


from typing import Optional, Tuple

import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule






def 					UpperCamelCase   (      __magic_name__	:				List[str]       ,       __magic_name__	:				Optional[Any]       ,       __magic_name__	:				Any=1E-1_2	)  ->    str:
		"""simple docstring"""




		lowercase__	     =						jnp.divide(emb_a.T       ,       jnp.clip(jnp.linalg.norm(__magic_name__       ,       axis=1	)       ,       a_min=__magic_name__	)	).T
		lowercase__	     =						jnp.divide(emb_a.T       ,       jnp.clip(jnp.linalg.norm(__magic_name__       ,       axis=1	)       ,       a_min=__magic_name__	)	).T
		return jnp.matmul(__magic_name__       ,       norm_emb_a.T	)



class 				A       (			nn.Module				):
					'''simple docstring'''






					A__     =					42
					A__     =					jnp.floataa

					def     lowerCamelCase__	(self       :		Dict						)		->  Dict:




							"""simple docstring"""


							lowercase__	     =						FlaxCLIPVisionModule(self.config.vision_config						)
							lowercase__	     =						nn.Dense(self.config.projection_dim ,   use_bias=_UpperCAmelCase ,   dtype=self.dtype						)

							lowercase__	     =						self.param("""concept_embeds""" ,   jax.nn.initializers.ones ,   (17, self.config.projection_dim)						)
							lowercase__	     =						self.param(
							    """special_care_embeds""" ,   jax.nn.initializers.ones ,   (3, self.config.projection_dim)						)

							lowercase__	     =						self.param("""concept_embeds_weights""" ,   jax.nn.initializers.ones ,   (17,)						)
							lowercase__	     =						self.param("""special_care_embeds_weights""" ,   jax.nn.initializers.ones ,   (3,)						)


					def __call__(self       :		List[str] ,   _UpperCAmelCase       :		List[Any]						)		->  List[str]:




							"""simple docstring"""


							lowercase__	     =						self.vision_model(_UpperCAmelCase						)[1]
							lowercase__	     =						self.visual_projection(_UpperCAmelCase						)

							lowercase__	     =						jax_cosine_distance(_UpperCAmelCase ,   self.special_care_embeds						)
							lowercase__	     =						jax_cosine_distance(_UpperCAmelCase ,   self.concept_embeds						)

							# increase this value to create a stronger `nfsw` filter
							# at the cost of increasing the possibility of filtering benign image inputs
							lowercase__	     =						0.0

							lowercase__	     =						special_cos_dist - self.special_care_embeds_weights[None, :] + adjustment
							lowercase__	     =						jnp.round(_UpperCAmelCase ,   3						)
							lowercase__	     =						jnp.any(special_scores > 0 ,   axis=1 ,   keepdims=_UpperCAmelCase						)
							# Use a lower threshold if an image has any special care concept
							lowercase__	     =						is_special_care * 0.01

							lowercase__	     =						cos_dist - self.concept_embeds_weights[None, :] + special_adjustment
							lowercase__	     =						jnp.round(_UpperCAmelCase ,   3						)
							lowercase__	     =						jnp.any(concept_scores > 0 ,   axis=1						)

							return has_nsfw_concepts






class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					CLIPConfig
					A__     =					'''clip_input'''
					A__     =					FlaxStableDiffusionSafetyCheckerModule

					def __init__(self       :		List[str] ,   _UpperCAmelCase       :		CLIPConfig ,   _UpperCAmelCase       :		Optional[Tuple] = None ,   _UpperCAmelCase       :		int = 0 ,   _UpperCAmelCase       :		jnp.dtype = jnp.floataa ,   _UpperCAmelCase       :		bool = True ,   **_UpperCAmelCase       :		str ,   )		->  Dict:




							"""simple docstring"""


							if input_shape is None:
									lowercase__	     =						(1, 224, 224, 3)
							lowercase__	     =						self.module_class(config=_UpperCAmelCase ,   dtype=_UpperCAmelCase ,   **_UpperCAmelCase						)
							super().__init__(_UpperCAmelCase ,   _UpperCAmelCase ,   input_shape=_UpperCAmelCase ,   seed=_UpperCAmelCase ,   dtype=_UpperCAmelCase ,   _do_init=_do_init						)

					def     lowerCamelCase__	(self       :		int ,   _UpperCAmelCase       :		jax.random.KeyArray ,   _UpperCAmelCase       :		Tuple ,   _UpperCAmelCase       :		FrozenDict = None						)		->  FrozenDict:




							"""simple docstring"""


							lowercase__	     =						jax.random.normal(_UpperCAmelCase ,   _UpperCAmelCase						)

							lowercase__     ,      lowercase__	     =						jax.random.split(_UpperCAmelCase						)
							lowercase__	     =						{"""params""": params_rng, """dropout""": dropout_rng}

							lowercase__	     =						self.module.init(_UpperCAmelCase ,   _UpperCAmelCase						)["""params"""]

							return random_params


					def __call__(self       :		Optional[Any] ,   _UpperCAmelCase       :		List[str] ,   _UpperCAmelCase       :		dict = None ,   )		->  Dict:




							"""simple docstring"""


							lowercase__	     =						jnp.transpose(_UpperCAmelCase ,   (0, 2, 3, 1)						)

							return self.module.apply(
							    {"""params""": params or self.params} ,   jnp.array(_UpperCAmelCase ,   dtype=jnp.floataa						) ,   rngs={} ,   )







UpperCAmelCase_		:					int          =  range(2, 20 + 1)
UpperCAmelCase_		:					Tuple          =  [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_		:					dict[int, dict[int, list[list[int]]]]          =  {}




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase ):
				__magic_name__						:						Union[str, Any]										=sum(a_i[j] for j in range(lowerCamelCase						,  len(lowerCamelCase ) ) )
				__magic_name__						:						Any										=sum(a_i[j] * base[j] for j in range(min(len(lowerCamelCase )						,  lowerCamelCase ) ) )

				__magic_name__					,			__magic_name__						:						Tuple										=0, 0
				__magic_name__						:						Optional[Any]										=n - i

				__magic_name__						:						Union[str, Any]										=memo.get(lowerCamelCase )

				if sub_memo is not None:
								__magic_name__						:						int										=sub_memo.get(lowerCamelCase )

								if jumps is not None and len(lowerCamelCase ) > 0:
												# find and make the largest jump without going over
												__magic_name__						:						Dict										=-1
												for _k in range(len(lowerCamelCase ) - 1						,  -1						,  -1 ):
																if jumps[_k][2] <= k and jumps[_k][1] <= max_dn:
																				__magic_name__						:						Optional[Any]										=_k
																				break

												if max_jump >= 0:
																__magic_name__					,			__magic_name__					,			__magic_name__						:						Optional[int]										=jumps[max_jump]
																# since the difference between jumps is cached, add c
																__magic_name__						:						Tuple										=diff + c
																for j in range(min(lowerCamelCase						,  len(lowerCamelCase ) ) ):
																				__magic_name__					,			__magic_name__						:						Tuple										=divmod(lowerCamelCase						,  10 )
																if new_c > 0:
																				add(lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase )

								else:
												__magic_name__						:						str										=[]
				else:
								__magic_name__						:						List[str]										={c: []}
								__magic_name__						:						List[str]										=sub_memo

				if dn >= max_dn or c + diff >= base[k]:
								return diff, dn

				if k > ks[0]:
								while True:
												# keep doing smaller jumps
												__magic_name__					,			__magic_name__						:						Union[str, Any]										=next_term(lowerCamelCase						,  k - 1						,  i + dn						,  lowerCamelCase )
												diff += _diff
												dn += terms_jumped

												if dn >= max_dn or c + diff >= base[k]:
																break
				else:
								# would be too small a jump, just compute sequential terms instead
								__magic_name__					,			__magic_name__						:						Optional[int]										=compute(lowerCamelCase						,  lowerCamelCase						,  i + dn						,  lowerCamelCase )
								diff += _diff
								dn += terms_jumped

				__magic_name__						:						Tuple										=sub_memo[c]

				# keep jumps sorted by # of terms skipped
				__magic_name__						:						List[Any]										=0
				while j < len(lowerCamelCase ):
								if jumps[j][1] > dn:
												break
								j += 1

				# cache the jump for this value digitsum(b) and c
				sub_memo[c].insert(lowerCamelCase						,  (diff, dn, k) )
				return (diff, dn)




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase ):
				if i >= n:
								return 0, i
				if k > len(lowerCamelCase ):
								a_i.extend([0 for _ in range(k - len(lowerCamelCase ) )] )

				# note: a_i -> b * 10^k + c
				# ds_b -> digitsum(b)
				# ds_c -> digitsum(c)
				__magic_name__						:						Tuple										=i
				__magic_name__					,			__magic_name__					,			__magic_name__						:						Tuple										=0, 0, 0
				for j in range(len(lowerCamelCase ) ):
								if j >= k:
												ds_b += a_i[j]
								else:
												ds_c += a_i[j]

				while i < n:
								i += 1
								__magic_name__						:						Optional[Any]										=ds_c + ds_b
								diff += addend
								__magic_name__						:						str										=0
								for j in range(lowerCamelCase ):
												__magic_name__						:						int										=a_i[j] + addend
												__magic_name__					,			__magic_name__						:						Any										=divmod(lowerCamelCase						,  10 )

												ds_c += a_i[j]

								if addend > 0:
												break

				if addend > 0:
								add(lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase )
				return diff, i - start_i




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase ):
				for j in range(lowerCamelCase						,  len(lowerCamelCase ) ):
								__magic_name__						:						Tuple										=digits[j] + addend
								if s >= 10:
												__magic_name__					,			__magic_name__						:						int										=divmod(lowerCamelCase						,  10 )
												__magic_name__						:						int										=addend // 10 + quotient
								else:
												__magic_name__						:						Dict										=s
												__magic_name__						:						Any										=addend // 10

								if addend == 0:
												break

				while addend > 0:
								__magic_name__					,			__magic_name__						:						Union[str, Any]										=divmod(lowerCamelCase						,  10 )
								digits.append(lowerCamelCase )




def 		lowerCAmelCase_ (						lowerCamelCase = 10**15 ):
				__magic_name__						:						List[str]										=[1]
				__magic_name__						:						str										=1
				__magic_name__						:						str										=0
				while True:
								__magic_name__					,			__magic_name__						:						List[str]										=next_term(lowerCamelCase						,  20						,  i + dn						,  lowerCamelCase )
								dn += terms_jumped
								if dn == n - i:
												break

				__magic_name__						:						int										=0
				for j in range(len(lowerCamelCase ) ):
								a_n += digits[j] * 10**j
				return a_n


if __name__ == "__main__":
							print(F"""{solution() = }""")




