


'''simple docstring'''

from typing import Dict, Optional, Tuple

import torch





def __snake_case (				UpperCAmelCase_						:						torch.Tensor		):
 lowerCamelCase_								=  boundaries[1] - boundaries[0]
 lowerCamelCase_								=  boundaries + step / 2
 lowerCamelCase_								=  torch.cat([bin_centers, (bin_centers[-1] + step).unsqueeze(-1		)] ,    dim=0		)
 return bin_centers





def __snake_case (				UpperCAmelCase_						:						torch.Tensor ,    UpperCAmelCase_						:						torch.Tensor ,    ):
 lowerCamelCase_								=  _calculate_bin_centers(UpperCAmelCase_		)
 return (
     torch.sum(aligned_distance_error_probs * bin_centers ,    dim=-1		),
     bin_centers[-1],
 )





def __snake_case (				UpperCAmelCase_						:						torch.Tensor ,    UpperCAmelCase_						:						int = 31 ,    UpperCAmelCase_						:						int = 64 ,    **UpperCAmelCase_						:						Optional[Any] ,    ):
 lowerCamelCase_								=  torch.linspace(0 ,    UpperCAmelCase_ ,    steps=(no_bins - 1) ,    device=logits.device		)

 lowerCamelCase_								=  torch.nn.functional.softmax(UpperCAmelCase_ ,    dim=-1		)
 lowerCamelCase_			,lowerCamelCase_								=  _calculate_expected_aligned_error(
     alignment_confidence_breaks=UpperCAmelCase_ ,    aligned_distance_error_probs=UpperCAmelCase_ ,    )

 return {
     "aligned_confidence_probs": aligned_confidence_probs,
     "predicted_aligned_error": predicted_aligned_error,
     "max_predicted_aligned_error": max_predicted_aligned_error,
 }







def __snake_case (				UpperCAmelCase_						:						torch.Tensor ,    UpperCAmelCase_						:						Optional[torch.Tensor] = None ,    UpperCAmelCase_						:						int = 31 ,    UpperCAmelCase_						:						int = 64 ,    UpperCAmelCase_						:						float = 1E-8 ,    **UpperCAmelCase_						:						List[Any] ,    ):
 if residue_weights is None:
  lowerCamelCase_								=  logits.new_ones(logits.shape[-2]		)

 lowerCamelCase_								=  torch.linspace(0 ,    UpperCAmelCase_ ,    steps=(no_bins - 1) ,    device=logits.device		)

 lowerCamelCase_								=  _calculate_bin_centers(UpperCAmelCase_		)
 torch.sum(UpperCAmelCase_		)
 lowerCamelCase_								=  logits.shape[-2]
 lowerCamelCase_								=  max(UpperCAmelCase_ ,    19		)

 lowerCamelCase_								=  1.24 * (clipped_n - 15) ** (1.0 / 3) - 1.8

 lowerCamelCase_								=  torch.nn.functional.softmax(UpperCAmelCase_ ,    dim=-1		)

 lowerCamelCase_								=  1.0 / (1 + (bin_centers**2) / (da**2))
 lowerCamelCase_								=  torch.sum(probs * tm_per_bin ,    dim=-1		)

 lowerCamelCase_								=  residue_weights / (eps + residue_weights.sum())
 lowerCamelCase_								=  torch.sum(predicted_tm_term * normed_residue_mask ,    dim=-1		)

 lowerCamelCase_								=  per_alignment * residue_weights

 lowerCamelCase_								=  (weighted == torch.max(UpperCAmelCase_		)).nonzero()[0]
 return per_alignment[tuple(UpperCAmelCase_		)]







'''simple docstring'''

class 					snake_case   :





  """simple docstring"""




  def __init__(   self      ,  UpperCamelCase					):







   """simple docstring"""
   lowerCamelCase_								=  data
   lowerCamelCase_								=  None
   lowerCamelCase_								=  None





def __snake_case (				UpperCAmelCase_						:						BinaryTreeNode | None ,    UpperCAmelCase_						:						int		):
 if node is None:
  lowerCamelCase_								=  BinaryTreeNode(UpperCAmelCase_		)
  return node

 # binary search tree is not empty,
 # so we will insert it into the tree
 # if new_value is less than value of data in node,
 #  add it to left subtree and proceed recursively
 if new_value < node.data:
  lowerCamelCase_								=  insert(node.left_child ,    UpperCAmelCase_		)
 else:
  # if new_value is greater than value of data in node,
  #  add it to right subtree and proceed recursively
  lowerCamelCase_								=  insert(node.right_child ,    UpperCAmelCase_		)
 return node





def __snake_case (				UpperCAmelCase_						:						None | BinaryTreeNode		):  # if node is None,return
 if node:
  lowerCamelCase_								=  inorder(node.left_child		)
  lowerCamelCase_								=  [*inorder_array, node.data]
  lowerCamelCase_								=  inorder_array + inorder(node.right_child		)
 else:
  lowerCamelCase_								=  []
 return inorder_array





def __snake_case (				):
 lowerCamelCase_								=  insert(UpperCAmelCase_ ,    15		)
 insert(UpperCAmelCase_ ,    10		)
 insert(UpperCAmelCase_ ,    25		)
 insert(UpperCAmelCase_ ,    6		)
 insert(UpperCAmelCase_ ,    14		)
 insert(UpperCAmelCase_ ,    20		)
 insert(UpperCAmelCase_ ,    60		)
 return root





def __snake_case (				):
 # main function
 lowerCamelCase_								=  make_tree()
 print("Printing values of binary search tree in Inorder Traversal."		)
 inorder(UpperCAmelCase_		)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()



