
"""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 							snake_case       (     unittest.TestCase		):







   def    UpperCAmelCase__	( self)   ->Dict:
      a_						   =     "runwayml/stable-diffusion-v1-5"
      a_						   =     TextToVideoZeroPipeline.from_pretrained(__UpperCAmelCase       ,							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=__UpperCAmelCase       ,							generator=__UpperCAmelCase).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(__UpperCAmelCase       ,							__UpperCAmelCase)

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase_						   =   {
    'configuration_sam': [
        'SAM_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SamConfig',
        'SamMaskDecoderConfig',
        'SamPromptEncoderConfig',
        'SamVisionConfig',
    ],
    'processing_sam': ['SamProcessor'],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_						   =   [
          'SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
          'SamModel',
          'SamPreTrainedModel',
      ]
try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_						   =   [
          'TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFSamModel',
          'TFSamPreTrainedModel',
      ]
try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_						   =   ['SamImageProcessor']


if TYPE_CHECKING:
      from .configuration_sam import (
          SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
          SamConfig,
          SamMaskDecoderConfig,
          SamPromptEncoderConfig,
          SamVisionConfig,
      )
      from .processing_sam import SamProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_sam import SamImageProcessor

else:
      import sys

      UpperCamelCase_						   =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)