'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a		:  Any   			=			{
    '''configuration_musicgen''': [
        '''MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MusicgenConfig''',
        '''MusicgenDecoderConfig''',
    ],
    '''processing_musicgen''': ['''MusicgenProcessor'''],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a		:  List[Any]   			=			[
      '''MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''MusicgenForConditionalGeneration''',
      '''MusicgenForCausalLM''',
      '''MusicgenModel''',
      '''MusicgenPreTrainedModel''',
  ]

if TYPE_CHECKING:
  from .configuration_musicgen import (
      MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP,
      MusicgenConfig,
      MusicgenDecoderConfig,
  )
  from .processing_musicgen import MusicgenProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_musicgen import (
        MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
        MusicgenForCausalLM,
        MusicgenForConditionalGeneration,
        MusicgenModel,
        MusicgenPreTrainedModel,
    )

else:
  import sys

  a		:  Union[str, Any]   			=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








'''simple docstring'''





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					):



  def 						a_       ( self   ):







      '''simple docstring'''


      _a							:       List[Any]       					=			"""runwayml/stable-diffusion-v1-5"""
      _a							:       Tuple       					=			TextToVideoZeroPipeline.from_pretrained(__lowerCAmelCase		,    torch_dtype=torch.floataa   ).to("""cuda"""   )
      _a							:       Dict       					=			DDIMScheduler.from_config(pipe.scheduler.config   )
      _a							:       int       					=			torch.Generator(device="""cuda"""   ).manual_seed(0   )

      _a							:       Union[str, Any]       					=			"""A bear is playing a guitar on Times Square"""
      _a							:       List[Any]       					=			pipe(prompt=__lowerCAmelCase		,    generator=__lowerCAmelCase   ).images

      _a							:       Any       					=			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(__lowerCAmelCase		,    __lowerCAmelCase   )


