






import os
from collections.abc import Iterator




def      __A					(     _lowercase = "." ):

					'''simple docstring'''







					for dir_path, dir_names, filenames in os.walk(_lowercase ):
										_A								= [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(_lowercase )[1] in (".py", ".ipynb"):
																				yield os.path.join(_lowercase					,			_lowercase ).lstrip('''./''' )




def      __A					(     _lowercase ):

					'''simple docstring'''







					return f"""{i * "  "}*""" if i else "\n##"




def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







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




def      __A					(     _lowercase = "." ):

					'''simple docstring'''







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


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











import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin





class 						SCREAMING_SNAKE_CASE				( snake_case  ,	unittest.TestCase					):





							"""simple docstring"""

							A_						  =					BlenderbotSmallTokenizer
							A_						  =					False

							def       __A (  self:   List[str]   )    ->				int:
												super().setUp()

												_A								= ['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
												_A								= dict(zip(__A		,     range(len(__A   )   )   )   )

												_A								= ['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
												_A								= {'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

												_A								= os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['''vocab_file''']   )
												_A								= os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['''merges_file''']   )
												with open(self.vocab_file		,     '''w'''		,     encoding='''utf-8'''   ) as fp:
																	fp.write(json.dumps(__A   ) + '''\n'''   )
												with open(self.merges_file		,     '''w'''		,     encoding='''utf-8'''   ) as fp:
																	fp.write('''\n'''.join(__A   )   )

							def       __A (  self:   str		,     **__A:   Optional[Any]   )    ->				Dict:
												kwargs.update(self.special_tokens_map   )
												return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname		,     **__A   )

							def       __A (  self:   str		,     __A:   List[str]   )    ->				int:
												_A								= '''adapt act apte'''
												_A								= '''adapt act apte'''
												return input_text, output_text

							def       __A (  self:   Union[str, Any]   )    ->				Any:
												_A								= BlenderbotSmallTokenizer(self.vocab_file		,     self.merges_file		,     **self.special_tokens_map   )
												_A								= '''adapt act apte'''
												_A								= ['''adapt''', '''act''', '''ap@@''', '''te''']
												_A								= tokenizer.tokenize(__A   )
												self.assertListEqual(__A		,     __A   )

												_A								= [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

												_A								= [0, 1, 2, 3, 4, 5]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(__A   )		,     __A   )

							def       __A (  self:   Any   )    ->				List[str]:
												_A								= BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''   )
												assert tok('''sam'''   ).input_ids == [13_84]
												_A								= '''I am a small frog.'''
												_A								= tok([src_text]		,     padding=__A		,     truncation=__A   )['''input_ids''']
												_A								= tok.batch_decode(__A		,     skip_special_tokens=__A		,     clean_up_tokenization_spaces=__A   )[0]
												assert src_text != decoded  # I wish it did!
												assert decoded == "i am a small frog ."



							def       __A (  self:   Any   )    ->				int:
												_A								= BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''   )
												_A								= '''I am a small frog .'''
												_A								= '''.'''
												_A								= tok(__A   )['''input_ids''']
												_A								= tok(__A   )['''input_ids''']

												assert encoded[-1] == encoded_dot[0]



