
import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference







@slow
@require_torch_gpu
class 							lowercase						(   unittest.TestCase						):




							def 					A__ (							self):
												lowercase		      =		'''runwayml/stable-diffusion-v1-5'''
												lowercase		      =		TextToVideoZeroPipeline.from_pretrained(A__  ,torch_dtype=torch.floataa).to('''cuda''')
												lowercase		      =		DDIMScheduler.from_config(pipe.scheduler.config)
												lowercase		      =		torch.Generator(device='''cuda''').manual_seed(0)

												lowercase		      =		'''A bear is playing a guitar on Times Square'''
												lowercase		      =		pipe(prompt=A__  ,generator=A__).images

												lowercase		      =		load_pt(
												    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt''')

												assert_mean_pixel_difference(A__  ,A__)






import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):
							lowercase_			:			Dict			   =['''image_processor''', '''tokenizer''']
							lowercase_			:			List[str]			   ='''AutoImageProcessor'''
							lowercase_			:			Optional[Any]			   ='''AutoTokenizer'''




							def __init__(							self  ,A__=None  ,A__=None  ,**A__):
												lowercase		      =		None
												if "feature_extractor" in kwargs:
																	warnings.warn(
																	    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
																	    ''' instead.'''  ,A__  ,)
																	lowercase		      =		kwargs.pop('''feature_extractor''')

												lowercase		      =		image_processor if image_processor is not None else feature_extractor
												if image_processor is None:
																	raise ValueError('''You need to specify an `image_processor`.''')
												if tokenizer is None:
																	raise ValueError('''You need to specify a `tokenizer`.''')

												super().__init__(A__  ,A__)
												lowercase		      =		self.image_processor
												lowercase		      =		False




							def __call__(							self  ,*A__  ,**A__):
												# For backward compatibility
												if self._in_target_context_manager:
																	return self.current_processor(*A__  ,**A__)

												lowercase		      =		kwargs.pop('''images'''  ,A__)
												lowercase		      =		kwargs.pop('''text'''  ,A__)
												if len(A__) > 0:
																	lowercase		      =		args[0]
																	lowercase		      =		args[1:]

												if images is None and text is None:
																	raise ValueError('''You need to specify either an `images` or `text` input to process.''')

												if images is not None:
																	lowercase		      =		self.image_processor(A__  ,*A__  ,**A__)
												if text is not None:
																	lowercase		      =		self.tokenizer(A__  ,**A__)

												if text is None:
																	return inputs
												elif images is None:
																	return encodings
												else:
																	lowercase		      =		encodings['''input_ids''']
																	return inputs




							def 					A__ (							self  ,*A__  ,**A__):
												return self.tokenizer.batch_decode(*A__  ,**A__)




							def 					A__ (							self  ,*A__  ,**A__):
												return self.tokenizer.decode(*A__  ,**A__)




							@contextmanager
							def 					A__ (							self):
												warnings.warn(
												    '''`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '''
												    '''labels by using the argument `text` of the regular `__call__` method (either in the same call as '''
												    '''your images inputs, or in a separate call.''')
												lowercase		      =		True
												lowercase		      =		self.tokenizer
												yield
												lowercase		      =		self.image_processor
												lowercase		      =		False




							@property
							def 					A__ (							self):
												warnings.warn(
												    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''  ,A__  ,)
												return self.image_processor_class





							@property
							def 					A__ (							self):
												warnings.warn(
												    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''  ,A__  ,)
												return self.image_processor




