


'''simple docstring'''

from functools import partial
from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload

import torch
import torch.nn as nn
import torch.types

def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	torch.Tensor:






       """simple docstring"""







       if not inplace:
              lowercase__				      =			ma + ma
       else:
              ma += ma

       return ma

def _SCREAMING_SNAKE_CASE				(A  ,			A	)	->	torch.Tensor:






       """simple docstring"""







       lowercase__				      =			-1 * len(A	)
       lowercase__				      =			list(range(len(tensor.shape[:zero_index]	)	)	)
       return tensor.permute(first_inds + [zero_index + i for i in inds]	)

def _SCREAMING_SNAKE_CASE				(A  ,			A	)	->	torch.Tensor:






       """simple docstring"""







       return t.reshape(t.shape[:-no_dims] + (-1,)	)

def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A  ,			A = 1E-4	)	->	torch.Tensor:






       """simple docstring"""







       lowercase__				      =			mask.expand(*value.shape	)
       return torch.sum(mask * value  ,			dim=A	) / (eps + torch.sum(A  ,			dim=A	))

def _SCREAMING_SNAKE_CASE				(A  ,			A = 2.3_125  ,			A = 21.6_875  ,			A = 64	)	->	torch.Tensor:






       """simple docstring"""







       lowercase__				      =			torch.linspace(A  ,			A  ,			no_bins - 1  ,			device=pts.device	)
       lowercase__				      =			torch.sqrt(torch.sum((pts.unsqueeze(-2	) - pts.unsqueeze(-3	)) ** 2  ,			dim=-1	)	)
       return torch.bucketize(A  ,			A	)

def _SCREAMING_SNAKE_CASE				(A  ,			A	)	->	dict:






       """simple docstring"""







       lowercase__				      =			dicts[0]
       lowercase__				      =			{}
       for k, v in first.items():
              lowercase__				      =			[d[k] for d in dicts]
              if isinstance(A  ,			A	):
                     lowercase__				      =			dict_multimap(A  ,			A	)
              else:
                     lowercase__				      =			fn(A	)

       return new_dict

def _SCREAMING_SNAKE_CASE				(A  ,			A	)	->	torch.Tensor:






       """simple docstring"""







       lowercase__				      =			v_bins.view(((1,) * len(x.shape	)) + (len(A	),)	)
       lowercase__				      =			x[..., None] - reshaped_bins
       lowercase__				      =			torch.argmin(torch.abs(A	)  ,			dim=-1	)
       return nn.functional.one_hot(A  ,			num_classes=len(A	)	).float()

def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A = 0  ,			A = 0	)	->	torch.Tensor:






       """simple docstring"""







       lowercase__				      =			[]
       for i, s in enumerate(data.shape[:no_batch_dims]	):
              lowercase__				      =			torch.arange(A	)
              lowercase__				      =			r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape	) - i - 1)))	)
              ranges.append(A	)

       lowercase__				      =			[slice(A	) for _ in range(len(data.shape	) - no_batch_dims	)]
       lowercase__				      =			inds
       ranges.extend(A	)
       # Matt note: Editing this to get around the behaviour of using a list as an array index changing
       # in recent Numpy versions
       return data[tuple(A	)]


lowerCamelCase							:       Optional[Any]  						=     TypeVar('T')

def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	Dict[Any, Union[dict, list, tuple, Any]]:






       """simple docstring"""







       lowercase__				      =			{}
       for k, v in dic.items():
              if isinstance(A  ,			A	):
                     lowercase__				      =			dict_map(A  ,			A  ,			A	)
              else:
                     lowercase__				      =			tree_map(A  ,			A  ,			A	)

       return new_dict

@overload
def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	Any:






       """simple docstring"""







       ...

@overload
def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	dict:






       """simple docstring"""







       ...

@overload
def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	list:






       """simple docstring"""







       ...

@overload
def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	tuple:






       """simple docstring"""







       ...

def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	Any:






       """simple docstring"""







       if isinstance(A  ,			A	):
              return dict_map(A  ,			A  ,			A	)
       elif isinstance(A  ,			A	):
              return [tree_map(A  ,			A  ,			A	) for x in tree]
       elif isinstance(A  ,			A	):
              return tuple(tree_map(A  ,			A  ,			A	) for x in tree	)
       elif isinstance(A  ,			A	):
              return fn(A	)
       else:
              print(type(A	)	)
              raise ValueError('''Not supported'''	)

lowerCamelCase							:       List[Any]  						=     partial(tree_map, leaf_type=torch.Tensor)








'''simple docstring'''

def _SCREAMING_SNAKE_CASE				(A	)	->	list:






       """simple docstring"""







       lowercase__				      =			len(A	)

       # Set the gap value to be decreased by a factor of 1.3
       # after each iteration
       lowercase__				      =			1.3

       # Continue sorting until the gap is 1
       while gap > 1:
              # Decrease the gap value
              lowercase__				      =			int(gap / shrink	)

              # Sort the elements using insertion sort
              for i in range(A  ,			len(A	)	):
                     lowercase__				      =			collection[i]
                     lowercase__				      =			i
                     while j >= gap and collection[j - gap] > temp:
                            lowercase__				      =			collection[j - gap]
                            j -= gap
                     lowercase__				      =			temp

       return collection


if __name__ == "__main__":
 import doctest

 doctest.testmod()




