
import numpy as np

class      lowerCAmelCase__  :






  def __init__(	self	:							Union[str, Any]							,    SCREAMING_SNAKE_CASE__	:							Optional[int]=5							,    SCREAMING_SNAKE_CASE__	:							Tuple=5						)  ->							List[Any]:
      __lowerCamelCase					      =			depth
      __lowerCamelCase					      =			0
      __lowerCamelCase					      =			None
      __lowerCamelCase					      =			None
      __lowerCamelCase					      =			min_leaf_size
      __lowerCamelCase					      =			None






  def 				__A (	self	:							str							,    SCREAMING_SNAKE_CASE__	:							Dict							,    SCREAMING_SNAKE_CASE__	:							str						)  ->							List[Any]:






      if labels.ndim != 1:
          print('''Error: Input labels must be one dimensional'''						)

      return np.mean((labels - prediction) ** 2						)






  def 				__A (	self	:							Optional[Any]							,    SCREAMING_SNAKE_CASE__	:							List[str]							,    SCREAMING_SNAKE_CASE__	:							Optional[Any]						)  ->							Optional[Any]:






      if x.ndim != 1:
          print('''Error: Input data set must be one dimensional'''						)
          return
      if len(lowerCAmelCase_						) != len(lowerCAmelCase_						):
          print('''Error: X and y have different lengths'''						)
          return
      if y.ndim != 1:
          print('''Error: Data set labels must be one dimensional'''						)
          return

      if len(lowerCAmelCase_						) < 2 * self.min_leaf_size:
          __lowerCamelCase					      =			np.mean(lowerCAmelCase_						)
          return

      if self.depth == 1:
          __lowerCamelCase					      =			np.mean(lowerCAmelCase_						)
          return

      __lowerCamelCase					      =			0
      __lowerCamelCase					      =			self.mean_squared_error(lowerCAmelCase_							,    np.mean(lowerCAmelCase_						)						) * 2
      for i in range(len(lowerCAmelCase_						)						):
          if len(x[:i]						) < self.min_leaf_size:
              continue
          elif len(x[i:]						) < self.min_leaf_size:
              continue
          else:
              __lowerCamelCase					      =			self.mean_squared_error(x[:i]							,    np.mean(y[:i]						)						)
              __lowerCamelCase					      =			self.mean_squared_error(x[i:]							,    np.mean(y[i:]						)						)
              __lowerCamelCase					      =			error_left + error_right
              if error < min_error:
                  __lowerCamelCase					      =			i
                  __lowerCamelCase					      =			error

      if best_split != 0:
          __lowerCamelCase					      =			x[:best_split]
          __lowerCamelCase					      =			y[:best_split]
          __lowerCamelCase					      =			x[best_split:]
          __lowerCamelCase					      =			y[best_split:]

          __lowerCamelCase					      =			x[best_split]
          __lowerCamelCase					      =			DecisionTree(
              depth=self.depth - 1							,    min_leaf_size=self.min_leaf_size						)
          __lowerCamelCase					      =			DecisionTree(
              depth=self.depth - 1							,    min_leaf_size=self.min_leaf_size						)
          self.left.train(lowerCAmelCase_							,    lowerCAmelCase_						)
          self.right.train(lowerCAmelCase_							,    lowerCAmelCase_						)
      else:
          __lowerCamelCase					      =			np.mean(lowerCAmelCase_						)

      return







  def 				__A (	self	:							Any							,    SCREAMING_SNAKE_CASE__	:							Optional[Any]						)  ->							List[Any]:






      if self.prediction is not None:
          return self.prediction
      elif self.left or self.right is not None:
          if x >= self.decision_boundary:
              return self.right.predict(lowerCAmelCase_						)
          else:
              return self.left.predict(lowerCAmelCase_						)
      else:
          print('''Error: Decision tree not yet trained'''						)
          return None





class      lowerCAmelCase__  :






  @staticmethod
  def 				__A (	SCREAMING_SNAKE_CASE__	:							List[Any]							,    SCREAMING_SNAKE_CASE__	:							Any						)  ->							str:
      __lowerCamelCase					      =			float(0						)
      for label in labels:
          squared_error_sum += (label - prediction) ** 2

      return float(squared_error_sum / labels.size						)





def 				__magic_name__				(     )    ->     Optional[Any]:
    __lowerCamelCase					      =			np.arange(-1.0	,						1.0	,						0.005							)
    __lowerCamelCase					      =			np.sin(__lowerCAmelCase							)

    __lowerCamelCase					      =			DecisionTree(depth=10	,						min_leaf_size=10							)
    tree.train(__lowerCAmelCase	,						__lowerCAmelCase							)

    __lowerCamelCase					      =			(np.random.rand(10							) * 2) - 1
    __lowerCamelCase					      =			np.array([tree.predict(__lowerCAmelCase							) for x in test_cases]							)
    __lowerCamelCase					      =			np.mean((predictions - test_cases) ** 2							)

    print('''Test values: ''' + str(__lowerCAmelCase							)							)
    print('''Predictions: ''' + str(__lowerCAmelCase							)							)
    print('''Average error: ''' + str(__lowerCAmelCase							)							)


if __name__ == "__main__":
     main()
     import doctest

     doctest.testmod(name="mean_squarred_error", verbose=True)





from ..utils import deprecate
from .attention_processor import (  # noqa: F401
    Attention,
    AttentionProcessor,
    AttnAddedKVProcessor,
    AttnProcessor2_0,
    LoRAAttnProcessor,
    LoRALinearLayer,
    LoRAXFormersAttnProcessor,
    SlicedAttnAddedKVProcessor,
    SlicedAttnProcessor,
    XFormersAttnProcessor,
)
from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401


deprecate(
    "cross_attention",
    "0.20.0",
    "Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.",
    standard_warn=False,
)


SCREAMING_SNAKE_CASE__     :    Optional[int]      							=					AttentionProcessor

class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							Tuple							,    *SCREAMING_SNAKE_CASE__	:							Dict							,    **SCREAMING_SNAKE_CASE__	:							int						)  ->							List[Any]:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							str							,    *SCREAMING_SNAKE_CASE__	:							Optional[Any]							,    **SCREAMING_SNAKE_CASE__	:							Optional[int]						)  ->							Optional[Any]:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							str							,    *SCREAMING_SNAKE_CASE__	:							List[Any]							,    **SCREAMING_SNAKE_CASE__	:							List[str]						)  ->							List[Any]:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							Optional[int]							,    *SCREAMING_SNAKE_CASE__	:							Optional[int]							,    **SCREAMING_SNAKE_CASE__	:							Tuple						)  ->							Optional[Any]:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							Optional[Any]							,    *SCREAMING_SNAKE_CASE__	:							int							,    **SCREAMING_SNAKE_CASE__	:							Optional[Any]						)  ->							List[str]:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							Tuple							,    *SCREAMING_SNAKE_CASE__	:							Tuple							,    **SCREAMING_SNAKE_CASE__	:							Any						)  ->							Union[str, Any]:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							str							,    *SCREAMING_SNAKE_CASE__	:							Union[str, Any]							,    **SCREAMING_SNAKE_CASE__	:							Tuple						)  ->							int:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)





class      lowerCAmelCase__  (			__lowercase    ):






		def __init__(	self	:							Optional[Any]							,    *SCREAMING_SNAKE_CASE__	:							Any							,    **SCREAMING_SNAKE_CASE__	:							str						)  ->							Dict:
						__lowerCamelCase					      =			f'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'						)						)} instead.'''
						deprecate('''cross_attention'''							,    '''0.20.0'''							,    SCREAMING_SNAKE_CASE__							,    standard_warn=SCREAMING_SNAKE_CASE__						)
						super().__init__(*SCREAMING_SNAKE_CASE__							,    **SCREAMING_SNAKE_CASE__						)



