
"""simple docstring"""




import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
   import torch

@require_torch
@require_optimum
@slow
class 						a__		( unittest.TestCase		):
   def      __magic_name__     (     self							):
          lowercase       :							List[str]									=				"hf-internal-testing/tiny-random-t5"
          lowercase       :							Dict									=				AutoTokenizer.from_pretrained(_a							)
          lowercase       :							Dict									=				AutoModelForSeqaSeqLM.from_pretrained(_a							)

          lowercase       :							Any									=				tokenizer("This is me"      ,       return_tensors="pt"							)

          lowercase       :							Dict									=				model.to_bettertransformer()

          self.assertTrue(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules()							)							)

          lowercase       :							Optional[int]									=				model.generate(**_a							)

          lowercase       :							List[Any]									=				model.reverse_bettertransformer()

          self.assertFalse(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules()							)							)

          with tempfile.TemporaryDirectory() as tmpdirname:
                 model.save_pretrained(_a							)

                 lowercase       :							int									=				AutoModelForSeqaSeqLM.from_pretrained(_a							)

                 self.assertFalse(
                     any("BetterTransformer" in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()							)							)

                 lowercase       :							str									=				model_reloaded.generate(**_a							)
                 self.assertTrue(torch.allclose(_a      ,       _a							)							)

   def      __magic_name__     (     self							):
          lowercase       :							List[str]									=				"hf-internal-testing/tiny-random-t5"
          lowercase       :							Optional[int]									=				AutoModelForSeqaSeqLM.from_pretrained(_a							)

          lowercase       :							Tuple									=				model.to_bettertransformer()

          with tempfile.TemporaryDirectory() as tmpdirname:
                 with self.assertRaises(_a							):
                        model.save_pretrained(_a							)

                 lowercase       :							Union[str, Any]									=				model.reverse_bettertransformer()
                 model.save_pretrained(_a							)




"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor


_A     :			Optional[int]  						=			logging.get_logger(__name__)

class 						a__		( a_		):
   def __init__(     self      ,       *_a      ,       **_a							):
          warnings.warn(
              "The class OwlViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
              " use OwlViTImageProcessor instead."      ,       _a      ,       )
          super().__init__(*_a      ,       **_a							)


