



"""simple docstring"""

lowercase__					:						Union[str, Any]												=			{
    '''Pillow''': '''Pillow''',
    '''accelerate''': '''accelerate>=0.11.0''',
    '''compel''': '''compel==0.1.8''',
    '''black''': '''black~=23.1''',
    '''datasets''': '''datasets''',
    '''filelock''': '''filelock''',
    '''flax''': '''flax>=0.4.1''',
    '''hf-doc-builder''': '''hf-doc-builder>=0.3.0''',
    '''huggingface-hub''': '''huggingface-hub>=0.13.2''',
    '''requests-mock''': '''requests-mock==1.10.0''',
    '''importlib_metadata''': '''importlib_metadata''',
    '''invisible-watermark''': '''invisible-watermark''',
    '''isort''': '''isort>=5.5.4''',
    '''jax''': '''jax>=0.2.8,!=0.3.2''',
    '''jaxlib''': '''jaxlib>=0.1.65''',
    '''Jinja2''': '''Jinja2''',
    '''k-diffusion''': '''k-diffusion>=0.0.12''',
    '''torchsde''': '''torchsde''',
    '''note_seq''': '''note_seq''',
    '''librosa''': '''librosa''',
    '''numpy''': '''numpy''',
    '''omegaconf''': '''omegaconf''',
    '''parameterized''': '''parameterized''',
    '''protobuf''': '''protobuf>=3.20.3,<4''',
    '''pytest''': '''pytest''',
    '''pytest-timeout''': '''pytest-timeout''',
    '''pytest-xdist''': '''pytest-xdist''',
    '''ruff''': '''ruff>=0.0.241''',
    '''safetensors''': '''safetensors''',
    '''sentencepiece''': '''sentencepiece>=0.1.91,!=0.1.92''',
    '''scipy''': '''scipy''',
    '''onnx''': '''onnx''',
    '''regex''': '''regex!=2019.12.17''',
    '''requests''': '''requests''',
    '''tensorboard''': '''tensorboard''',
    '''torch''': '''torch>=1.4''',
    '''torchvision''': '''torchvision''',
    '''transformers''': '''transformers>=4.25.1''',
    '''urllib3''': '''urllib3<=2.0.0''',
}










"""simple docstring"""

import unittest

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device


if is_torch_available():
     import torch

     from transformers import AutoModelForImageClassification

if is_vision_available():
     from transformers import AutoImageProcessor




@require_torch
@require_vision
class  _UpperCAmelCase (    unittest.TestCase):

 @slow
 def 		_snake_case      (  self	: List[Any]       ):
     snake_case_				:  List[Any]       =			AutoImageProcessor.from_pretrained('''microsoft/dit-base-finetuned-rvlcdip'''       )
     snake_case_				:  List[Any]       =			AutoModelForImageClassification.from_pretrained('''microsoft/dit-base-finetuned-rvlcdip'''       )
     model.to(lowercase_       )

     from datasets import load_dataset

     snake_case_				:  str       =			load_dataset('''nielsr/rvlcdip-demo'''       )

     snake_case_				:  Tuple       =			dataset['''train'''][0]['''image'''].convert('''RGB'''       )

     snake_case_				:  Union[str, Any]       =			image_processor(lowercase_						,  return_tensors='''pt'''       ).to(lowercase_       )

     # forward pass
     with torch.no_grad():
         snake_case_				:  List[Any]       =			model(**lowercase_       )
         snake_case_				:  int       =			outputs.logits

     snake_case_				:  Any       =			torch.Size((1, 16)       )
     self.assertEqual(logits.shape						,  lowercase_       )

     snake_case_				:  Any       =			torch.tensor(
         [-0.41_58, -0.40_92, -0.43_47]						,  device=lowercase_						,  dtype=torch.float						,  )
     self.assertTrue(torch.allclose(logits[0, :3]						,  lowercase_						,  atol=1E-4       )       )





