

import os
from collections.abc import Iterator





def    __lowerCamelCase      (					UpperCamelCase__ = "." ):







							'''simple docstring'''






							for dir_path, dir_names, filenames in os.walk(UpperCamelCase__ ):
														snake_case_     							=       [d for d in dir_names if d != 'scripts' and d[0] not in '._']
														for filename in filenames:
																					if filename == "__init__.py":
																												continue
																					if os.path.splitext(UpperCamelCase__ )[1] in (".py", ".ipynb"):
																												yield os.path.join(UpperCamelCase__  ,				UpperCamelCase__ ).lstrip('./' )





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							return F'''{i * "  "}*''' if i else "\n##"





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       old_path.split(os.sep )
							for i, new_part in enumerate(new_path.split(os.sep ) ):
														if (i + 1 > len(UpperCamelCase__ ) or old_parts[i] != new_part) and new_part:
																					print(F'''{md_prefix(UpperCamelCase__ )} {new_part.replace("_"  ,				" " ).title()}''' )
							return new_path





def    __lowerCamelCase      (					UpperCamelCase__ = "." ):







							'''simple docstring'''






							snake_case_     							=       ''
							for filepath in sorted(good_file_paths(UpperCamelCase__ ) ):
														snake_case_							,       snake_case_     							=       os.path.split(UpperCamelCase__ )
														if filepath != old_path:
																					snake_case_     							=       print_path(UpperCamelCase__  ,				UpperCamelCase__ )
														snake_case_     							=       (filepath.count(os.sep ) + 1) if filepath else 0
														snake_case_     							=       F'''{filepath}/{filename}'''.replace(' '  ,				'%20' )
														snake_case_     							=       os.path.splitext(filename.replace('_'  ,				' ' ).title() )[0]
														print(F'''{md_prefix(UpperCamelCase__ )} [{filename}]({url})''' )


if __name__ == "__main__":
					print_directory_md(""".""")







import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
					from PIL import Image

					from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast







@require_vision
class 					lowercase							(			unittest.TestCase     ):




				def        a				(   self			):
											snake_case_     							=       tempfile.mkdtemp()

											snake_case_     							=       BlipImageProcessor()
											snake_case_     							=       GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model'			)

											snake_case_     							=       BlipaProcessor(snake_case ,  snake_case			)

											processor.save_pretrained(self.tmpdirname			)




				def        a				(   self ,  **snake_case			):
											return AutoProcessor.from_pretrained(self.tmpdirname ,  **snake_case			).tokenizer




				def        a				(   self ,  **snake_case			):
											return AutoProcessor.from_pretrained(self.tmpdirname ,  **snake_case			).image_processor




				def        a				(   self			):
											shutil.rmtree(self.tmpdirname			)




				def        a				(   self			):
											snake_case_     							=       [np.random.randint(255 ,  size=(3, 30, 400) ,  dtype=np.uinta			)]

											snake_case_     							=       [Image.fromarray(np.moveaxis(snake_case ,  0 ,  -1			)			) for x in image_inputs]

											return image_inputs




				def        a				(   self			):
											snake_case_     							=       BlipaProcessor(tokenizer=self.get_tokenizer() ,  image_processor=self.get_image_processor()			)
											processor.save_pretrained(self.tmpdirname			)

											snake_case_     							=       self.get_tokenizer(bos_token='(BOS)' ,  eos_token='(EOS)'			)
											snake_case_     							=       self.get_image_processor(do_normalize=snake_case ,  padding_value=1.0			)

											snake_case_     							=       BlipaProcessor.from_pretrained(
											    self.tmpdirname ,  bos_token='(BOS)' ,  eos_token='(EOS)' ,  do_normalize=snake_case ,  padding_value=1.0			)

											self.assertEqual(processor.tokenizer.get_vocab() ,  tokenizer_add_kwargs.get_vocab()			)
											self.assertIsInstance(processor.tokenizer ,  snake_case			)

											self.assertEqual(processor.image_processor.to_json_string() ,  image_processor_add_kwargs.to_json_string()			)
											self.assertIsInstance(processor.image_processor ,  snake_case			)




				def        a				(   self			):
											snake_case_     							=       self.get_image_processor()
											snake_case_     							=       self.get_tokenizer()

											snake_case_     							=       BlipaProcessor(tokenizer=snake_case ,  image_processor=snake_case			)

											snake_case_     							=       self.prepare_image_inputs()

											snake_case_     							=       image_processor(snake_case ,  return_tensors='np'			)
											snake_case_     							=       processor(images=snake_case ,  return_tensors='np'			)

											for key in input_feat_extract.keys():
																		self.assertAlmostEqual(input_feat_extract[key].sum() ,  input_processor[key].sum() ,  delta=1e-2			)




				def        a				(   self			):
											snake_case_     							=       self.get_image_processor()
											snake_case_     							=       self.get_tokenizer()

											snake_case_     							=       BlipaProcessor(tokenizer=snake_case ,  image_processor=snake_case			)

											snake_case_     							=       'lower newer'

											snake_case_     							=       processor(text=snake_case			)

											snake_case_     							=       tokenizer(snake_case ,  return_token_type_ids=snake_case			)

											for key in encoded_tok.keys():
																		self.assertListEqual(encoded_tok[key] ,  encoded_processor[key]			)




				def        a				(   self			):
											snake_case_     							=       self.get_image_processor()
											snake_case_     							=       self.get_tokenizer()

											snake_case_     							=       BlipaProcessor(tokenizer=snake_case ,  image_processor=snake_case			)

											snake_case_     							=       'lower newer'
											snake_case_     							=       self.prepare_image_inputs()

											snake_case_     							=       processor(text=snake_case ,  images=snake_case			)

											self.assertListEqual(list(inputs.keys()			) ,  ['pixel_values', 'input_ids', 'attention_mask']			)

											# test if it raises when no input is passed
											with pytest.raises(snake_case			):
																		processor()




				def        a				(   self			):
											snake_case_     							=       self.get_image_processor()
											snake_case_     							=       self.get_tokenizer()

											snake_case_     							=       BlipaProcessor(tokenizer=snake_case ,  image_processor=snake_case			)

											snake_case_     							=       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

											snake_case_     							=       processor.batch_decode(snake_case			)
											snake_case_     							=       tokenizer.batch_decode(snake_case			)

											self.assertListEqual(snake_case ,  snake_case			)




				def        a				(   self			):
											snake_case_     							=       self.get_image_processor()
											snake_case_     							=       self.get_tokenizer()

											snake_case_     							=       BlipaProcessor(tokenizer=snake_case ,  image_processor=snake_case			)

											snake_case_     							=       'lower newer'
											snake_case_     							=       self.prepare_image_inputs()

											snake_case_     							=       processor(text=snake_case ,  images=snake_case			)

											# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
											self.assertListEqual(list(inputs.keys()			) ,  ['pixel_values', 'input_ids', 'attention_mask']			)




