
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__ = 21.6875		,						__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)


_snake_case			:       List[Any]      =						{
    "A": ("ABCDEFGHIJKLM", "NOPQRSTUVWXYZ"),
    "B": ("ABCDEFGHIJKLM", "NOPQRSTUVWXYZ"),
    "C": ("ABCDEFGHIJKLM", "ZNOPQRSTUVWXY"),
    "D": ("ABCDEFGHIJKLM", "ZNOPQRSTUVWXY"),
    "E": ("ABCDEFGHIJKLM", "YZNOPQRSTUVWX"),
    "F": ("ABCDEFGHIJKLM", "YZNOPQRSTUVWX"),
    "G": ("ABCDEFGHIJKLM", "XYZNOPQRSTUVW"),
    "H": ("ABCDEFGHIJKLM", "XYZNOPQRSTUVW"),
    "I": ("ABCDEFGHIJKLM", "WXYZNOPQRSTUV"),
    "J": ("ABCDEFGHIJKLM", "WXYZNOPQRSTUV"),
    "K": ("ABCDEFGHIJKLM", "VWXYZNOPQRSTU"),
    "L": ("ABCDEFGHIJKLM", "VWXYZNOPQRSTU"),
    "M": ("ABCDEFGHIJKLM", "UVWXYZNOPQRST"),
    "N": ("ABCDEFGHIJKLM", "UVWXYZNOPQRST"),
    "O": ("ABCDEFGHIJKLM", "TUVWXYZNOPQRS"),
    "P": ("ABCDEFGHIJKLM", "TUVWXYZNOPQRS"),
    "Q": ("ABCDEFGHIJKLM", "STUVWXYZNOPQR"),
    "R": ("ABCDEFGHIJKLM", "STUVWXYZNOPQR"),
    "S": ("ABCDEFGHIJKLM", "RSTUVWXYZNOPQ"),
    "T": ("ABCDEFGHIJKLM", "RSTUVWXYZNOPQ"),
    "U": ("ABCDEFGHIJKLM", "QRSTUVWXYZNOP"),
    "V": ("ABCDEFGHIJKLM", "QRSTUVWXYZNOP"),
    "W": ("ABCDEFGHIJKLM", "PQRSTUVWXYZNO"),
    "X": ("ABCDEFGHIJKLM", "PQRSTUVWXYZNO"),
    "Y": ("ABCDEFGHIJKLM", "OPQRSTUVWXYZN"),
    "Z": ("ABCDEFGHIJKLM", "OPQRSTUVWXYZN"),
}

def    __snake_case       (  __magic_name__	):







				'''simple docstring'''


				return [alphabet[char] for char in key.upper()]

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase						    =			""
				lowercase						    =			0
				lowercase						    =			generate_table(__magic_name__	)
				for char in words.upper():
								cipher += get_opponent(table[count]		,						__magic_name__	)
								lowercase						    =			(count + 1) % len(__magic_name__	)
				return cipher

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				return encrypt(__magic_name__		,						__magic_name__	)

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase						    =			0 if char in table[0] else 1
				lowercase						    =			table[row].index(__magic_name__	)
				return row, col

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase    ,  lowercase						    =			get_position(__magic_name__		,						char.upper()	)
				if row == 1:
								return table[0][col]
				else:
								return table[1][col] if row == 0 else char


if __name__ == "__main__":
						import doctest

						doctest.testmod()  # Fist ensure that all our tests are passing...
						_snake_case			:       List[Any]      =						input("Enter key: ").strip()
						_snake_case			:       Optional[int]      =						input("Enter text to encrypt: ").strip()
						_snake_case			:       Optional[Any]      =						encrypt(key, text)

						print(F"Encrypted: {cipher_text}")
						print(F"Decrypted with key: {decrypt(key, cipher_text)}")
