


"""simple docstring"""


import copy
import re



class 			lowerCamelCase__						:
						lowerCAmelCase       =     """hp"""
						lowerCAmelCase       =     {}
						lowerCAmelCase       =     None







						@classmethod
						def __a						(							cls   :    Tuple			,			_lowercase   :    Union[str, Any]			,			_lowercase   :    int		):
								A					       = prefix
								A					       = defaults
								cls.build_naming_info()







						@staticmethod
						def __a						(							_lowercase   :    str			,			_lowercase   :    Any		):
								if len(_lowercase		) == 0:
										return ""
								A					       = None
								if any(char.isdigit() for char in word		):
										raise Exception(f'Parameters should not contain numbers: \'{word}\' contains a number'		)
								if word in info["short_word"]:
										return info["short_word"][word]
								for prefix_len in range(1			,			len(_lowercase		) + 1		):
										A					       = word[:prefix_len]
										if prefix in info["reverse_short_word"]:
												continue
										else:
												A					       = prefix
												break

								if short_word is None:
										# Paranoid fallback
										def int_to_alphabetic(_lowercase   :    Tuple		):
												A					       = ''
												while integer != 0:
														A					       = chr(ord('A'		) + integer % 10		) + s
														integer //= 10
												return s

										A					       = 0
										while True:
												A					       = word + '#' + int_to_alphabetic(_lowercase		)
												if sword in info["reverse_short_word"]:
														continue
												else:
														A					       = sword
														break

								A					       = short_word
								A					       = word
								return short_word







						@staticmethod
						def __a						(							_lowercase   :    Tuple			,			_lowercase   :    Any		):
								A					       = param_name.split('_'		)

								A					       = [TrialShortNamer.shortname_for_word(_lowercase			,			_lowercase		) for word in words]

								# We try to create a separatorless short name, but if there is a collision we have to fallback
								# to a separated short name
								A					       = ['', '_']

								for separator in separators:
										A					       = separator.join(_lowercase		)
										if shortname not in info["reverse_short_param"]:
												A					       = shortname
												A					       = param_name
												return shortname

								return param_name







						@staticmethod
						def __a						(							_lowercase   :    Optional[int]			,			_lowercase   :    Union[str, Any]		):
								A					       = TrialShortNamer.shortname_for_key(_lowercase			,			_lowercase		)
								A					       = short_name
								A					       = param_name







						@classmethod
						def __a						(							cls   :    Optional[Any]		):
								if cls.NAMING_INFO is not None:
										return

								A					       = {
								    'short_word': {},
								    'reverse_short_word': {},
								    'short_param': {},
								    'reverse_short_param': {},
								}

								A					       = list(cls.DEFAULTS.keys()		)

								for k in field_keys:
										cls.add_new_param_name(_lowercase			,			_lowercase		)

								A					       = info







						@classmethod
						def __a						(							cls   :    str			,			_lowercase   :    Any		):
								cls.build_naming_info()
								assert cls.PREFIX is not None
								A					       = [copy.copy(cls.PREFIX		)]

								for k, v in params.items():
										if k not in cls.DEFAULTS:
												raise Exception(f'You should provide a default value for the param name {k} with value {v}'		)
										if v == cls.DEFAULTS[k]:
												# The default value is not added to the name
												continue

										A					       = cls.NAMING_INFO['short_param'][k]

										if isinstance(_lowercase			,			_lowercase		):
												A					       = 1 if v else 0

										A					       = '' if isinstance(_lowercase			,			(int, float)		) else '-'
										A					       = f'{key}{sep}{v}'
										name.append(_lowercase		)

								return "_".join(_lowercase		)







						@classmethod
						def __a						(							cls   :    int			,			_lowercase   :    List[Any]		):
								A					       = repr[len(cls.PREFIX		) + 1 :]
								if repr == "":
										A					       = []
								else:
										A					       = repr.split('_'		)

								A					       = {}

								for value in values:
										if "-" in value:
												A       , A					       = value.split('-'		)
										else:
												A					       = re.sub('[0-9.]'			,			''			,			_lowercase		)
												A					       = float(re.sub('[^0-9.]'			,			''			,			_lowercase		)		)

										A					       = cls.NAMING_INFO['reverse_short_param'][p_k]

										A					       = p_v

								for k in cls.DEFAULTS:
										if k not in parameters:
												A					       = cls.DEFAULTS[k]

								return parameters









"""simple docstring"""


import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible



class 			lowerCamelCase__						(   unittest.TestCase			):







						def __a						(							self   :    Dict		):
								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(_lowercase		)		)







						def __a						(							self   :    Union[str, Any]		):
								A					       = [
								    'unet/diffusion_pytorch_model.bin',
								    'unet/diffusion_pytorch_model.safetensors',
								]
								self.assertTrue(is_safetensors_compatible(_lowercase		)		)







						def __a						(							self   :    int		):
								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(_lowercase		)		)







						def __a						(							self   :    Dict		):
								A					       = [
								    'text_encoder/pytorch_model.bin',
								    'text_encoder/model.safetensors',
								]
								self.assertTrue(is_safetensors_compatible(_lowercase		)		)







						def __a						(							self   :    Union[str, 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(_lowercase		)		)







						def __a						(							self   :    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',
								    'unet/diffusion_pytorch_model.fp16.safetensors',
								]
								A					       = 'fp16'
								self.assertTrue(is_safetensors_compatible(_lowercase			,			variant=_lowercase		)		)







						def __a						(							self   :    Union[str, Any]		):
								A					       = [
								    'unet/diffusion_pytorch_model.fp16.bin',
								    'unet/diffusion_pytorch_model.fp16.safetensors',
								]
								A					       = 'fp16'
								self.assertTrue(is_safetensors_compatible(_lowercase			,			variant=_lowercase		)		)







						def __a						(							self   :    Optional[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(_lowercase			,			variant=_lowercase		)		)







						def __a						(							self   :    Dict		):
								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(_lowercase			,			variant=_lowercase		)		)







						def __a						(							self   :    Dict		):
								A					       = [
								    'text_encoder/pytorch_model.fp16.bin',
								    'text_encoder/model.fp16.safetensors',
								]
								A					       = 'fp16'
								self.assertTrue(is_safetensors_compatible(_lowercase			,			variant=_lowercase		)		)







						def __a						(							self   :    Any		):
								# 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(_lowercase			,			variant=_lowercase		)		)







						def __a						(							self   :    List[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.assertFalse(is_safetensors_compatible(_lowercase			,			variant=_lowercase		)		)





