


"""simple docstring"""




import os
import unittest

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    BertTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english





@require_tokenizers
class  snake_case     (							__lowercase       ,			unittest.TestCase   ):
							UpperCAmelCase__						     =      BertTokenizer
							UpperCAmelCase__						     =      BertTokenizerFast
							UpperCAmelCase__						     =      True
							UpperCAmelCase__						     =      True
							UpperCAmelCase__						     =      filter_non_english

							def _lowercase					(self    ):

									"""simple docstring"""







									super().setUp()

									SCREAMING_SNAKE_CASE_						 = [
									    '''[UNK]''',
									    '''[CLS]''',
									    '''[SEP]''',
									    '''[PAD]''',
									    '''[MASK]''',
									    '''want''',
									    '''##want''',
									    '''##ed''',
									    '''wa''',
									    '''un''',
									    '''runn''',
									    '''##ing''',
									    ''',''',
									    '''low''',
									    '''lowest''',
									]
									SCREAMING_SNAKE_CASE_						 = os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''vocab_file''']    )
									with open(self.vocab_file       ,       '''w'''       ,       encoding='''utf-8'''    ) as vocab_writer:
											vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]    )    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = '''UNwant\u00E9d,running'''
									SCREAMING_SNAKE_CASE_						 = '''unwanted, running'''
									return input_text, output_text

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.tokenizer_class(self.vocab_file    )

									SCREAMING_SNAKE_CASE_						 = tokenizer.tokenize('''UNwant\u00E9d,running'''    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       ['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']    )
									self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_    )       ,       [9, 6, 7, 12, 10, 11]    )

							def _lowercase					(self    ):

									"""simple docstring"""







									if not self.test_rust_tokenizer:
											return

									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_rust_tokenizer()

									SCREAMING_SNAKE_CASE_						 = '''UNwant\u00E9d,running'''

									SCREAMING_SNAKE_CASE_						 = tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = tokenizer.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = rust_tokenizer.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = self.get_rust_tokenizer()
									SCREAMING_SNAKE_CASE_						 = tokenizer.encode(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = rust_tokenizer.encode(SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									# With lower casing
									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer(do_lower_case=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.get_rust_tokenizer(do_lower_case=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = '''UNwant\u00E9d,running'''

									SCREAMING_SNAKE_CASE_						 = tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = tokenizer.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = rust_tokenizer.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = self.get_rust_tokenizer()
									SCREAMING_SNAKE_CASE_						 = tokenizer.encode(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = rust_tokenizer.encode(SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer()

									self.assertListEqual(tokenizer.tokenize('''ah\u535A\u63A8zz'''    )       ,       ['''ah''', '''\u535A''', '''\u63A8''', '''zz''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''    )       ,       ['''hello''', '''!''', '''how''', '''are''', '''you''', '''?''']    )
									self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''    )       ,       ['''hello''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_       ,       strip_accents=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''    )       ,       ['''hällo''', '''!''', '''how''', '''are''', '''you''', '''?''']    )
									self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''    )       ,       ['''h\u00E9llo''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_       ,       strip_accents=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''    )       ,       ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']    )
									self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''    )       ,       ['''hello''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''    )       ,       ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']    )
									self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''    )       ,       ['''hello''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''    )       ,       ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_       ,       strip_accents=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''    )       ,       ['''HäLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_       ,       strip_accents=SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''    )       ,       ['''HaLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_       ,       never_split=['''[UNK]''']    )

									self.assertListEqual(
									    tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU? [UNK]'''    )       ,       ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''', '''[UNK]''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = BasicTokenizer()
									SCREAMING_SNAKE_CASE_						 = '''a\n\'ll !!to?\'d of, can\'t.'''
									SCREAMING_SNAKE_CASE_						 = ['''a''', '''\'''', '''ll''', '''!''', '''!''', '''to''', '''?''', '''\'''', '''d''', '''of''', ''',''', '''can''', '''\'''', '''t''', '''.''']
									self.assertListEqual(tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )       ,       SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

									SCREAMING_SNAKE_CASE_						 = {}
									for i, token in enumerate(SCREAMING_SNAKE_CASE_    ):
											SCREAMING_SNAKE_CASE_						 = i
									SCREAMING_SNAKE_CASE_						 = WordpieceTokenizer(vocab=SCREAMING_SNAKE_CASE_       ,       unk_token='''[UNK]'''    )

									self.assertListEqual(tokenizer.tokenize(''''''    )       ,       []    )

									self.assertListEqual(tokenizer.tokenize('''unwanted running'''    )       ,       ['''un''', '''##want''', '''##ed''', '''runn''', '''##ing''']    )

									self.assertListEqual(tokenizer.tokenize('''unwantedX running'''    )       ,       ['''[UNK]''', '''runn''', '''##ing''']    )

							def _lowercase					(self    ):

									"""simple docstring"""







									self.assertTrue(_is_whitespace(''' '''    )    )
									self.assertTrue(_is_whitespace('''\t'''    )    )
									self.assertTrue(_is_whitespace('''\r'''    )    )
									self.assertTrue(_is_whitespace('''\n'''    )    )
									self.assertTrue(_is_whitespace('''\u00A0'''    )    )

									self.assertFalse(_is_whitespace('''A'''    )    )
									self.assertFalse(_is_whitespace('''-'''    )    )

							def _lowercase					(self    ):

									"""simple docstring"""







									self.assertTrue(_is_control('''\u0005'''    )    )

									self.assertFalse(_is_control('''A'''    )    )
									self.assertFalse(_is_control(''' '''    )    )
									self.assertFalse(_is_control('''\t'''    )    )
									self.assertFalse(_is_control('''\r'''    )    )

							def _lowercase					(self    ):

									"""simple docstring"""







									self.assertTrue(_is_punctuation('''-'''    )    )
									self.assertTrue(_is_punctuation('''$'''    )    )
									self.assertTrue(_is_punctuation('''`'''    )    )
									self.assertTrue(_is_punctuation('''.'''    )    )

									self.assertFalse(_is_punctuation('''A'''    )    )
									self.assertFalse(_is_punctuation(''' '''    )    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_rust_tokenizer()

									# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
									self.assertListEqual([tokenizer.tokenize(SCREAMING_SNAKE_CASE_    ) for t in ['''Test''', '''\xad''', '''test''']]       ,       [['''[UNK]'''], [], ['''[UNK]''']]    )

									self.assertListEqual(
									    [rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_    ) for t in ['''Test''', '''\xad''', '''test''']]       ,       [['''[UNK]'''], [], ['''[UNK]''']]    )

							@slow
							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.tokenizer_class.from_pretrained('''bert-base-uncased'''    )

									SCREAMING_SNAKE_CASE_						 = tokenizer.encode('''sequence builders'''       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = tokenizer.encode('''multi-sequence build'''       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									assert encoded_sentence == [1_01] + text + [1_02]
									assert encoded_pair == [1_01] + text + [1_02] + text_a + [1_02]

							def _lowercase					(self    ):

									"""simple docstring"""







									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'    ):
													SCREAMING_SNAKE_CASE_						 = self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )

													SCREAMING_SNAKE_CASE_						 = f'A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'
													SCREAMING_SNAKE_CASE_						 = tokenizer_r.encode_plus(
													    SCREAMING_SNAKE_CASE_       ,       return_attention_mask=SCREAMING_SNAKE_CASE_       ,       return_token_type_ids=SCREAMING_SNAKE_CASE_       ,       return_offsets_mapping=SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_       ,       )

													SCREAMING_SNAKE_CASE_						 = tokenizer_r.do_lower_case if hasattr(SCREAMING_SNAKE_CASE_       ,       '''do_lower_case'''    ) else False
													SCREAMING_SNAKE_CASE_						 = (
													    [
													        ((0, 0), tokenizer_r.cls_token),
													        ((0, 1), '''A'''),
													        ((1, 2), ''','''),
													        ((3, 5), '''na'''),
													        ((5, 6), '''##ï'''),
													        ((6, 8), '''##ve'''),
													        ((9, 15), tokenizer_r.mask_token),
													        ((16, 21), '''Allen'''),
													        ((21, 23), '''##NL'''),
													        ((23, 24), '''##P'''),
													        ((25, 33), '''sentence'''),
													        ((33, 34), '''.'''),
													        ((0, 0), tokenizer_r.sep_token),
													    ]
													    if not do_lower_case
													    else [
													        ((0, 0), tokenizer_r.cls_token),
													        ((0, 1), '''a'''),
													        ((1, 2), ''','''),
													        ((3, 8), '''naive'''),
													        ((9, 15), tokenizer_r.mask_token),
													        ((16, 21), '''allen'''),
													        ((21, 23), '''##nl'''),
													        ((23, 24), '''##p'''),
													        ((25, 33), '''sentence'''),
													        ((33, 34), '''.'''),
													        ((0, 0), tokenizer_r.sep_token),
													    ]
													)

													self.assertEqual(
													    [e[1] for e in expected_results]       ,       tokenizer_r.convert_ids_to_tokens(tokens['''input_ids''']    )    )
													self.assertEqual([e[0] for e in expected_results]       ,       tokens['''offset_mapping''']    )







							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = ['''的''', '''人''', '''有''']
									SCREAMING_SNAKE_CASE_						 = ''''''.join(SCREAMING_SNAKE_CASE_    )
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'    ):
													SCREAMING_SNAKE_CASE_						 = True
													SCREAMING_SNAKE_CASE_						 = self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )
													SCREAMING_SNAKE_CASE_						 = self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )

													SCREAMING_SNAKE_CASE_						 = tokenizer_p.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
													SCREAMING_SNAKE_CASE_						 = tokenizer_r.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )

													SCREAMING_SNAKE_CASE_						 = tokenizer_r.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_    )
													SCREAMING_SNAKE_CASE_						 = tokenizer_p.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_    )

													# it is expected that each Chinese character is not preceded by "##"
													self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
													self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

													SCREAMING_SNAKE_CASE_						 = False
													SCREAMING_SNAKE_CASE_						 = self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )
													SCREAMING_SNAKE_CASE_						 = self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )

													SCREAMING_SNAKE_CASE_						 = tokenizer_r.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
													SCREAMING_SNAKE_CASE_						 = tokenizer_p.encode(SCREAMING_SNAKE_CASE_       ,       add_special_tokens=SCREAMING_SNAKE_CASE_    )

													SCREAMING_SNAKE_CASE_						 = tokenizer_r.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_    )
													SCREAMING_SNAKE_CASE_						 = tokenizer_p.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_    )

													# it is expected that only the first Chinese character is not preceded by "##".
													SCREAMING_SNAKE_CASE_						 = [
													    f'##{token}' if idx != 0 else token for idx, token in enumerate(SCREAMING_SNAKE_CASE_    )
													]
													self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
													self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

"""simple docstring"""




import warnings
from typing import List, Optional, Tuple, Union

import numpy as np
import PIL
import torch

from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput


lowerCAmelCase__							=				logging.get_logger(__name__)  # pylint: disable=invalid-name



def        _lowerCamelCase ( __a    ):
		warnings.warn(
		    '''The preprocess method is deprecated and will be removed in a future version. Please'''
		    ''' use VaeImageProcessor.preprocess instead''',							__a,							)
		if isinstance(__a,							torch.Tensor    ):
				return image
		elif isinstance(__a,							PIL.Image.Image    ):
				SCREAMING_SNAKE_CASE_						 = [image]

		if isinstance(image[0],							PIL.Image.Image    ):
				SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = image[0].size
				SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = (x - x % 8 for x in (w, h))  # resize to integer multiple of 8

				SCREAMING_SNAKE_CASE_						 = [np.array(i.resize((w, h),							resample=PIL_INTERPOLATION['''lanczos''']    )    )[None, :] for i in image]
				SCREAMING_SNAKE_CASE_						 = np.concatenate(__a,							axis=0    )
				SCREAMING_SNAKE_CASE_						 = np.array(__a    ).astype(np.floataa    ) / 2_5_5.0
				SCREAMING_SNAKE_CASE_						 = image.transpose(0,							3,							1,							2    )
				SCREAMING_SNAKE_CASE_						 = 2.0 * image - 1.0
				SCREAMING_SNAKE_CASE_						 = torch.from_numpy(__a    )
		elif isinstance(image[0],							torch.Tensor    ):
				SCREAMING_SNAKE_CASE_						 = torch.cat(__a,							dim=0    )
		return image



def        _lowerCamelCase ( __a    ):
		if isinstance(__a,							torch.Tensor    ):
				return mask
		elif isinstance(__a,							PIL.Image.Image    ):
				SCREAMING_SNAKE_CASE_						 = [mask]

		if isinstance(mask[0],							PIL.Image.Image    ):
				SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = mask[0].size
				SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = (x - x % 32 for x in (w, h))  # resize to integer multiple of 32
				SCREAMING_SNAKE_CASE_						 = [np.array(m.convert('''L'''    ).resize((w, h),							resample=PIL_INTERPOLATION['''nearest''']    )    )[None, :] for m in mask]
				SCREAMING_SNAKE_CASE_						 = np.concatenate(__a,							axis=0    )
				SCREAMING_SNAKE_CASE_						 = mask.astype(np.floataa    ) / 2_5_5.0
				SCREAMING_SNAKE_CASE_						 = 0
				SCREAMING_SNAKE_CASE_						 = 1
				SCREAMING_SNAKE_CASE_						 = torch.from_numpy(__a    )
		elif isinstance(mask[0],							torch.Tensor    ):
				SCREAMING_SNAKE_CASE_						 = torch.cat(__a,							dim=0    )
		return mask





class  snake_case     (							__lowercase   ):
							UpperCAmelCase__						     =      42
							UpperCAmelCase__						     =      42

							def __init__(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									super().__init__()
									self.register_modules(unet=SCREAMING_SNAKE_CASE_       ,       scheduler=SCREAMING_SNAKE_CASE_    )







							@torch.no_grad()
							def __call__(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = 2_50       ,       SCREAMING_SNAKE_CASE_ = 0.0       ,       SCREAMING_SNAKE_CASE_ = 10       ,       SCREAMING_SNAKE_CASE_ = 10       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = "pil"       ,       SCREAMING_SNAKE_CASE_ = True       ,       ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = image

									SCREAMING_SNAKE_CASE_						 = _preprocess_image(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = original_image.to(device=self.device       ,       dtype=self.unet.dtype    )
									SCREAMING_SNAKE_CASE_						 = _preprocess_mask(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = mask_image.to(device=self.device       ,       dtype=self.unet.dtype    )

									SCREAMING_SNAKE_CASE_						 = original_image.shape[0]

									# sample gaussian noise to begin the loop
									if isinstance(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ) and len(SCREAMING_SNAKE_CASE_    ) != batch_size:
											raise ValueError(
											    f'You have passed a list of generators of length {len(SCREAMING_SNAKE_CASE_    )}, but requested an effective batch'
											    f' size of {batch_size}. Make sure the batch size matches the length of the generators.'    )

									SCREAMING_SNAKE_CASE_						 = original_image.shape
									SCREAMING_SNAKE_CASE_						 = randn_tensor(SCREAMING_SNAKE_CASE_       ,       generator=SCREAMING_SNAKE_CASE_       ,       device=self.device       ,       dtype=self.unet.dtype    )

									# set step values
									self.scheduler.set_timesteps(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       self.device    )
									SCREAMING_SNAKE_CASE_						 = eta

									SCREAMING_SNAKE_CASE_						 = self.scheduler.timesteps[0] + 1
									SCREAMING_SNAKE_CASE_						 = generator[0] if isinstance(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ) else generator
									for i, t in enumerate(self.progress_bar(self.scheduler.timesteps    )    ):
											if t < t_last:
													# predict the noise residual
													SCREAMING_SNAKE_CASE_						 = self.unet(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ).sample
													# compute previous image: x_t -> x_t-1
													SCREAMING_SNAKE_CASE_						 = self.scheduler.step(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ).prev_sample

											else:
													# compute the reverse: x_t-1 -> x_t
													SCREAMING_SNAKE_CASE_						 = self.scheduler.undo_step(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
											SCREAMING_SNAKE_CASE_						 = t

									SCREAMING_SNAKE_CASE_						 = (image / 2 + 0.5).clamp(0       ,       1    )
									SCREAMING_SNAKE_CASE_						 = image.cpu().permute(0       ,       2       ,       3       ,       1    ).numpy()
									if output_type == "pil":
											SCREAMING_SNAKE_CASE_						 = self.numpy_to_pil(SCREAMING_SNAKE_CASE_    )

									if not return_dict:
											return (image,)

									return ImagePipelineOutput(images=SCREAMING_SNAKE_CASE_    )