code: 
  
  
  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 					_UpperCamelCase (      unittest.TestCase	):
  
  
  
  
  
  
  
  							'''simple docstring'''
  
  
  
  
  
  
  
  							def 		_UpperCAmelCase	(		self  :				int		):
  													_a     =			'runwayml/stable-diffusion-v1-5'
  													_a     =			TextToVideoZeroPipeline.from_pretrained(SCREAMING_SNAKE_CASE_		,				torch_dtype=torch.floataa		).to('cuda'		)
  													_a     =			DDIMScheduler.from_config(pipe.scheduler.config		)
  													_a     =			torch.Generator(device='cuda'		).manual_seed(0		)
  
  													_a     =			'A bear is playing a guitar on Times Square'
  													_a     =			pipe(prompt=SCREAMING_SNAKE_CASE_		,				generator=SCREAMING_SNAKE_CASE_		).images
  
  													_a     =			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(SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_		)
  
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  lowercase_								=    {
      'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
      'tokenization_codegen': ['CodeGenTokenizer'],
  }
  
  try:
  		if not is_tokenizers_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		lowercase_								=    ['CodeGenTokenizerFast']
  
  try:
  		if not is_torch_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		lowercase_								=    [
  		    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
  		    'CodeGenForCausalLM',
  		    'CodeGenModel',
  		    'CodeGenPreTrainedModel',
  		]
  
  if TYPE_CHECKING:
  		from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
  		from .tokenization_codegen import CodeGenTokenizer
  
  		try:
  				if not is_tokenizers_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .tokenization_codegen_fast import CodeGenTokenizerFast
  
  		try:
  				if not is_torch_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .modeling_codegen import (
  				    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
  				    CodeGenForCausalLM,
  				    CodeGenModel,
  				    CodeGenPreTrainedModel,
  				)
  
  else:
  		import sys
  
  		lowercase_								=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  