
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__		,						__magic_name__	):







    '''simple docstring'''


    if start == end:
        return start if lst[start] > item else start + 1
    if start > end:
        return start

    lowercase						    =			(start + end) // 2
    if lst[mid] < item:
        return binary_search(__magic_name__		,						__magic_name__		,						mid + 1		,						__magic_name__	)
    elif lst[mid] > item:
        return binary_search(__magic_name__		,						__magic_name__		,						__magic_name__		,						mid - 1	)
    else:
        return mid

def    __snake_case       (  __magic_name__	):







    '''simple docstring'''


    lowercase						    =			len(__magic_name__	)

    for index in range(1		,						__magic_name__	):
        lowercase						    =			lst[index]
        lowercase						    =			binary_search(__magic_name__		,						__magic_name__		,						0		,						index - 1	)
        lowercase						    =			lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]

    return lst

def    __snake_case       (  __magic_name__		,						__magic_name__	):







    '''simple docstring'''


    if not left:
        return right

    if not right:
        return left

    if left[0] < right[0]:
        return [left[0], *merge(left[1:]		,						__magic_name__	)]

    return [right[0], *merge(__magic_name__		,						right[1:]	)]

def    __snake_case       (  __magic_name__	):







    '''simple docstring'''


    lowercase						    =			len(__magic_name__	)
    lowercase    ,  lowercase						    =			[], []
    lowercase						    =			[lst[0]]
    lowercase						    =			[]
    lowercase						    =			1
    while i < length:
        if lst[i] < lst[i - 1]:
            runs.append(__magic_name__	)
            lowercase						    =			[lst[i]]
        else:
            new_run.append(lst[i]	)
        i += 1
    runs.append(__magic_name__	)

    for run in runs:
        sorted_runs.append(insertion_sort(__magic_name__	)	)
    for run in sorted_runs:
        lowercase						    =			merge(__magic_name__		,						__magic_name__	)

    return sorted_array

def    __snake_case       (  ):







    '''simple docstring'''


    lowercase						    =			[5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7]
    lowercase						    =			tim_sort(__magic_name__	)
    print(__magic_name__	)


if __name__ == "__main__":
      main()


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    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


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

				return ma

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


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

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


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

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__		,						__magic_name__ = 1e-4	):







				'''simple docstring'''


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

def    __snake_case       (  __magic_name__		,						__magic_name__ = 2.3_1_2_5		,						__magic_name__ = 2_1.6_8_7_5		,						__magic_name__ = 64	):







				'''simple docstring'''


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

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


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

				return new_dict

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


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

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__ = 0		,						__magic_name__ = 0	):







				'''simple docstring'''


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

				lowercase						    =			[slice(__magic_name__	) for _ in range(len(data.shape	) - no_batch_dims	)]
				lowercase						    =			inds
				ranges.extend(__magic_name__	)
				# 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(__magic_name__	)]


_snake_case			:       List[Any]      =						TypeVar("T")

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


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

				return new_dict

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


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




_snake_case			:       Union[str, Any]      =						partial(tree_map, leaf_type=torch.Tensor)
