





"""simple docstring"""


import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible



class      __SCREAMING_SNAKE_CASE    (						unittest.TestCase   ):







  '''simple docstring'''


  def    __SCREAMING_SNAKE_CASE				(		self   :       Any	)		->				Optional[int]:
        _UpperCamelCase      :	Optional[Any]						=       [
            "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    __SCREAMING_SNAKE_CASE				(		self   :       Tuple	)		->				str:
        _UpperCamelCase      :	Any						=       [
            "unet/diffusion_pytorch_model.bin",
            "unet/diffusion_pytorch_model.safetensors",
        ]
        self.assertTrue(is_safetensors_compatible(__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       str	)		->				int:
        _UpperCamelCase      :	int						=       [
            "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    __SCREAMING_SNAKE_CASE				(		self   :       int	)		->				List[str]:
        _UpperCamelCase      :	Any						=       [
            "text_encoder/pytorch_model.bin",
            "text_encoder/model.safetensors",
        ]
        self.assertTrue(is_safetensors_compatible(__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       int	)		->				int:
        _UpperCamelCase      :	Any						=       [
            "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    __SCREAMING_SNAKE_CASE				(		self   :       Any	)		->				Union[str, Any]:
        _UpperCamelCase      :	Any						=       [
            "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",
        ]
        _UpperCamelCase      :	Optional[int]						=       "fp16"
        self.assertTrue(is_safetensors_compatible(__a					,   variant=__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Any	)		->				Any:
        _UpperCamelCase      :	Optional[Any]						=       [
            "unet/diffusion_pytorch_model.fp16.bin",
            "unet/diffusion_pytorch_model.fp16.safetensors",
        ]
        _UpperCamelCase      :	List[Any]						=       "fp16"
        self.assertTrue(is_safetensors_compatible(__a					,   variant=__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       str	)		->				Union[str, Any]:
        # pass variant but use the non-variant filenames
        _UpperCamelCase      :	int						=       [
            "unet/diffusion_pytorch_model.bin",
            "unet/diffusion_pytorch_model.safetensors",
        ]
        _UpperCamelCase      :	int						=       "fp16"
        self.assertTrue(is_safetensors_compatible(__a					,   variant=__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[Any]	)		->				Union[str, Any]:
        _UpperCamelCase      :	Optional[Any]						=       [
            "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',
        ]
        _UpperCamelCase      :	Tuple						=       "fp16"
        self.assertFalse(is_safetensors_compatible(__a					,   variant=__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Union[str, Any]	)		->				Union[str, Any]:
        _UpperCamelCase      :	int						=       [
            "text_encoder/pytorch_model.fp16.bin",
            "text_encoder/model.fp16.safetensors",
        ]
        _UpperCamelCase      :	int						=       "fp16"
        self.assertTrue(is_safetensors_compatible(__a					,   variant=__a	)	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       int	)		->				int:
        # pass variant but use the non-variant filenames
        _UpperCamelCase      :	Optional[int]						=       [
            "text_encoder/pytorch_model.bin",
            "text_encoder/model.safetensors",
        ]
        _UpperCamelCase      :	Tuple						=       "fp16"
        self.assertTrue(is_safetensors_compatible(__a					,   variant=__a	)	)


  def    __SCREAMING_SNAKE_CASE				(		self   :       List[Any]	)		->				Optional[Any]:
        _UpperCamelCase      :	str						=       [
            "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",
        ]
        _UpperCamelCase      :	Optional[int]						=       "fp16"
        self.assertFalse(is_safetensors_compatible(__a					,   variant=__a	)	)







"""simple docstring"""


from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

lowerCamelCase__				  =   TypeVar("KEY")
lowerCamelCase__				  =   TypeVar("VAL")



@dataclass(frozen=_UpperCamelCase		,  slots=_UpperCamelCase   )
class      __SCREAMING_SNAKE_CASE    (						Generic[KEY, VAL]   ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:KEY
  SCREAMING_SNAKE_CASE__							:VAL





class      __SCREAMING_SNAKE_CASE    (						_Item   ):







  '''simple docstring'''


  def __init__(		self   :       List[str]	)		->				None:
        super().__init__(__a					,   __a	)


  def __bool__(		self   :       Dict	)		->				bool:
        return False





lowerCamelCase__				  =   _DeletedItem()



class      __SCREAMING_SNAKE_CASE    (						MutableMapping[KEY, VAL]   ):







  '''simple docstring'''


  def __init__(		self   :       int					,   __a   :       int = 8					,   __a   :       float = 0.75	)		->				None:
        _UpperCamelCase      :	str						=       initial_block_size
        _UpperCamelCase      :	list[_Item | None]						=       [None] * initial_block_size
        assert 0.0 < capacity_factor < 1.0
        _UpperCamelCase      :	List[str]						=       capacity_factor
        _UpperCamelCase      :	Dict						=       0

  def    __SCREAMING_SNAKE_CASE				(		self   :       int					,   __a   :       KEY	)		->				int:
        return hash(__a	) % len(self._buckets	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[Any]					,   __a   :       int	)		->				int:
        return (ind + 1) % len(self._buckets	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Tuple					,   __a   :       int					,   __a   :       KEY					,   __a   :       VAL	)		->				bool:
        _UpperCamelCase      :	List[Any]						=       self._buckets[ind]
        if not stored:
              _UpperCamelCase      :	Tuple						=       _Item(__a					,   __a	)
              self._len += 1
              return True
        elif stored.key == key:
              _UpperCamelCase      :	Union[str, Any]						=       _Item(__a					,   __a	)
              return True
        else:
              return False

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[str]	)		->				bool:
        _UpperCamelCase      :	Any						=       len(self._buckets	) * self._capacity_factor
        return len(self	) >= int(__a	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       str	)		->				bool:
        if len(self._buckets	) <= self._initial_block_size:
              return False
        _UpperCamelCase      :	List[str]						=       len(self._buckets	) * self._capacity_factor / 2
        return len(self	) < limit

  def    __SCREAMING_SNAKE_CASE				(		self   :       Union[str, Any]					,   __a   :       int	)		->				None:
        _UpperCamelCase      :	Any						=       self._buckets
        _UpperCamelCase      :	List[Any]						=       [None] * new_size
        _UpperCamelCase      :	List[str]						=       0
        for item in old_buckets:
              if item:
                    self._add_item(item.key					,   item.val	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       int	)		->				None:
        self._resize(len(self._buckets	) * 2	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Union[str, Any]	)		->				None:
        self._resize(len(self._buckets	) // 2	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[Any]					,   __a   :       KEY	)		->				Iterator[int]:
        _UpperCamelCase      :	str						=       self._get_bucket_index(__a	)
        for _ in range(len(self._buckets	)	):
              yield ind
              _UpperCamelCase      :	Tuple						=       self._get_next_ind(__a	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Optional[int]					,   __a   :       KEY					,   __a   :       VAL	)		->				None:
        for ind in self._iterate_buckets(__a	):
              if self._try_set(__a					,   __a					,   __a	):
                    break

  def __setitem__(		self   :       int					,   __a   :       KEY					,   __a   :       VAL	)		->				None:
        if self._is_full():
              self._size_up()

        self._add_item(__a					,   __a	)

  def __delitem__(		self   :       str					,   __a   :       KEY	)		->				None:
        for ind in self._iterate_buckets(__a	):
              _UpperCamelCase      :	Tuple						=       self._buckets[ind]
              if item is None:
                    raise KeyError(__a	)
              if item is _deleted:
                    continue
              if item.key == key:
                    _UpperCamelCase      :	List[Any]						=       _deleted
                    self._len -= 1
                    break
        if self._is_sparse():
              self._size_down()

  def __getitem__(		self   :       str					,   __a   :       KEY	)		->				VAL:
        for ind in self._iterate_buckets(__a	):
              _UpperCamelCase      :	Tuple						=       self._buckets[ind]
              if item is None:
                    break
              if item is _deleted:
                    continue
              if item.key == key:
                    return item.val
        raise KeyError(__a	)

  def __len__(		self   :       List[Any]	)		->				int:
        return self._len

  def __iter__(		self   :       List[str]	)		->				Iterator[KEY]:
        yield from (item.key for item in self._buckets if item)


  def __repr__(		self   :       List[str]	)		->				str:
        _UpperCamelCase      :	Optional[int]						=       " ,".join(
            F'''{item.key}: {item.val}''' for item in self._buckets if item	)
        return F'''HashMap({val_string})'''
