"""simple docstring"""






from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					snake_case__				    = 42
					snake_case__				    = 42







					def __init__(				self   :	Tuple    ,lowerCamelCase__   :	UNetaDModel    ,lowerCamelCase__   :	ScoreSdeVeScheduler			):
									super().__init__()
									self.register_modules(unet=lowerCamelCase__    ,scheduler=lowerCamelCase__			)







					@torch.no_grad()
					def __call__(				self   :	str    ,lowerCamelCase__   :	int = 1    ,lowerCamelCase__   :	int = 2_000    ,lowerCamelCase__   :	Optional[Union[torch.Generator, List[torch.Generator]]] = None    ,lowerCamelCase__   :	Optional[str] = "pil"    ,lowerCamelCase__   :	bool = True    ,**lowerCamelCase__   :	Optional[int]    ,):
									UpperCAmelCase__             =							self.unet.config.sample_size
									UpperCAmelCase__             =							(batch_size, 3, img_size, img_size)

									UpperCAmelCase__             =							self.unet

									UpperCAmelCase__             =							randn_tensor(lowerCamelCase__    ,generator=lowerCamelCase__			) * self.scheduler.init_noise_sigma
									UpperCAmelCase__             =							sample.to(self.device			)

									self.scheduler.set_timesteps(lowerCamelCase__			)
									self.scheduler.set_sigmas(lowerCamelCase__			)

									for i, t in enumerate(self.progress_bar(self.scheduler.timesteps			)			):
													UpperCAmelCase__             =							self.scheduler.sigmas[i] * torch.ones(shape[0]    ,device=self.device			)

													# correction step
													for _ in range(self.scheduler.config.correct_steps			):
																	UpperCAmelCase__             =							self.unet(lowerCamelCase__    ,lowerCamelCase__			).sample
																	UpperCAmelCase__             =							self.scheduler.step_correct(lowerCamelCase__    ,lowerCamelCase__    ,generator=lowerCamelCase__			).prev_sample

													# prediction step
													UpperCAmelCase__             =							model(lowerCamelCase__    ,lowerCamelCase__			).sample
													UpperCAmelCase__             =							self.scheduler.step_pred(lowerCamelCase__    ,lowerCamelCase__    ,lowerCamelCase__    ,generator=lowerCamelCase__			)

													UpperCAmelCase__      ,	UpperCAmelCase__             =							output.prev_sample, output.prev_sample_mean

									UpperCAmelCase__             =							sample_mean.clamp(0    ,1			)
									UpperCAmelCase__             =							sample.cpu().permute(0    ,2    ,3    ,1			).numpy()
									if output_type == "pil":
													UpperCAmelCase__             =							self.numpy_to_pil(lowerCamelCase__			)

									if not return_dict:
													return (sample,)

									return ImagePipelineOutput(images=lowerCamelCase__			)




"""simple docstring"""






import os
import sys
import unittest


lowerCAmelCase__  :  Tuple						     =	os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


lowerCAmelCase__  :  Tuple						     =	os.path.join('tests', 'models', 'bert', 'test_modeling_bert.py')
lowerCAmelCase__  :  Optional[Any]						     =	os.path.join('tests', 'models', 'blip', 'test_modeling_blip.py')
class 				snake_case       ( unittest.TestCase				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	List[str]			):
									UpperCAmelCase__             =							get_test_to_tester_mapping(lowerCamelCase__			)
									UpperCAmelCase__             =							get_test_to_tester_mapping(lowerCamelCase__			)

									UpperCAmelCase__             =							{'BertModelTest': 'BertModelTester'}

									UpperCAmelCase__             =							{
									    'BlipModelTest': 'BlipModelTester',
									    'BlipTextImageModelTest': 'BlipTextImageModelsModelTester',
									    'BlipTextModelTest': 'BlipTextModelTester',
									    'BlipTextRetrievalModelTest': 'BlipTextRetrievalModelTester',
									    'BlipVQAModelTest': 'BlipVQAModelTester',
									    'BlipVisionModelTest': 'BlipVisionModelTester',
									}

									self.assertEqual(get_test_info.to_json(lowerCamelCase__			)    ,lowerCamelCase__			)
									self.assertEqual(get_test_info.to_json(lowerCamelCase__			)    ,lowerCamelCase__			)







					def 		__lowerCAmelCase						(				self   :	Optional[Any]			):
									UpperCAmelCase__             =							get_model_to_test_mapping(lowerCamelCase__			)
									UpperCAmelCase__             =							get_model_to_test_mapping(lowerCamelCase__			)

									UpperCAmelCase__             =							{
									    'BertForMaskedLM': ['BertModelTest'],
									    'BertForMultipleChoice': ['BertModelTest'],
									    'BertForNextSentencePrediction': ['BertModelTest'],
									    'BertForPreTraining': ['BertModelTest'],
									    'BertForQuestionAnswering': ['BertModelTest'],
									    'BertForSequenceClassification': ['BertModelTest'],
									    'BertForTokenClassification': ['BertModelTest'],
									    'BertLMHeadModel': ['BertModelTest'],
									    'BertModel': ['BertModelTest'],
									}

									UpperCAmelCase__             =							{
									    'BlipForConditionalGeneration': ['BlipTextImageModelTest'],
									    'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTest'],
									    'BlipForQuestionAnswering': ['BlipVQAModelTest'],
									    'BlipModel': ['BlipModelTest'],
									    'BlipTextModel': ['BlipTextModelTest'],
									    'BlipVisionModel': ['BlipVisionModelTest'],
									}

									self.assertEqual(get_test_info.to_json(lowerCamelCase__			)    ,lowerCamelCase__			)
									self.assertEqual(get_test_info.to_json(lowerCamelCase__			)    ,lowerCamelCase__			)







					def 		__lowerCAmelCase						(				self   :	int			):
									UpperCAmelCase__             =							get_model_to_tester_mapping(lowerCamelCase__			)
									UpperCAmelCase__             =							get_model_to_tester_mapping(lowerCamelCase__			)

									UpperCAmelCase__             =							{
									    'BertForMaskedLM': ['BertModelTester'],
									    'BertForMultipleChoice': ['BertModelTester'],
									    'BertForNextSentencePrediction': ['BertModelTester'],
									    'BertForPreTraining': ['BertModelTester'],
									    'BertForQuestionAnswering': ['BertModelTester'],
									    'BertForSequenceClassification': ['BertModelTester'],
									    'BertForTokenClassification': ['BertModelTester'],
									    'BertLMHeadModel': ['BertModelTester'],
									    'BertModel': ['BertModelTester'],
									}

									UpperCAmelCase__             =							{
									    'BlipForConditionalGeneration': ['BlipTextImageModelsModelTester'],
									    'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTester'],
									    'BlipForQuestionAnswering': ['BlipVQAModelTester'],
									    'BlipModel': ['BlipModelTester'],
									    'BlipTextModel': ['BlipTextModelTester'],
									    'BlipVisionModel': ['BlipVisionModelTester'],
									}

									self.assertEqual(get_test_info.to_json(lowerCamelCase__			)    ,lowerCamelCase__			)
									self.assertEqual(get_test_info.to_json(lowerCamelCase__			)    ,lowerCamelCase__			)



