




import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict

import requests
from slack_sdk import WebClient


UpperCAmelCase_									=	WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])




def 					lowerCamelCase__       (						A__       :					Union[str, Any]	):





       '''simple docstring'''



       __lowerCamelCase   =						test_results.split(""" """	)

       __lowerCamelCase   =						0
       __lowerCamelCase   =						0

       # When the output is short enough, the output is surrounded by = signs: "== OUTPUT =="
       # When it is too long, those signs are not present.
       __lowerCamelCase   =						expressions[-2] if """=""" in expressions[-1] else expressions[-1]

       for i, expression in enumerate(A__	):
              if "failed" in expression:
                     failed += int(expressions[i - 1]	)
              if "passed" in expression:
                     success += int(expressions[i - 1]	)

       return failed, success, time_spent




def 					lowerCamelCase__       (						A__       :					Optional[int]	):





       '''simple docstring'''



       __lowerCamelCase   =						{}
       __lowerCamelCase   =						None
       __lowerCamelCase   =						False
       for line in failures_short_lines.split("""\n"""	):
              if re.search(R"""_ \[doctest\]"""  ,			A__	):
                     __lowerCamelCase   =						True
                     __lowerCamelCase   =						line.split(""" """	)[2]
              elif in_error and not line.split(""" """	)[0].isdigit():
                     __lowerCamelCase   =						line
                     __lowerCamelCase   =						False

       return failures





class     lowerCamelCase__:
      def __init__(				self: int    ,       UpperCamelCase_: str    ,       UpperCamelCase_: Dict   ):
             __lowerCamelCase   =						title

             __lowerCamelCase   =						doc_test_results["""time_spent"""].split(""","""   )[0]
             __lowerCamelCase   =						doc_test_results["""success"""]
             __lowerCamelCase   =						doc_test_results["""failures"""]
             __lowerCamelCase   =						self.n_success + self.n_failures

             # Failures and success of the modeling tests
             __lowerCamelCase   =						doc_test_results
      @property
      def 			lowerCAmelCase__						(				self: List[str]   ):
             __lowerCamelCase   =						[self._time_spent]
             __lowerCamelCase   =						0

             for time in time_spent:
                    __lowerCamelCase   =						time.split(""":"""   )

                    # Time can be formatted as xx:xx:xx, as .xx, or as x.xx if the time spent was less than a minute.
                    if len(UpperCamelCase_   ) == 1:
                           __lowerCamelCase   =						[0, 0, time_parts[0]]

                    __lowerCamelCase,   __lowerCamelCase,   __lowerCamelCase   =						int(time_parts[0]   ), int(time_parts[1]   ), float(time_parts[2]   )
                    total_secs += hours * 36_00 + minutes * 60 + seconds

             __lowerCamelCase,   __lowerCamelCase,   __lowerCamelCase   =						total_secs // 36_00, (total_secs % 36_00) // 60, total_secs % 60
             return F'{int(UpperCamelCase_   )}h{int(UpperCamelCase_   )}m{int(UpperCamelCase_   )}s'
      @property
      def 			lowerCAmelCase__						(				self: List[str]   ):
             return {"type": "header", "text": {"type": "plain_text", "text": self.title}}
      @property
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             return {
                 "type": "section",
                 "text": {
                     "type": "plain_text",
                     "text": F'🌞 There were no failures: all {self.n_tests} tests passed. The suite ran in {self.time}.',
                     "emoji": True,
                 },
                 "accessory": {
                     "type": "button",
                     "text": {"type": "plain_text", "text": "Check Action results", "emoji": True},
                     "url": F'https://github.com/huggingface/transformers/actions/runs/{os.environ["GITHUB_RUN_ID"]}',
                 },
             }
      @property
      def 			lowerCAmelCase__						(				self: Optional[int]   ):
             return {
                 "type": "section",
                 "text": {
                     "type": "plain_text",
                     "text": (
                         F'There were {self.n_failures} failures, out of {self.n_tests} tests.\nThe suite ran in'
                         F' {self.time}.'
                     ),
                     "emoji": True,
                 },
                 "accessory": {
                     "type": "button",
                     "text": {"type": "plain_text", "text": "Check Action results", "emoji": True},
                     "url": F'https://github.com/huggingface/transformers/actions/runs/{os.environ["GITHUB_RUN_ID"]}',
                 },
             }
      @property
      def 			lowerCAmelCase__						(				self: str   ):
             __lowerCamelCase   =						40
             __lowerCamelCase   =						{k: v["""failed"""] for k, v in doc_test_results.items() if isinstance(UpperCamelCase_    ,       UpperCamelCase_   )}

             __lowerCamelCase   =						""""""
             for category, failures in category_failures.items():
                    if len(UpperCamelCase_   ) == 0:
                           continue

                    if report != "":
                           report += "\n\n"

                    report += F'*{category} failures*:'.ljust(line_length // 2   ).rjust(line_length // 2   ) + "\n"
                    report += "`"
                    report += "`\n`".join(UpperCamelCase_   )
                    report += "`"

             return {
                 "type": "section",
                 "text": {
                     "type": "mrkdwn",
                     "text": F'The following examples had failures:\n\n\n{report}\n',
                 },
             }
      @property
      def 			lowerCAmelCase__						(				self: List[str]   ):
             __lowerCamelCase   =						[self.header]

             if self.n_failures > 0:
                    blocks.append(self.failures   )

             if self.n_failures > 0:
                    blocks.extend([self.category_failures]   )

             if self.n_failures == 0:
                    blocks.append(self.no_failures   )

             return json.dumps(UpperCamelCase_   )
      @staticmethod
      def 			lowerCAmelCase__						(				):
             __lowerCamelCase   =						[
                 {
                     """type""": """section""",
                     """text""": {
                         """type""": """plain_text""",
                         """text""": """There was an issue running the tests.""",
                     },
                     """accessory""": {
                         """type""": """button""",
                         """text""": {"""type""": """plain_text""", """text""": """Check Action results""", """emoji""": True},
                         """url""": F'https://github.com/huggingface/transformers/actions/runs/{os.environ["GITHUB_RUN_ID"]}',
                     },
                 }
             ]

             print("""Sending the following payload"""   )
             print(json.dumps({"""blocks""": json.loads(UpperCamelCase_   )}   )   )

             client.chat_postMessage(
                 channel=os.environ["""CI_SLACK_CHANNEL_ID_DAILY"""]    ,       text="""There was an issue running the tests."""    ,       blocks=UpperCamelCase_    ,       )
      def 			lowerCAmelCase__						(				self: int   ):
             print("""Sending the following payload"""   )
             print(json.dumps({"""blocks""": json.loads(self.payload   )}   )   )

             __lowerCamelCase   =						F'{self.n_failures} failures out of {self.n_tests} tests,' if self.n_failures else """All tests passed."""

             __lowerCamelCase   =						client.chat_postMessage(
                 channel=os.environ["""CI_SLACK_CHANNEL_ID_DAILY"""]    ,       blocks=self.payload    ,       text=UpperCamelCase_    ,       )
      def 			lowerCAmelCase__						(				self: List[Any]    ,       UpperCamelCase_: List[str]    ,       UpperCamelCase_: Tuple    ,       UpperCamelCase_: Optional[Any]    ,       UpperCamelCase_: Tuple   ):
             __lowerCamelCase   =						""""""
             for key, value in failures.items():
                    __lowerCamelCase   =						value[:2_00] + """ [Truncated]""" if len(UpperCamelCase_   ) > 2_50 else value
                    failures_text += F'*{key}*\n_{value}_\n\n'

             __lowerCamelCase   =						job_name
             __lowerCamelCase   =						{"""type""": """section""", """text""": {"""type""": """mrkdwn""", """text""": text}}

             if job_link is not None:
                    __lowerCamelCase   =						{
                        """type""": """button""",
                        """text""": {"""type""": """plain_text""", """text""": """GitHub Action job""", """emoji""": True},
                        """url""": job_link,
                    }

             return [
                 {"type": "header", "text": {"type": "plain_text", "text": title.upper(), "emoji": True}},
                 content,
                 {"type": "section", "text": {"type": "mrkdwn", "text": failures_text}},
             ]




      def 			lowerCAmelCase__						(				self: List[Any]   ):
             if self.thread_ts is None:
                    raise ValueError("""Can only post reply if a post has been made."""   )

             __lowerCamelCase   =						self.doc_test_results.pop("""job_link"""   )
             self.doc_test_results.pop("""failures"""   )
             self.doc_test_results.pop("""success"""   )
             self.doc_test_results.pop("""time_spent"""   )

             __lowerCamelCase   =						sorted(self.doc_test_results.items()    ,       key=lambda UpperCamelCase_   : t[0]   )
             for job, job_result in sorted_dict:
                    if len(job_result["""failures"""]   ):
                           __lowerCamelCase   =						F'*Num failures* :{len(job_result["failed"]   )} \n'
                           __lowerCamelCase   =						job_result["""failures"""]
                           __lowerCamelCase   =						self.get_reply_blocks(UpperCamelCase_    ,       UpperCamelCase_    ,       UpperCamelCase_    ,       text=UpperCamelCase_   )

                           print("""Sending the following reply"""   )
                           print(json.dumps({"""blocks""": blocks}   )   )

                           client.chat_postMessage(
                               channel=os.environ["""CI_SLACK_CHANNEL_ID_DAILY"""]    ,       text=F'Results for {job}'    ,       blocks=UpperCamelCase_    ,       thread_ts=self.thread_ts["""ts"""]    ,       )

                           time.sleep(1   )




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						os.environ["""GITHUB_RUN_ID"""]
       __lowerCamelCase   =						f'https://api.github.com/repos/huggingface/transformers/actions/runs/{run_id}/jobs?per_page=100'
       __lowerCamelCase   =						requests.get(A__	).json()
       __lowerCamelCase   =						{}

       try:
              jobs.update({job["""name"""]: job["""html_url"""] for job in result["""jobs"""]}	)
              __lowerCamelCase   =						math.ceil((result["""total_count"""] - 100) / 100	)

              for i in range(A__	):
                     __lowerCamelCase   =						requests.get(url + f'&page={i + 2}'	).json()
                     jobs.update({job["""name"""]: job["""html_url"""] for job in result["""jobs"""]}	)

              return jobs
       except Exception as e:
              print("""Unknown error, could not fetch links."""  ,			A__	)

       return {}




def 					lowerCamelCase__       (						A__       :					str	):





       '''simple docstring'''



       __lowerCamelCase   =						{}

       if os.path.exists(A__	):
              __lowerCamelCase   =						os.listdir(A__	)
              for file in files:
                     try:
                            with open(os.path.join(A__  ,			A__	)  ,			encoding="""utf-8"""	) as f:
                                   __lowerCamelCase   =						f.read()
                     except UnicodeDecodeError as e:
                            raise ValueError(f'Could not open {os.path.join(A__  ,			A__	)}.'	) from e

       return _artifact




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       class     lowerCamelCase__:
             def __init__(				self: Optional[Any]    ,       UpperCamelCase_: str   ):
                    __lowerCamelCase   =						name
                    __lowerCamelCase   =						[]
             def __str__(				self: List[str]   ):
                    return self.name




             def 			lowerCAmelCase__						(				self: List[str]    ,       UpperCamelCase_: str   ):
                    self.paths.append({"""name""": self.name, """path""": path}   )



       __lowerCamelCase   =						{}

       __lowerCamelCase   =						filter(os.path.isdir  ,			os.listdir()	)
       for directory in directories:
              __lowerCamelCase   =						directory
              if artifact_name not in _available_artifacts:
                     __lowerCamelCase   =						Artifact(A__	)

                     _available_artifacts[artifact_name].add_path(A__	)

       return _available_artifacts


if __name__ == "__main__":
       UpperCAmelCase_									=	get_job_links()
       UpperCAmelCase_									=	retrieve_available_artifacts()

       UpperCAmelCase_									=	collections.OrderedDict(
           [
               ('*.py', 'API Examples'),
               ('*.md', 'MD Examples'),
           ]
       )

       # This dict will contain all the information relative to each doc test category:
       # - failed: list of failed tests
       # - failures: dict in the format 'test': 'error_message'
       UpperCAmelCase_									=	{
           v: {
               'failed': [],
               'failures': {},
           }
           for v in docs.values()
       }

       # Link to the GitHub Action job
       UpperCAmelCase_									=	github_actions_job_links.get('run_doctests')

       UpperCAmelCase_									=	available_artifacts['doc_tests_gpu_test_reports'].paths[0]
       UpperCAmelCase_									=	retrieve_artifact(artifact_path['name'])
       if "stats" in artifact:
              UpperCAmelCase_				,			UpperCAmelCase_				,			UpperCAmelCase_									=	handle_test_results(artifact['stats'])
              UpperCAmelCase_									=	failed
              UpperCAmelCase_									=	success
              UpperCAmelCase_									=	time_spent[1:-1] + ', '

              UpperCAmelCase_									=	extract_first_line_failure(artifact['failures_short'])
              for line in artifact["summary_short"].split('\n'):
                     if re.search('FAILED', line):
                            UpperCAmelCase_									=	line.replace('FAILED ', '')
                            UpperCAmelCase_									=	line.split()[0].replace('\n', '')

                            if "::" in line:
                                   UpperCAmelCase_				,			UpperCAmelCase_									=	line.split('::')
                            else:
                                   UpperCAmelCase_				,			UpperCAmelCase_									=	line, line

                            for file_regex in docs.keys():
                                   if fnmatch(file_path, file_regex):
                                          UpperCAmelCase_									=	docs[file_regex]
                                          doc_test_results[category]["failed"].append(test)

                                          UpperCAmelCase_									=	all_failures[test] if test in all_failures else 'N/A'
                                          UpperCAmelCase_									=	failure
                                          break

       UpperCAmelCase_									=	Message('🤗 Results of the doc tests.', doc_test_results)
       message.post()
       message.post_reply()




import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 				UpperCAmelCase_		(			__lowercase				,       unittest.TestCase   ):
							"""simple docstring"""







							UpperCAmelCase__       :						int	    =    GPTaTokenizer
							UpperCAmelCase__       :						str	    =    GPTaTokenizerFast
							UpperCAmelCase__       :						Tuple	    =    True
							UpperCAmelCase__       :						List[Any]	    =    {"add_prefix_space": True}
							UpperCAmelCase__       :						int	    =    False


							def 				__lowercase				(			self       )    ->    int:
												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												_a	:    str         =		[
												    '''l''',
												    '''o''',
												    '''w''',
												    '''e''',
												    '''r''',
												    '''s''',
												    '''t''',
												    '''i''',
												    '''d''',
												    '''n''',
												    '''\u0120''',
												    '''\u0120l''',
												    '''\u0120n''',
												    '''\u0120lo''',
												    '''\u0120low''',
												    '''er''',
												    '''\u0120lowest''',
												    '''\u0120newer''',
												    '''\u0120wider''',
												    '''<unk>''',
												    '''<|endoftext|>''',
												]
												_a	:    List[Any]         =		dict(zip(_a       ,							range(len(_a       )       )       )       )
												_a	:    Tuple         =		['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
												_a	:    List[str]         =		{'''unk_token''': '''<unk>'''}

												_a	:    List[str]         =		os.path.join(self.tmpdirname       ,							VOCAB_FILES_NAMES['''vocab_file''']       )
												_a	:    Tuple         =		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 				__lowercase				(			self       ,							**_a       )    ->    List[str]:
												kwargs.update(self.special_tokens_map       )
												return GPTaTokenizer.from_pretrained(self.tmpdirname       ,							**_a       )


							def 				__lowercase				(			self       ,							**_a       )    ->    List[Any]:
												kwargs.update(self.special_tokens_map       )
												return GPTaTokenizerFast.from_pretrained(self.tmpdirname       ,							**_a       )


							def 				__lowercase				(			self       ,							_a       )    ->    Optional[Any]:
												_a	:    Tuple         =		'''lower newer'''
												_a	:    Tuple         =		'''lower newer'''
												return input_text, output_text


							def 				__lowercase				(			self       )    ->    Any:
												_a	:    Any         =		GPTaTokenizer(self.vocab_file       ,							self.merges_file       ,							**self.special_tokens_map       )
												_a	:    int         =		'''lower newer'''
												_a	:    int         =		['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
												_a	:    List[str]         =		tokenizer.tokenize(_a       ,							add_prefix_space=_a       )
												self.assertListEqual(_a       ,							_a       )

												_a	:    Optional[int]         =		tokens + [tokenizer.unk_token]
												_a	:    List[Any]         =		[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_a       )       ,							_a       )


							def 				__lowercase				(			self       )    ->    Optional[int]:
												if not self.test_rust_tokenizer:
																	return

												_a	:    int         =		self.get_tokenizer()
												_a	:    Tuple         =		self.get_rust_tokenizer(add_prefix_space=_a       )

												_a	:    Tuple         =		'''lower newer'''

												# Testing tokenization
												_a	:    List[str]         =		tokenizer.tokenize(_a       ,							add_prefix_space=_a       )
												_a	:    Optional[Any]         =		rust_tokenizer.tokenize(_a       )
												self.assertListEqual(_a       ,							_a       )

												# Testing conversion to ids without special tokens
												_a	:    List[Any]         =		tokenizer.encode(_a       ,							add_special_tokens=_a       ,							add_prefix_space=_a       )
												_a	:    List[Any]         =		rust_tokenizer.encode(_a       ,							add_special_tokens=_a       )
												self.assertListEqual(_a       ,							_a       )

												# Testing conversion to ids with special tokens
												_a	:    List[str]         =		self.get_rust_tokenizer(add_prefix_space=_a       )
												_a	:    List[str]         =		tokenizer.encode(_a       ,							add_prefix_space=_a       )
												_a	:    Tuple         =		rust_tokenizer.encode(_a       )
												self.assertListEqual(_a       ,							_a       )

												# Testing the unknown token
												_a	:    Optional[Any]         =		tokens + [rust_tokenizer.unk_token]
												_a	:    str         =		[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
												self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_a       )       ,							_a       )


							def 				__lowercase				(			self       ,							*_a       ,							**_a       )    ->    int:
												# It's very difficult to mix/test pretokenization with byte-level
												# And get both GPT2 and Roberta to work at the same time (mostly an issue of adding a space before the string)
												pass


							def 				__lowercase				(			self       ,							_a=1_5       )    ->    str:
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
																						_a	:    Optional[int]         =		self.rust_tokenizer_class.from_pretrained(_a       ,							**_a       )

																						# Simple input
																						_a	:    List[str]         =		'''This is a simple input'''
																						_a	:    Optional[Any]         =		['''This is a simple input 1''', '''This is a simple input 2''']
																						_a	:    Tuple         =		('''This is a simple input''', '''This is a pair''')
																						_a	:    Optional[Any]         =		[
																						    ('''This is a simple input 1''', '''This is a simple input 2'''),
																						    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
																						]

																						# Simple input tests
																						self.assertRaises(_a       ,							tokenizer_r.encode       ,							_a       ,							max_length=_a       ,							padding='''max_length'''       )

																						# Simple input
																						self.assertRaises(_a       ,							tokenizer_r.encode_plus       ,							_a       ,							max_length=_a       ,							padding='''max_length'''       )

																						# Simple input
																						self.assertRaises(
																						    _a       ,							tokenizer_r.batch_encode_plus       ,							_a       ,							max_length=_a       ,							padding='''max_length'''       ,							)

																						# Pair input
																						self.assertRaises(_a       ,							tokenizer_r.encode       ,							_a       ,							max_length=_a       ,							padding='''max_length'''       )

																						# Pair input
																						self.assertRaises(_a       ,							tokenizer_r.encode_plus       ,							_a       ,							max_length=_a       ,							padding='''max_length'''       )

																						# Pair input
																						self.assertRaises(
																						    _a       ,							tokenizer_r.batch_encode_plus       ,							_a       ,							max_length=_a       ,							padding='''max_length'''       ,							)


							def 				__lowercase				(			self       )    ->    List[Any]:
												_a	:    int         =		GPTaTokenizer.from_pretrained(self.tmpdirname       ,							pad_token='''<pad>'''       )

												# Simple input
												_a	:    int         =		'''This is a simple input'''
												_a	:    int         =		['''This is a simple input looooooooong''', '''This is a simple input''']
												_a	:    Any         =		('''This is a simple input''', '''This is a pair''')
												_a	:    Dict         =		[
												    ('''This is a simple input loooooong''', '''This is a simple input'''),
												    ('''This is a simple pair loooooong''', '''This is a simple pair'''),
												]

												_a	:    Optional[int]         =		tokenizer.pad_token_id

												_a	:    List[Any]         =		tokenizer(_a       ,							padding='''max_length'''       ,							max_length=3_0       ,							return_tensors='''np'''       )
												_a	:    Optional[int]         =		tokenizer(_a       ,							padding=_a       ,							truncate=_a       ,							return_tensors='''np'''       )
												_a	:    int         =		tokenizer(*_a       ,							padding='''max_length'''       ,							max_length=6_0       ,							return_tensors='''np'''       )
												_a	:    Union[str, Any]         =		tokenizer(_a       ,							padding=_a       ,							truncate=_a       ,							return_tensors='''np'''       )

												# s
												# test single string max_length padding
												self.assertEqual(out_s['''input_ids'''].shape[-1]       ,							3_0       )
												self.assertTrue(pad_token_id in out_s['''input_ids''']       )
												self.assertTrue(0 in out_s['''attention_mask''']       )

												# s2
												# test automatic padding
												self.assertEqual(out_sa['''input_ids'''].shape[-1]       ,							3_3       )
												# long slice doesn't have padding
												self.assertFalse(pad_token_id in out_sa['''input_ids'''][0]       )
												self.assertFalse(0 in out_sa['''attention_mask'''][0]       )
												# short slice does have padding
												self.assertTrue(pad_token_id in out_sa['''input_ids'''][1]       )
												self.assertTrue(0 in out_sa['''attention_mask'''][1]       )

												# p
												# test single pair max_length padding
												self.assertEqual(out_p['''input_ids'''].shape[-1]       ,							6_0       )
												self.assertTrue(pad_token_id in out_p['''input_ids''']       )
												self.assertTrue(0 in out_p['''attention_mask''']       )

												# p2
												# test automatic padding pair
												self.assertEqual(out_pa['''input_ids'''].shape[-1]       ,							5_2       )
												# long slice pair doesn't have padding
												self.assertFalse(pad_token_id in out_pa['''input_ids'''][0]       )
												self.assertFalse(0 in out_pa['''attention_mask'''][0]       )
												# short slice pair does have padding
												self.assertTrue(pad_token_id in out_pa['''input_ids'''][1]       )
												self.assertTrue(0 in out_pa['''attention_mask'''][1]       )


							def 				__lowercase				(			self       )    ->    Any:
												_a	:    Union[str, Any]         =		'''$$$'''
												_a	:    List[Any]         =		GPTaTokenizer.from_pretrained(self.tmpdirname       ,							bos_token=_a       ,							add_bos_token=_a       )

												_a	:    Any         =		'''This is a simple input'''
												_a	:    str         =		['''This is a simple input 1''', '''This is a simple input 2''']

												_a	:    Tuple         =		tokenizer.bos_token_id

												_a	:    Optional[Any]         =		tokenizer(_a       )
												_a	:    str         =		tokenizer(_a       )

												self.assertEqual(out_s.input_ids[0]       ,							_a       )
												self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids       )       )

												_a	:    str         =		tokenizer.decode(out_s.input_ids       )
												_a	:    Optional[Any]         =		tokenizer.batch_decode(out_sa.input_ids       )

												self.assertEqual(decode_s.split()[0]       ,							_a       )
												self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa       )       )


							def 				__lowercase				(			self       )    ->    str:
												pass




							def 				__lowercase				(			self       )    ->    Dict:
												# TODO: change to self.get_tokenizers() when the fast version is implemented
												_a	:    Optional[int]         =		[self.get_tokenizer(do_lower_case=_a       ,							add_bos_token=_a       )]
												for tokenizer in tokenizers:
																	with self.subTest(F"""{tokenizer.__class__.__name__}"""       ):
																						_a	:    Tuple         =		'''Encode this.'''
																						_a	:    Optional[Any]         =		'''This one too please.'''
																						_a	:    List[Any]         =		tokenizer.encode(_a       ,							add_special_tokens=_a       )
																						encoded_sequence += tokenizer.encode(_a       ,							add_special_tokens=_a       )
																						_a	:    List[str]         =		tokenizer.encode_plus(
																						    _a       ,							_a       ,							add_special_tokens=_a       ,							return_special_tokens_mask=_a       ,							)
																						_a	:    int         =		encoded_sequence_dict['''input_ids''']
																						_a	:    int         =		encoded_sequence_dict['''special_tokens_mask''']
																						self.assertEqual(len(_a       )       ,							len(_a       )       )

																						_a	:    List[Any]         =		[
																						    (x if not special_tokens_mask[i] else None) for i, x in enumerate(_a       )
																						]
																						_a	:    str         =		[x for x in filtered_sequence if x is not None]
																						self.assertEqual(_a       ,							_a       )



@require_tokenizers
class 				UpperCAmelCase_		(			unittest.TestCase   ):
							"""simple docstring"""







							def 				__lowercase				(			self       )    ->    List[Any]:
												# More context:
												# https://huggingface.co/wjmcat/opt-350m-paddle/discussions/1
												# https://huggingface.slack.com/archives/C01N44FJDHT/p1653511495183519
												# https://github.com/huggingface/transformers/pull/17088#discussion_r871246439

												_a	:    Any         =		AutoTokenizer.from_pretrained('''facebook/opt-350m'''       ,							from_slow=_a       )
												_a	:    int         =		'''A photo of a cat'''

												_a	:    List[Any]         =		tokenizer.encode(
												    _a       ,							)
												self.assertEqual(_a       ,							[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]       )
												tokenizer.save_pretrained('''test_opt'''       )

												_a	:    Union[str, Any]         =		AutoTokenizer.from_pretrained('''./test_opt'''       )
												_a	:    Any         =		tokenizer.encode(
												    _a       ,							)
												self.assertEqual(_a       ,							[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]       )


							def 				__lowercase				(			self       )    ->    int:
												_a	:    Union[str, Any]         =		AutoTokenizer.from_pretrained('''facebook/opt-350m'''       ,							use_slow=_a       )
												_a	:    Any         =		'''A photo of a cat'''

												_a	:    Optional[int]         =		tokenizer.encode(
												    _a       ,							)
												# Same as above
												self.assertEqual(_a       ,							[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]       )




							@unittest.skip('''This test is failing because of a bug in the fast tokenizer'''       )
							def 				__lowercase				(			self       )    ->    Any:
												_a	:    Union[str, Any]         =		AutoTokenizer.from_pretrained('''facebook/opt-350m'''       ,							from_slow=_a       )

												_a	:    Optional[Any]         =		'''bos'''
												_a	:    Optional[Any]         =		tokenizer.get_vocab()['''bos''']

												_a	:    str         =		'''A photo of a cat'''
												_a	:    int         =		tokenizer.encode(
												    _a       ,							)
												# We changed the bos token
												self.assertEqual(_a       ,							[3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]       )
												tokenizer.save_pretrained('''./tok'''       )
												_a	:    Dict         =		AutoTokenizer.from_pretrained('''./tok'''       )
												self.assertTrue(tokenizer.is_fast       )
												_a	:    Union[str, Any]         =		tokenizer.encode(
												    _a       ,							)
												self.assertEqual(_a       ,							[3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]       )



