from abc import ABC, abstractmethod
from typing import List, Optional



class  SCREAMING_SNAKE_CASE_ (					__SCREAMING_SNAKE_CASE			):
  '''simple docstring'''


  def __init__(				self    :					Dict     )    ->				Dict:
         # test for the above condition
         self.test()







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				Optional[Any]:
         A						:     Tuple         =0
         A						:     int         =False
         while not completed:
                if counter == 1:
                       self.reset()
                A						:     List[Any]         =self.advance()
                if not self.does_advance(_a     ):
                       raise Exception(
                           'Custom Constraint is not defined correctly. self.does_advance(self.advance()) must be true.'     )

                A  ,  A  ,  A						:     Optional[int]         =self.update(_a     )
                counter += 1

                if counter > 1_00_00:
                       raise Exception('update() does not fulfill the constraint.'     )

         if self.remaining() != 0:
                raise Exception('Custom Constraint is not defined correctly.'     )







  @abstractmethod
  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Any:
         raise NotImplementedError(
             f'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'     )







  @abstractmethod
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Any      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]     )    ->				List[Any]:
         raise NotImplementedError(
             f'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'     )







  @abstractmethod
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Any     )    ->				Optional[int]:
         raise NotImplementedError(
             f'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'     )







  @abstractmethod
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				Dict:
         raise NotImplementedError(
             f'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'     )







  @abstractmethod
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Any     )    ->				List[str]:
         raise NotImplementedError(
             f'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'     )







  @abstractmethod
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					List[str]=False     )    ->				List[str]:
         raise NotImplementedError(
             f'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'     )







class  SCREAMING_SNAKE_CASE_ (					__SCREAMING_SNAKE_CASE			):
  '''simple docstring'''


  def __init__(				self    :					Any      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]     )    ->				Optional[Any]:
         super(_a      ,	self     ).__init__()

         if not isinstance(_a      ,	_a     ) or len(_a     ) == 0:
                raise ValueError(f'`token_ids` has to be a non-empty list, but is {token_ids}.'     )
         if any((not isinstance(_a      ,	_a     ) or token_id < 0) for token_id in token_ids     ):
                raise ValueError(f'Each list in `token_ids` has to be a list of positive integers, but is {token_ids}.'     )

         A						:     Union[str, Any]         =token_ids

         A						:     int         =len(self.token_ids     )
         A						:     Union[str, Any]         =-1  # the index of the currently fulfilled step
         A						:     Union[str, Any]         =False







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				Optional[int]:
         if self.completed:
                return None
         return self.token_ids[self.fulfilled_idx + 1]







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]     )    ->				Any:
         if not isinstance(_a      ,	_a     ):
                raise ValueError(f'`token_id` has to be an `int`, but is {token_id} of type {type(_a     )}'     )

         if self.completed:
                return False

         return token_id == self.token_ids[self.fulfilled_idx + 1]







  def 		SCREAMING_SNAKE_CASE_		(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					List[Any]     )    ->				Any:
         if not isinstance(_a      ,	_a     ):
                raise ValueError(f'`token_id` has to be an `int`, but is {token_id} of type {type(_a     )}'     )

         A						:     Union[str, Any]         =False
         A						:     str         =False
         A						:     List[Any]         =False

         if self.does_advance(_a     ):
                self.fulfilled_idx += 1
                A						:     int         =True
                if self.fulfilled_idx == (self.seqlen - 1):
                       A						:     str         =True
                A						:     Optional[int]         =completed
         else:
                # failed to make progress.
                A						:     Dict         =True
                self.reset()
         return stepped, completed, reset







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				List[str]:
         A						:     Optional[Any]         =False
         A						:     str         =0







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				str:
         return self.seqlen - (self.fulfilled_idx + 1)







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					str=False     )    ->				Optional[int]:
         A						:     Tuple         =PhrasalConstraint(self.token_ids     )

         if stateful:
                A						:     Optional[Any]         =self.seqlen
                A						:     str         =self.fulfilled_idx
                A						:     List[Any]         =self.completed

         return new_constraint







class  SCREAMING_SNAKE_CASE_ :
  '''simple docstring'''


  def __init__(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=True     )    ->				int:
         A						:     List[Any]         =max([len(_a     ) for one in nested_token_ids]     )

         A						:     Any         ={}
         for token_ids in nested_token_ids:
                A						:     int         =root
                for tidx, token_id in enumerate(_a     ):
                       if token_id not in level:
                              A						:     int         ={}

                       A						:     Dict         =level[token_id]

         if no_subsets and self.has_subsets(_a      ,	_a     ):
                raise ValueError(
                    'Each list in `nested_token_ids` can\'t be a complete subset of another list, but is'
                    f' {nested_token_ids}.'     )

         A						:     List[str]         =root







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]     )    ->				Dict:
         A						:     Tuple         =self.trie

         for current_token in current_seq:
                A						:     str         =start[current_token]

         A						:     Union[str, Any]         =list(start.keys()     )

         return next_tokens







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]     )    ->				Dict:
         A						:     Optional[int]         =self.next_tokens(_a     )

         return len(_a     ) == 0







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Any      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]     )    ->				List[str]:
         A						:     Tuple         =list(root.values()     )
         if len(_a     ) == 0:
                return 1
         else:
                return sum([self.count_leaves(_a     ) for nn in next_nodes]     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]     )    ->				Union[str, Any]:
         A						:     Optional[int]         =self.count_leaves(_a     )
         return len(_a     ) != leaf_count







class  SCREAMING_SNAKE_CASE_ (					__SCREAMING_SNAKE_CASE			):
  '''simple docstring'''


  def __init__(				self    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					Dict     )    ->				List[Any]:
         super(_a      ,	self     ).__init__()

         if not isinstance(_a      ,	_a     ) or len(_a     ) == 0:
                raise ValueError(f'`nested_token_ids` has to be a non-empty list, but is {nested_token_ids}.'     )
         if any(not isinstance(_a      ,	_a     ) for token_ids in nested_token_ids     ):
                raise ValueError(f'`nested_token_ids` has to be a list of lists, but is {nested_token_ids}.'     )
         if any(
             any((not isinstance(_a      ,	_a     ) or token_id < 0) for token_id in token_ids     )
             for token_ids in nested_token_ids     ):
                raise ValueError(
                    f'Each list in `nested_token_ids` has to be a list of positive integers, but is {nested_token_ids}.'     )

         A						:     str         =DisjunctiveTrie(_a     )
         A						:     str         =nested_token_ids

         A						:     Tuple         =self.trie.max_height
         A						:     List[str]         =[]
         A						:     int         =False







  def 		SCREAMING_SNAKE_CASE_		(				self    :					int     )    ->				str:
         A						:     str         =self.trie.next_tokens(self.current_seq     )

         if len(_a     ) == 0:
                return None
         else:
                return token_list







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]      ,	SCREAMING_SNAKE_CASE__    :					List[Any]     )    ->				List[str]:
         if not isinstance(_a      ,	_a     ):
                raise ValueError(f'`token_id` is supposed to be type `int`, but is {token_id} of type {type(_a     )}'     )

         A						:     Union[str, Any]         =self.trie.next_tokens(self.current_seq     )

         return token_id in next_tokens







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					List[Any]     )    ->				List[Any]:
         if not isinstance(_a      ,	_a     ):
                raise ValueError(f'`token_id` is supposed to be type `int`, but is {token_id} of type {type(_a     )}'     )

         A						:     List[str]         =False
         A						:     Dict         =False
         A						:     List[Any]         =False

         if self.does_advance(_a     ):
                self.current_seq.append(_a     )
                A						:     Tuple         =True
         else:
                A						:     List[Any]         =True
                self.reset()

         A						:     Optional[Any]         =self.trie.reached_leaf(self.current_seq     )
         A						:     Any         =completed

         return stepped, completed, reset







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				List[Any]:
         A						:     Union[str, Any]         =False
         A						:     Optional[int]         =[]







  def 		SCREAMING_SNAKE_CASE_		(				self    :					str     )    ->				Optional[Any]:
         if self.completed:
                # since this can be completed without reaching max height
                return 0
         else:
                return self.seqlen - len(self.current_seq     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]      ,	SCREAMING_SNAKE_CASE__    :					Tuple=False     )    ->				Union[str, Any]:
         A						:     List[str]         =DisjunctiveConstraint(self.token_ids     )

         if stateful:
                A						:     int         =self.seqlen
                A						:     str         =self.current_seq
                A						:     Union[str, Any]         =self.completed

         return new_constraint







class  SCREAMING_SNAKE_CASE_ :
  '''simple docstring'''


  def __init__(				self    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					int     )    ->				Tuple:
         A						:     Optional[int]         =constraints

         # max # of steps required to fulfill a given constraint
         A						:     Tuple         =max([c.seqlen for c in constraints]     )
         A						:     Any         =len(_a     )
         A						:     Dict         =False

         self.init_state()







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				str:
         A						:     List[Any]         =[]
         A						:     Union[str, Any]         =None
         A						:     Union[str, Any]         =[constraint.copy(stateful=_a     ) for constraint in self.constraints]







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				List[str]:
         A						:     str         =0
         if self.inprogress_constraint:
                # extra points for having a constraint mid-fulfilled
                add += self.max_seqlen - self.inprogress_constraint.remaining()

         return (len(self.complete_constraints     ) * self.max_seqlen) + add







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[Any]     )    ->				Optional[int]:
         A						:     Optional[int]         =[]
         if self.inprogress_constraint is None:
                for constraint in self.pending_constraints:  # "pending" == "unfulfilled yet"
                       A						:     Optional[int]         =constraint.advance()
                       if isinstance(_a      ,	_a     ):
                              token_list.append(_a     )
                       elif isinstance(_a      ,	_a     ):
                              token_list.extend(_a     )
         else:
                A						:     Dict         =self.inprogress_constraint.advance()
                if isinstance(_a      ,	_a     ):
                       token_list.append(_a     )
                elif isinstance(_a      ,	_a     ):
                       token_list.extend(_a     )

         if len(_a     ) == 0:
                return None
         else:
                return token_list







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					int     )    ->				List[str]:
         self.init_state()

         if token_ids is not None:
                for token in token_ids:
                       # completes or steps **one** constraint
                       A  ,  A						:     Optional[int]         =self.add(_a     )

                       # the entire list of constraints are fulfilled
                       if self.completed:
                              break







  def 		SCREAMING_SNAKE_CASE_		(				self    :					str      ,	SCREAMING_SNAKE_CASE__    :					Dict     )    ->				List[str]:
         if not isinstance(_a      ,	_a     ):
                raise ValueError(f'`token_id` should be an `int`, but is `{token_id}`.'     )

         A  ,  A						:     Optional[int]         =False, False

         if self.completed:
                A						:     str         =True
                A						:     List[str]         =False
                return complete, stepped

         if self.inprogress_constraint is not None:
                # In the middle of fulfilling a constraint. If the `token_id` *does* makes an incremental progress to current
                # job, simply update the state

                A  ,  A  ,  A						:     List[Any]         =self.inprogress_constraint.update(_a     )
                if reset:
                       # 1. If the next token breaks the progress, then we must restart.
                       #     e.g. constraint = "I love pies" and sequence so far is "I love" but `token_id` == "books".

                       #     But that doesn't mean we self.init_state(), since we only reset the state for this particular
                       #     constraint, not the full list of constraints.

                       self.pending_constraints.append(self.inprogress_constraint.copy(stateful=_a     )     )
                       A						:     Any         =None

                if complete:
                       # 2. If the next token completes the constraint, move it to completed list, set
                       #     inprogress to None. If there are no pending constraints either, then this full list of constraints
                       #     is complete.

                       self.complete_constraints.append(self.inprogress_constraint     )
                       A						:     str         =None

                       if len(self.pending_constraints     ) == 0:
                              # we're done!
                              A						:     List[Any]         =True

         else:
                # Not in the middle of fulfilling a constraint. So does this `token_id` helps us step towards any of our list
                # of constraints?

                for cidx, pending_constraint in enumerate(self.pending_constraints     ):
                       if pending_constraint.does_advance(_a     ):
                              A  ,  A  ,  A						:     str         =pending_constraint.update(_a     )

                              if not stepped:
                                     raise Exception(
                                         '`constraint.update(token_id)` is not yielding incremental progress, '
                                         'even though `constraint.does_advance(token_id)` is true.'     )

                              if complete:
                                     self.complete_constraints.append(_a     )
                                     A						:     Optional[int]         =None

                              if not complete and stepped:
                                     A						:     Any         =pending_constraint

                              if complete or stepped:
                                     # If we made any progress at all, then it's at least not a "pending constraint".

                                     A						:     Optional[int]         =(
                                         self.pending_constraints[:cidx] + self.pending_constraints[cidx + 1 :]
                                     )

                                     if len(self.pending_constraints     ) == 0 and self.inprogress_constraint is None:
                                            # If there's no longer any pending after this and no inprogress either, then we must be
                                            # complete.

                                            A						:     Optional[int]         =True

                                     break  # prevent accidentally stepping through multiple constraints with just one token.

         return complete, stepped







  def 		SCREAMING_SNAKE_CASE_		(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					Dict=True     )    ->				Optional[Any]:
         A						:     List[Any]         =ConstraintListState(self.constraints     )  # we actually never though self.constraints objects
         # throughout this process. So it's at initialization state.

         if stateful:
                A						:     Tuple         =[
                    constraint.copy(stateful=_a     ) for constraint in self.complete_constraints
                ]
                if self.inprogress_constraint is not None:
                       A						:     str         =self.inprogress_constraint.copy(stateful=_a     )
                A						:     str         =[constraint.copy() for constraint in self.pending_constraints]

         return new_state







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


_lowercase							:      Optional[Any]      							=WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])



def A__  (			lowercase:     Optional[int]					)				->		Optional[int]:
       A						:     str         =test_results.split(' '					)

       A						:     List[str]         =0
       A						:     Tuple         =0

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

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

       return failed, success, time_spent



def A__  (			lowercase:     List[Any]					)				->		str:
       A						:     Union[str, Any]         ={}
       A						:     Optional[Any]         =None
       A						:     Union[str, Any]         =False
       for line in failures_short_lines.split('\n'					):
              if re.search(r'_ \[doctest\]',		lowercase					):
                     A						:     List[Any]         =True
                     A						:     Any         =line.split(' '					)[2]
              elif in_error and not line.split(' '					)[0].isdigit():
                     A						:     Dict         =line
                     A						:     List[str]         =False

       return failures



class  SCREAMING_SNAKE_CASE_ :
  '''simple docstring'''


  def __init__(				self    :					str      ,	SCREAMING_SNAKE_CASE__    :					str      ,	SCREAMING_SNAKE_CASE__    :					Dict     )    ->				List[str]:
         A						:     Tuple         =title

         A						:     Dict         =doc_test_results['time_spent'].split(','     )[0]
         A						:     Union[str, Any]         =doc_test_results['success']
         A						:     Any         =doc_test_results['failures']
         A						:     Optional[Any]         =self.n_success + self.n_failures

         # Failures and success of the modeling tests
         A						:     Union[str, Any]         =doc_test_results







  @property
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple     )    ->				str:
         A						:     Any         =[self._time_spent]
         A						:     List[str]         =0

         for time in time_spent:
                A						:     List[Any]         =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(SCREAMING_SNAKE_CASE__     ) == 1:
                       A						:     List[str]         =[0, 0, time_parts[0]]

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

         A  ,  A  ,  A						:     str         =total_secs // 36_00, (total_secs % 36_00) // 60, total_secs % 60
         return f'{int(SCREAMING_SNAKE_CASE__     )}h{int(SCREAMING_SNAKE_CASE__     )}m{int(SCREAMING_SNAKE_CASE__     )}s'







  @property
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple     )    ->				Dict:
         return {"type": "header", "text": {"type": "plain_text", "text": self.title}}







  @property
  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Dict:
         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 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				Dict:
         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 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				Dict:
         A						:     Tuple         =40
         A						:     Optional[Any]         ={k: v['failed'] for k, v in doc_test_results.items() if isinstance(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__     )}

         A						:     Any         =''
         for category, failures in category_failures.items():
                if len(SCREAMING_SNAKE_CASE__     ) == 0:
                       continue

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

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

         return {
             "type": "section",
             "text": {
                 "type": "mrkdwn",
                 "text": f'The following examples had failures:\n\n\n{report}\n',
             },
         }







  @property
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[Any]     )    ->				str:
         A						:     Optional[int]         =[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(SCREAMING_SNAKE_CASE__     )







  @staticmethod
  def 		SCREAMING_SNAKE_CASE_		(				)    ->				Optional[Any]:
         A						:     Tuple         =[
             {
                 '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(SCREAMING_SNAKE_CASE__     )}     )     )

         client.chat_postMessage(
             channel=os.environ['CI_SLACK_CHANNEL_ID_DAILY']      ,	text='There was an issue running the tests.'      ,	blocks=SCREAMING_SNAKE_CASE__      ,	)







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict     )    ->				Optional[int]:
         print('Sending the following payload'     )
         print(json.dumps({'blocks': json.loads(self.payload     )}     )     )

         A						:     Any         =f'{self.n_failures} failures out of {self.n_tests} tests,' if self.n_failures else 'All tests passed.'

         A						:     Dict         =client.chat_postMessage(
             channel=os.environ['CI_SLACK_CHANNEL_ID_DAILY']      ,	blocks=self.payload      ,	text=SCREAMING_SNAKE_CASE__      ,	)







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					List[str]      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					int      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]     )    ->				Optional[int]:
         A						:     List[str]         =''
         for key, value in failures.items():
                A						:     Any         =value[:2_00] + ' [Truncated]' if len(SCREAMING_SNAKE_CASE__     ) > 2_50 else value
                failures_text += f'*{key}*\n_{value}_\n\n'

         A						:     Union[str, Any]         =job_name
         A						:     Any         ={'type': 'section', 'text': {'type': 'mrkdwn', 'text': text}}

         if job_link is not None:
                A						:     int         ={
                    '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 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple     )    ->				List[Any]:
         if self.thread_ts is None:
                raise ValueError('Can only post reply if a post has been made.'     )

         A						:     Union[str, Any]         =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'     )

         A						:     Union[str, Any]         =sorted(self.doc_test_results.items()      ,	key=lambda SCREAMING_SNAKE_CASE__     : t[0]     )
         for job, job_result in sorted_dict:
                if len(job_result['failures']     ):
                       A						:     Any         =f'*Num failures* :{len(job_result["failed"]     )} \n'
                       A						:     List[Any]         =job_result['failures']
                       A						:     Any         =self.get_reply_blocks(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	text=SCREAMING_SNAKE_CASE__     )

                       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=SCREAMING_SNAKE_CASE__      ,	thread_ts=self.thread_ts['ts']      ,	)

                       time.sleep(1     )







def A__  (			)				->		Union[str, Any]:
       A						:     Any         =os.environ['GITHUB_RUN_ID']
       A						:     List[Any]         =F'https://api.github.com/repos/huggingface/transformers/actions/runs/{run_id}/jobs?per_page=100'
       A						:     Union[str, Any]         =requests.get(lowercase					).json()
       A						:     List[Any]         ={}

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

              for i in range(lowercase					):
                     A						:     List[str]         =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.',		lowercase					)

       return {}



def A__  (			lowercase:     str					)				->		Optional[Any]:
       A						:     Any         ={}

       if os.path.exists(lowercase					):
              A						:     List[Any]         =os.listdir(lowercase					)
              for file in files:
                     try:
                            with open(os.path.join(lowercase,		lowercase					),		encoding='utf-8'					) as f:
                                   A						:     Optional[int]         =f.read()
                     except UnicodeDecodeError as e:
                            raise ValueError(F'Could not open {os.path.join(lowercase,		lowercase					)}.'					) from e

       return _artifact



def A__  (			)				->		int:



       class  SCREAMING_SNAKE_CASE_ :
         '''simple docstring'''


         def __init__(				self    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					str     )    ->				List[str]:
                A						:     Dict         =name
                A						:     Dict         =[]







         def __str__(				self    :					Optional[Any]     )    ->				List[str]:
                return self.name







         def 		SCREAMING_SNAKE_CASE_		(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					str     )    ->				List[Any]:
                self.paths.append({'name': self.name, 'path': path}     )







       A						:     Dict[str, Artifact]         ={}

       A						:     str         =filter(os.path.isdir,		os.listdir()					)
       for directory in directories:
              A						:     Tuple         =directory
              if artifact_name not in _available_artifacts:
                     A						:     int         =Artifact(lowercase					)

                     _available_artifacts[artifact_name].add_path(lowercase					)

       return _available_artifacts


if __name__ == "__main__":
    _lowercase							:      Optional[int]      							=get_job_links()
    _lowercase							:      str      							=retrieve_available_artifacts()

    _lowercase							:      List[Any]      							=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'
    _lowercase							:      Optional[Any]      							={
        v: {
            '''failed''': [],
            '''failures''': {},
        }
        for v in docs.values()
    }

    # Link to the GitHub Action job
    _lowercase							:      List[Any]      							=github_actions_job_links.get('''run_doctests''')

    _lowercase							:      int      							=available_artifacts['''doc_tests_gpu_test_reports'''].paths[0]
    _lowercase							:      Dict      							=retrieve_artifact(artifact_path['''name'''])
    if "stats" in artifact:
        _lowercase							,	_lowercase							,	_lowercase							:      List[Any]      							=handle_test_results(artifact['''stats'''])
        _lowercase							:      Any      							=failed
        _lowercase							:      Union[str, Any]      							=success
        _lowercase							:      str      							=time_spent[1:-1] + ''', '''

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

                if "::" in line:
                    _lowercase							,	_lowercase							:      str      							=line.split('''::''')
                else:
                    _lowercase							,	_lowercase							:      Union[str, Any]      							=line, line

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

                        _lowercase							:      Any      							=all_failures[test] if test in all_failures else '''N/A'''
                        _lowercase							:      Tuple      							=failure
                        break

    _lowercase							:      Optional[int]      							=Message('''🤗 Results of the doc tests.''', doc_test_results)
    message.post()
    message.post_reply()






