [
								    "text_encoder/pytorch_model.bin",
								    "text_encoder/model.safetensors",
								]
								_a								= "fp16"
								self.assertTrue(is_safetensors_compatible(__a					,				variant=__a					)					)




				def   UpperCamelCase__   (  self     :					Optional[int]					):
								_a								= [
								    "safety_checker/pytorch_model.fp16.bin",
								    "safety_checker/model.fp16.safetensors",
								    "vae/diffusion_pytorch_model.fp16.bin",
								    "vae/diffusion_pytorch_model.fp16.safetensors",
								    "text_encoder/pytorch_model.fp16.bin",
								    # 'text_encoder/model.fp16.safetensors',
								    "unet/diffusion_pytorch_model.fp16.bin",
								    "unet/diffusion_pytorch_model.fp16.safetensors",
								]
								_a								= "fp16"
								self.assertFalse(is_safetensors_compatible(__a					,				variant=__a					)					)
