

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 					_a		(unittest.TestCase       ):


					'''simple docstring'''






					@slow
					def 						__A    (				self    ):
						A__							:					int       =	AutoImageProcessor.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip"""    )
						A__							:					Dict       =	AutoModelForImageClassification.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip"""    )
						model.to(A__    )

						from datasets import load_dataset

						A__							:					Union[str, Any]       =	load_dataset("""nielsr/rvlcdip-demo"""    )

						A__							:					List[str]       =	dataset["""train"""][0]["""image"""].convert("""RGB"""    )

						A__							:					int       =	image_processor(A__					, return_tensors="""pt"""    ).to(A__    )

						# forward pass
						with torch.no_grad():
							A__							:					Optional[int]       =	model(**A__    )
							A__							:					int       =	outputs.logits

						A__							:					List[str]       =	torch.Size((1, 16)    )
						self.assertEqual(logits.shape					, A__    )

						A__							:					Optional[int]       =	torch.tensor(
						    [-0.4_1_5_8, -0.4_0_9_2, -0.4_3_4_7]					, device=A__					, dtype=torch.float					, )
						self.assertTrue(torch.allclose(logits[0, :3]					, A__					, atol=1e-4    )    )






import os

try:
	from .build_directory_md import good_file_paths
except ImportError:
	from build_directory_md import good_file_paths  # type: ignore

A_ :				Dict						 =    list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

A_ :				Optional[Any]						 =    [file for file in filepaths if file != file.lower()]
if upper_files:
	print(f'''{len(upper_files)} files contain uppercase characters:''')
	print('\n'.join(upper_files) + '\n')

A_ :				Tuple						 =    [file for file in filepaths if ' ' in file]
if space_files:
	print(f'''{len(space_files)} files contain space characters:''')
	print('\n'.join(space_files) + '\n')

A_ :				Any						 =    [file for file in filepaths if '-' in file]
if hyphen_files:
	print(f'''{len(hyphen_files)} files contain hyphen characters:''')
	print('\n'.join(hyphen_files) + '\n')

A_ :				List[str]						 =    [file for file in filepaths if os.sep not in file]
if nodir_files:
	print(f'''{len(nodir_files)} files are not in a directory:''')
	print('\n'.join(nodir_files) + '\n')

A_ :				Any						 =    len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
	import sys

	sys.exit(bad_files)



