
'''simple docstring'''





import unittest

import torch

from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism

from .test_modeling_common import ModelTesterMixin, UNetTesterMixin


enable_full_determinism()


class        UpperCamelCase__     (			UpperCamelCase_					,   UpperCamelCase_					,   unittest.TestCase):
 UpperCAmelCase__			:			Optional[Any]   =    VQModel
 UpperCAmelCase__			:			Tuple   =    'sample'






 @property
 def 		lowercase_  (	self     :Tuple		, _A     :Any=(32, 32)	) ->	Dict:







       '''simple docstring'''



       __A						=	4
       __A						=	3

       __A						=	floats_tensor((batch_size, num_channels) + sizes	).to(UpperCamelCase__	)

       return {"sample": image}






 @property
 def 		lowercase_  (	self     :List[Any]	) ->	Dict:







       '''simple docstring'''



       return (3, 32, 32)






 @property
 def 		lowercase_  (	self     :Union[str, Any]	) ->	str:







       '''simple docstring'''



       return (3, 32, 32)






 def 		lowercase_  (	self     :Union[str, Any]	) ->	int:







       '''simple docstring'''



       __A						=	{
           '''block_out_channels''': [32, 64],
           '''in_channels''': 3,
           '''out_channels''': 3,
           '''down_block_types''': ['''DownEncoderBlock2D''', '''DownEncoderBlock2D'''],
           '''up_block_types''': ['''UpDecoderBlock2D''', '''UpDecoderBlock2D'''],
           '''latent_channels''': 3,
       }
       __A						=	self.dummy_input
       return init_dict, inputs_dict






 def 		lowercase_  (	self     :Optional[int]	) ->	Optional[Any]:







       '''simple docstring'''



       pass






 def 		lowercase_  (	self     :List[Any]	) ->	int:







       '''simple docstring'''



       pass






 def 		lowercase_  (	self     :Dict	) ->	Tuple:







       '''simple docstring'''



       __A						=	VQModel.from_pretrained('fusing/vqgan-dummy'		, output_loading_info=UpperCamelCase__	)
       self.assertIsNotNone(UpperCamelCase__	)
       self.assertEqual(len(loading_info['missing_keys']	)		, 0	)

       model.to(UpperCamelCase__	)
       __A						=	model(**self.dummy_input	)

       assert image is not None, "Make sure output is not None"






 def 		lowercase_  (	self     :List[str]	) ->	Any:







       '''simple docstring'''



       __A						=	VQModel.from_pretrained('fusing/vqgan-dummy'	)
       model.to(UpperCamelCase__	).eval()

       torch.manual_seed(0	)
       if torch.cuda.is_available():
             torch.cuda.manual_seed_all(0	)

       __A						=	torch.randn(1		, model.config.in_channels		, model.config.sample_size		, model.config.sample_size	)
       __A						=	image.to(UpperCamelCase__	)
       with torch.no_grad():
             __A						=	model(UpperCamelCase__	).sample

       __A						=	output[0, -1, -3:, -3:].flatten().cpu()
       # fmt: off
       __A						=	torch.tensor([-0.0_153, -0.4_044, -0.1_880, -0.5_161, -0.2_418, -0.4_072, -0.1_612, -0.0_633, -0.0_143]	)
       # fmt: on
       self.assertTrue(torch.allclose(UpperCamelCase__		, UpperCamelCase__		, atol=1E-3	)	)







import itertools
import string
from collections.abc import Generator, Iterable
def       A	(    _lowercase		,  _lowercase						):
						SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							iter(_lowercase						)
						while True:
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							tuple(itertools.islice(_lowercase		,  _lowercase						)						)
												if not chunk:
																		return
												yield chunk
def       A	(    _lowercase						):
						SCREAMING_SNAKE_CASE							:    int							=							''''''.join([c.upper() for c in dirty if c in string.ascii_letters]						)
						SCREAMING_SNAKE_CASE							:    List[str]							=							''''''

						if len(_lowercase						) < 2:
												return dirty

						for i in range(len(_lowercase						) - 1						):
												clean += dirty[i]

												if dirty[i] == dirty[i + 1]:
																		clean += "X"

						clean += dirty[-1]

						if len(_lowercase						) & 1:
												clean += "X"

						return clean
def       A	(    _lowercase						):
						# I and J are used interchangeably to allow
						# us to use a 5x5 table (25 letters)
						SCREAMING_SNAKE_CASE							:    Optional[Any]							=							'''ABCDEFGHIKLMNOPQRSTUVWXYZ'''
						# we're using a list instead of a '2d' array because it makes the math
						# for setting up the table and doing the actual encoding/decoding simpler
						SCREAMING_SNAKE_CASE							:    List[Any]							=							[]

						# copy key chars into the table if they are in `alphabet` ignoring duplicates
						for char in key.upper():
												if char not in table and char in alphabet:
																		table.append(_lowercase						)

    # fill the rest of the table in with the remaining alphabet chars
						for char in alphabet:
												if char not in table:
																		table.append(_lowercase						)

						return table
def       A	(    _lowercase		,  _lowercase						):
						SCREAMING_SNAKE_CASE							:    Any							=							generate_table(_lowercase						)
						SCREAMING_SNAKE_CASE							:    Any							=							prepare_input(_lowercase						)
						SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							''''''

						# https://en.wikipedia.org/wiki/Playfair_cipher#Description
						for chara, chara in chunker(_lowercase		,  2						):
												SCREAMING_SNAKE_CASE				,  SCREAMING_SNAKE_CASE							:    int							=							divmod(table.index(_lowercase						)		,  5						)
												SCREAMING_SNAKE_CASE				,  SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							divmod(table.index(_lowercase						)		,  5						)

												if rowa == rowa:
																		ciphertext += table[rowa * 5 + (cola + 1) % 5]
																		ciphertext += table[rowa * 5 + (cola + 1) % 5]
												elif cola == cola:
																		ciphertext += table[((rowa + 1) % 5) * 5 + cola]
																		ciphertext += table[((rowa + 1) % 5) * 5 + cola]
												else:  # rectangle
																		ciphertext += table[rowa * 5 + cola]
																		ciphertext += table[rowa * 5 + cola]

						return ciphertext



def       A	(    _lowercase		,  _lowercase						):
						SCREAMING_SNAKE_CASE							:    Any							=							generate_table(_lowercase						)
						SCREAMING_SNAKE_CASE							:    List[Any]							=							''''''

						# https://en.wikipedia.org/wiki/Playfair_cipher#Description
						for chara, chara in chunker(_lowercase		,  2						):
												SCREAMING_SNAKE_CASE				,  SCREAMING_SNAKE_CASE							:    List[str]							=							divmod(table.index(_lowercase						)		,  5						)
												SCREAMING_SNAKE_CASE				,  SCREAMING_SNAKE_CASE							:    Optional[Any]							=							divmod(table.index(_lowercase						)		,  5						)

												if rowa == rowa:
																		plaintext += table[rowa * 5 + (cola - 1) % 5]
																		plaintext += table[rowa * 5 + (cola - 1) % 5]
												elif cola == cola:
																		plaintext += table[((rowa - 1) % 5) * 5 + cola]
																		plaintext += table[((rowa - 1) % 5) * 5 + cola]
												else:  # rectangle
																		plaintext += table[rowa * 5 + cola]
																		plaintext += table[rowa * 5 + cola]

						return plaintext





