

import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible






class _UpperCamelCase				(				unittest.TestCase ):
			'''simple docstring'''







			def 				__UpperCamelCase			(      self				:			Any						)				->							int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   str					  =							[
				    "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[Any]						)				->							Tuple:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Tuple					  =							[
				    "unet/diffusion_pytorch_model.bin",
				    "unet/diffusion_pytorch_model.safetensors",
				]
				self.assertTrue(is_safetensors_compatible(a						)						)
			def 				__UpperCamelCase			(      self				:			Tuple						)				->							List[str]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   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",
				    # Removed: 'unet/diffusion_pytorch_model.safetensors',
				]
				self.assertFalse(is_safetensors_compatible(a						)						)
			def 				__UpperCamelCase			(      self				:			List[Any]						)				->							Dict:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							[
				    "text_encoder/pytorch_model.bin",
				    "text_encoder/model.safetensors",
				]
				self.assertTrue(is_safetensors_compatible(a						)						)
			def 				__UpperCamelCase			(      self				:			List[Any]						)				->							Optional[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[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",
				    # Removed: 'text_encoder/model.safetensors',
				    "unet/diffusion_pytorch_model.bin",
				    "unet/diffusion_pytorch_model.safetensors",
				]
				self.assertFalse(is_safetensors_compatible(a						)						)
			def 				__UpperCamelCase			(      self				:			Any						)				->							int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   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",
				]
				SCREAMING_SNAKE_CASE :   str					  =							"fp16"
				self.assertTrue(is_safetensors_compatible(a   ,   variant=a						)						)
			def 				__UpperCamelCase			(      self				:			Tuple						)				->							Dict:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   str					  =							[
				    "unet/diffusion_pytorch_model.fp16.bin",
				    "unet/diffusion_pytorch_model.fp16.safetensors",
				]
				SCREAMING_SNAKE_CASE :   int					  =							"fp16"
				self.assertTrue(is_safetensors_compatible(a   ,   variant=a						)						)
			def 				__UpperCamelCase			(      self				:			Dict						)				->							Union[str, Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Any					  =							[
				    "unet/diffusion_pytorch_model.bin",
				    "unet/diffusion_pytorch_model.safetensors",
				]
				SCREAMING_SNAKE_CASE :   Tuple					  =							"fp16"
				self.assertTrue(is_safetensors_compatible(a   ,   variant=a						)						)
			def 				__UpperCamelCase			(      self				:			str						)				->							List[str]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   int					  =							[
				    "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',
				]
				SCREAMING_SNAKE_CASE :   List[Any]					  =							"fp16"
				self.assertFalse(is_safetensors_compatible(a   ,   variant=a						)						)
			def 				__UpperCamelCase			(      self				:			List[str]						)				->							Any:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							[
				    "text_encoder/pytorch_model.fp16.bin",
				    "text_encoder/model.fp16.safetensors",
				]
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							"fp16"
				self.assertTrue(is_safetensors_compatible(a   ,   variant=a						)						)
			def 				__UpperCamelCase			(      self				:			Union[str, Any]						)				->							Optional[Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							[
				    "text_encoder/pytorch_model.bin",
				    "text_encoder/model.safetensors",
				]
				SCREAMING_SNAKE_CASE :   int					  =							"fp16"
				self.assertTrue(is_safetensors_compatible(a   ,   variant=a						)						)






			def 				__UpperCamelCase			(      self				:			Union[str, Any]						)				->							Tuple:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							[
				    "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",
				]
				SCREAMING_SNAKE_CASE :   List[str]					  =							"fp16"
				self.assertFalse(is_safetensors_compatible(a   ,   variant=a						)						)


from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap

def 			lowerCamelCase__			(       _a):
	return getitem, k

def 			lowerCamelCase__			(       _a				,      _a):
	return setitem, k, v

def 			lowerCamelCase__			(       _a):
	return delitem, k

def 			lowerCamelCase__			(       _a				,      _a				,      *_a):
	try:
		return fun(_a				,      *_a), None
	except Exception as e:
		return None, e


a_      =     (
    _set('key_a', 'val_a'),
    _set('key_b', 'val_b'),
)

a_      =     [
    _set('key_a', 'val_a'),
    _set('key_a', 'val_b'),
]

a_      =     [
    _set('key_a', 'val_a'),
    _set('key_b', 'val_b'),
    _del('key_a'),
    _del('key_b'),
    _set('key_a', 'val_a'),
    _del('key_a'),
]

a_      =     [
    _get('key_a'),
    _del('key_a'),
    _set('key_a', 'val_a'),
    _del('key_a'),
    _del('key_a'),
    _get('key_a'),
]

a_      =     [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

a_      =     [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set('key_a', 'val_b'),
]

@pytest.mark.parametrize(
    "operations"				,      (
        pytest.param(_add_items				,      id="add items"),
        pytest.param(_overwrite_items				,      id="overwrite items"),
        pytest.param(_delete_items				,      id="delete items"),
        pytest.param(_access_absent_items				,      id="access absent items"),
        pytest.param(_add_with_resize_up				,      id="add with resize up"),
        pytest.param(_add_with_resize_down				,      id="add with resize down"),
    )				,      )
def 			lowerCamelCase__			(       _a):
	SCREAMING_SNAKE_CASE :   Dict					  =							HashMap(initial_block_size=4)
	SCREAMING_SNAKE_CASE :   List[str]					  =							{}
	for _, (fun, *args) in enumerate(_a):
		SCREAMING_SNAKE_CASE  ,SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							_run_operation(_a				,      _a				,      *_a)
		SCREAMING_SNAKE_CASE  ,SCREAMING_SNAKE_CASE :   List[Any]					  =							_run_operation(_a				,      _a				,      *_a)
		assert my_res == py_res
		assert str(_a) == str(_a)
		assert set(_a) == set(_a)
		assert len(_a) == len(_a)
		assert set(my.items()) == set(py.items())


def 			lowerCamelCase__			(       ):
	def is_public(_a) -> bool:
		return not name.startswith("_")

	SCREAMING_SNAKE_CASE :   List[str]					  =							{name for name in dir({}) if is_public(_a)}
	SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							{name for name in dir(HashMap()) if is_public(_a)}

	assert dict_public_names > hash_public_names