

import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union

import numpy as np
import regex

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_flax_available, is_tf_available, is_torch_available, logging
from ...utils.generic import _is_jax, _is_numpy


__A			:					List[Any]						=			logging.get_logger(__name__)

__A			:					int						=			{
    'artists_file': 'artists.json',
    'lyrics_file': 'lyrics.json',
    'genres_file': 'genres.json',
}

__A			:					List[str]						=			{
    'artists_file': {
        'jukebox': 'https://huggingface.co/ArthurZ/jukebox/blob/main/artists.json',
    },
    'genres_file': {
        'jukebox': 'https://huggingface.co/ArthurZ/jukebox/blob/main/genres.json',
    },
    'lyrics_file': {
        'jukebox': 'https://huggingface.co/ArthurZ/jukebox/blob/main/lyrics.json',
    },
}

__A			:					Optional[Any]						=			{
    'jukebox': 5_1_2,
}





class 			_SCREAMING_SNAKE_CASE (   __snake_case		):







   '''simple docstring'''




   lowerCamelCase__				=      VOCAB_FILES_NAMES
   lowerCamelCase__				=      PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase__				=      PRETRAINED_LYRIC_TOKENS_SIZES
   lowerCamelCase__				=      ["input_ids", "attention_mask"]





   def __init__(       self					:			List[Any]     , __lowerCamelCase					:			Tuple     , __lowerCamelCase					:			Union[str, Any]     , __lowerCamelCase					:			Optional[int]     , __lowerCamelCase					:			Optional[int]=["v3", "v2", "v2"]     , __lowerCamelCase					:			str=512     , __lowerCamelCase					:			str=5     , __lowerCamelCase					:			List[str]="<|endoftext|>"     , **__lowerCamelCase					:			Tuple     , ):
       SCREAMING_SNAKE_CASE										=   AddedToken(__lowerCamelCase     , lstrip=__lowerCamelCase     , rstrip=__lowerCamelCase			) if isinstance(__lowerCamelCase     , __lowerCamelCase			) else unk_token
       super().__init__(
           unk_token=__lowerCamelCase     , n_genres=__lowerCamelCase     , version=__lowerCamelCase     , max_n_lyric_tokens=__lowerCamelCase     , **__lowerCamelCase     , )
       SCREAMING_SNAKE_CASE										=   version
       SCREAMING_SNAKE_CASE										=   max_n_lyric_tokens
       SCREAMING_SNAKE_CASE										=   n_genres

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)

       SCREAMING_SNAKE_CASE										=   r"[^A-Za-z0-9.,:;!?\-'\"()\[\] \t\n]+"
       # In v2, we had a n_vocab=80 and in v3 we missed + and so n_vocab=79 of characters.
       if len(self.lyrics_encoder			) == 79:
           SCREAMING_SNAKE_CASE										=   oov.replace(r"\-'"     , r"\-+'"			)

       SCREAMING_SNAKE_CASE										=   regex.compile(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   {v: k for k, v in self.artists_encoder.items()}
       SCREAMING_SNAKE_CASE										=   {v: k for k, v in self.genres_encoder.items()}
       SCREAMING_SNAKE_CASE										=   {v: k for k, v in self.lyrics_encoder.items()}





   @property
   def      _snake_case		(       self					:			str			):
       return len(self.artists_encoder			) + len(self.genres_encoder			) + len(self.lyrics_encoder			)





   def      _snake_case		(       self					:			Dict			):
       return dict(self.artists_encoder     , self.genres_encoder     , self.lyrics_encoder			)





   def      _snake_case		(       self					:			Optional[Any]     , __lowerCamelCase					:			Optional[int]     , __lowerCamelCase					:			List[str]     , __lowerCamelCase					:			Dict			):
       SCREAMING_SNAKE_CASE										=   [self.artists_encoder.get(__lowerCamelCase     , 0			) for artist in list_artists]
       for genres in range(len(__lowerCamelCase			)			):
           SCREAMING_SNAKE_CASE										=   [self.genres_encoder.get(__lowerCamelCase     , 0			) for genre in list_genres[genres]]
           SCREAMING_SNAKE_CASE										=   list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]			))

       SCREAMING_SNAKE_CASE										=   [[self.lyrics_encoder.get(__lowerCamelCase     , 0			) for character in list_lyrics[0]], [], []]
       return artists_id, list_genres, lyric_ids





   def      _snake_case		(       self					:			List[Any]     , __lowerCamelCase					:			Any			):
       return list(__lowerCamelCase			)





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			Optional[int]     , __lowerCamelCase					:			Union[str, Any]     , __lowerCamelCase					:			Dict     , **__lowerCamelCase					:			Any			):
       SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   self.prepare_for_tokenization(__lowerCamelCase     , __lowerCamelCase     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self._tokenize(__lowerCamelCase			)
       return artist, genre, lyrics





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			str     , __lowerCamelCase					:			str     , __lowerCamelCase					:			str     , __lowerCamelCase					:			bool = False			):
       for idx in range(len(self.version			)			):
           if self.version[idx] == "v3":
               SCREAMING_SNAKE_CASE										=   artists[idx].lower()
               SCREAMING_SNAKE_CASE										=   [genres[idx].lower()]
           else:
               SCREAMING_SNAKE_CASE										=   self._normalize(artists[idx]			) + ".v2"
               SCREAMING_SNAKE_CASE										=   [
                   self._normalize(__lowerCamelCase			) + ".v2" for genre in genres[idx].split("_"			)
               ]  # split is for the full dictionary with combined genres

       if self.version[0] == "v2":
           SCREAMING_SNAKE_CASE										=   regex.compile(r"[^A-Za-z0-9.,:;!?\-'\"()\[\] \t\n]+"			)
           SCREAMING_SNAKE_CASE										=   "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,:;!?-+'\"()[] \t\n"
           SCREAMING_SNAKE_CASE										=   {vocab[index]: index + 1 for index in range(len(__lowerCamelCase			)			)}
           SCREAMING_SNAKE_CASE										=   0
           SCREAMING_SNAKE_CASE										=   len(__lowerCamelCase			) + 1
           SCREAMING_SNAKE_CASE										=   self.vocab
           SCREAMING_SNAKE_CASE										=   {v: k for k, v in self.vocab.items()}
           SCREAMING_SNAKE_CASE										=   ""
       else:
           SCREAMING_SNAKE_CASE										=   regex.compile(r"[^A-Za-z0-9.,:;!?\-+'\"()\[\] \t\n]+"			)

       SCREAMING_SNAKE_CASE										=   self._run_strip_accents(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   lyrics.replace("\\"     , "\n"			)
       SCREAMING_SNAKE_CASE										=   self.out_of_vocab.sub(""     , __lowerCamelCase			), [], []
       return artists, genres, lyrics





   def      _snake_case		(       self					:			Any     , __lowerCamelCase					:			Union[str, Any]			):
       SCREAMING_SNAKE_CASE										=   unicodedata.normalize("NFD"     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   []
       for char in text:
           SCREAMING_SNAKE_CASE										=   unicodedata.category(__lowerCamelCase			)
           if cat == "Mn":
               continue
           output.append(__lowerCamelCase			)
       return "".join(__lowerCamelCase			)





   def      _snake_case		(       self					:			Any     , __lowerCamelCase					:			str			):
       SCREAMING_SNAKE_CASE										=   (
           [chr(__lowerCamelCase			) for i in range(ord("a"			)     , ord("z"			) + 1			)]
           + [chr(__lowerCamelCase			) for i in range(ord("A"			)     , ord("Z"			) + 1			)]
           + [chr(__lowerCamelCase			) for i in range(ord("0"			)     , ord("9"			) + 1			)]
           + ["."]
       )
       SCREAMING_SNAKE_CASE										=   frozenset(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   re.compile(r"_+"			)
       SCREAMING_SNAKE_CASE										=   "".join([c if c in accepted else "_" for c in text.lower()]			)
       SCREAMING_SNAKE_CASE										=   pattern.sub("_"     , __lowerCamelCase			).strip("_"			)
       return text





   def      _snake_case		(       self					:			Tuple     , __lowerCamelCase					:			List[str]			):
       return " ".join(__lowerCamelCase			)





   def      _snake_case		(       self					:			Dict     , __lowerCamelCase					:			Union[str, Any]     , __lowerCamelCase					:			Optional[Union[str, TensorType]] = None     , __lowerCamelCase					:			bool = False			):
       # Convert to TensorType
       if not isinstance(__lowerCamelCase     , __lowerCamelCase			):
           SCREAMING_SNAKE_CASE										=   TensorType(__lowerCamelCase			)

       # Get a function reference for the correct framework
       if tensor_type == TensorType.TENSORFLOW:
           if not is_tf_available():
               raise ImportError(
                   "Unable to convert output to TensorFlow tensors format, TensorFlow is not installed."			)
           import tensorflow as tf

           SCREAMING_SNAKE_CASE										=   tf.constant
           SCREAMING_SNAKE_CASE										=   tf.is_tensor
       elif tensor_type == TensorType.PYTORCH:
           if not is_torch_available():
               raise ImportError("Unable to convert output to PyTorch tensors format, PyTorch is not installed."			)
           import torch

           SCREAMING_SNAKE_CASE										=   torch.tensor
           SCREAMING_SNAKE_CASE										=   torch.is_tensor
       elif tensor_type == TensorType.JAX:
           if not is_flax_available():
               raise ImportError("Unable to convert output to JAX tensors format, JAX is not installed."			)
           import jax.numpy as jnp  # noqa: F811

           SCREAMING_SNAKE_CASE										=   jnp.array
           SCREAMING_SNAKE_CASE										=   _is_jax
       else:
           SCREAMING_SNAKE_CASE										=   np.asarray
           SCREAMING_SNAKE_CASE										=   _is_numpy

       # Do the tensor conversion in batch

       try:
           if prepend_batch_axis:
               SCREAMING_SNAKE_CASE										=   [inputs]

           if not is_tensor(__lowerCamelCase			):
               SCREAMING_SNAKE_CASE										=   as_tensor(__lowerCamelCase			)
       except:  # noqa E722
           raise ValueError(
               "Unable to create tensor, you should probably activate truncation and/or padding "
               "with 'padding=True' 'truncation=True' to have batched tensors with the same length."			)

       return inputs





   def __call__(       self					:			int     , __lowerCamelCase					:			Optional[Any]     , __lowerCamelCase					:			str     , __lowerCamelCase					:			str=""     , __lowerCamelCase					:			Union[str, Any]="pt"			):
       SCREAMING_SNAKE_CASE										=   [0, 0, 0]
       SCREAMING_SNAKE_CASE										=   [artist] * len(self.version			)
       SCREAMING_SNAKE_CASE										=   [genres] * len(self.version			)

       SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   self.tokenize(__lowerCamelCase     , __lowerCamelCase     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   self._convert_token_to_id(__lowerCamelCase     , __lowerCamelCase     , __lowerCamelCase			)

       SCREAMING_SNAKE_CASE										=   [-INFINITY] * len(full_tokens[-1]			)
       SCREAMING_SNAKE_CASE										=   [
           self.convert_to_tensors(
               [input_ids + [artists_id[i]] + genres_ids[i] + full_tokens[i]]     , tensor_type=__lowerCamelCase			)
           for i in range(len(self.version			)			)
       ]
       return BatchEncoding({"input_ids": input_ids, "attention_masks": attention_masks}			)





   def      _snake_case		(       self					:			Optional[int]     , __lowerCamelCase					:			str     , __lowerCamelCase					:			Optional[str] = None			):
       if not os.path.isdir(__lowerCamelCase			):
           logger.error(f"Vocabulary path ({save_directory}) should be a directory"			)
           return

       SCREAMING_SNAKE_CASE										=   os.path.join(
           __lowerCamelCase     , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["artists_file"]			)
       with open(__lowerCamelCase     , "w"     , encoding="utf-8"			) as f:
           f.write(json.dumps(self.artists_encoder     , ensure_ascii=__lowerCamelCase			)			)

       SCREAMING_SNAKE_CASE										=   os.path.join(
           __lowerCamelCase     , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["genres_file"]			)
       with open(__lowerCamelCase     , "w"     , encoding="utf-8"			) as f:
           f.write(json.dumps(self.genres_encoder     , ensure_ascii=__lowerCamelCase			)			)

       SCREAMING_SNAKE_CASE										=   os.path.join(
           __lowerCamelCase     , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["lyrics_file"]			)
       with open(__lowerCamelCase     , "w"     , encoding="utf-8"			) as f:
           f.write(json.dumps(self.lyrics_encoder     , ensure_ascii=__lowerCamelCase			)			)

       return (artists_file, genres_file, lyrics_file)





   def      _snake_case		(       self					:			str     , __lowerCamelCase					:			int     , __lowerCamelCase					:			str     , __lowerCamelCase					:			Any			):
       SCREAMING_SNAKE_CASE										=   self.artists_decoder.get(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   [self.genres_decoder.get(__lowerCamelCase			) for genre in genres_index]
       SCREAMING_SNAKE_CASE										=   [self.lyrics_decoder.get(__lowerCamelCase			) for character in lyric_index]
       return artist, genres, lyrics


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


A_			:					str    			=     WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])

def 		UpperCamelCase   (lowercase_:					Union[str, Any]   )	-> Dict:
	A__				:       Union[str, Any]	  =						test_results.split(""" """   )

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

	return failures



class        _a		:


					'''simple docstring'''






					def __init__(					self       ,			A__       ,			A__     ):
						A__				:       Optional[Any]	  =						title

						A__				:       Tuple	  =						doc_test_results["""time_spent"""].split(""","""     )[0]
						A__				:       str	  =						doc_test_results["""success"""]
						A__				:       Optional[int]	  =						doc_test_results["""failures"""]
						A__				:       int	  =						self.n_success + self.n_failures

						# Failures and success of the modeling tests
						A__				:       Optional[int]	  =						doc_test_results






					@property
					def     __A     (					self     ):
						A__				:       Tuple	  =						[self._time_spent]
						A__				:       Tuple	  =						0

						for time in time_spent:
							A__				:       Dict	  =						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(A__     ) == 1:
								A__				:       Dict	  =						[0, 0, time_parts[0]]

							A__  ,  A__  ,  A__				:       Optional[Any]	  =						int(time_parts[0]     ), int(time_parts[1]     ), float(time_parts[2]     )
							total_secs += hours * 3600 + minutes * 60 + seconds

						A__  ,  A__  ,  A__				:       List[str]	  =						total_secs // 3600, (total_secs % 3600) // 60, total_secs % 60
						return F"""{int(A__     )}h{int(A__     )}m{int(A__     )}s"""






					@property
					def     __A     (					self     ):
						return {"type": "header", "text": {"type": "plain_text", "text": self.title}}






					@property
					def     __A     (					self     ):
						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     __A     (					self     ):
						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     __A     (					self     ):
						A__				:       Tuple	  =						40
						A__				:       Dict	  =						{k: v["""failed"""] for k, v in doc_test_results.items() if isinstance(A__       ,			A__     )}

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

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

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

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






					@property
					def     __A     (					self     ):
						A__				:       Tuple	  =						[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(A__     )






					@staticmethod
					def     __A     (					):
						A__				:       List[str]	  =						[
						    {
						        """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(A__     )}     )     )

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






					def     __A     (					self     ):
						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__				:       Any	  =						client.chat_postMessage(
						    channel=os.environ["""CI_SLACK_CHANNEL_ID_DAILY"""]       ,			blocks=self.payload       ,			text=A__       ,			)






					def     __A     (					self       ,			A__       ,			A__       ,			A__       ,			A__     ):
						A__				:       Tuple	  =						""""""
						for key, value in failures.items():
							A__				:       Any	  =						value[:200] + """ [Truncated]""" if len(A__     ) > 250 else value
							failures_text += F"""*{key}*\n_{value}_\n\n"""

						A__				:       Optional[Any]	  =						job_name
						A__				:       Union[str, Any]	  =						{"""type""": """section""", """text""": {"""type""": """mrkdwn""", """text""": text}}

						if job_link is not None:
							A__				:       Dict	  =						{
							    """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     __A     (					self     ):
						if self.thread_ts is None:
							raise ValueError("""Can only post reply if a post has been made."""     )

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

								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=A__       ,			thread_ts=self.thread_ts["""ts"""]       ,			)

								time.sleep(1     )



def 		UpperCamelCase   ()	-> Dict:
	A__				:       int	  =						os.environ["""GITHUB_RUN_ID"""]
	A__				:       Union[str, Any]	  =						f"""https://api.github.com/repos/huggingface/transformers/actions/runs/{run_id}/jobs?per_page=100"""
	A__				:       Optional[int]	  =						requests.get(lowercase_   ).json()
	A__				:       List[str]	  =						{}

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

		for i in range(lowercase_   ):
			A__				:       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 		UpperCamelCase   (lowercase_:					str   )	-> Any:
	A__				:       List[Any]	  =						{}

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

	return _artifact

def 		UpperCamelCase   ()	-> Union[str, Any]:



	class        _a		:


						'''simple docstring'''






						def __init__(					self       ,			A__     ):
							A__				:       str	  =						name
							A__				:       Optional[int]	  =						[]






						def __str__(					self     ):
							return self.name






						def     __A     (					self       ,			A__     ):
							self.paths.append({"""name""": self.name, """path""": path}     )



	A__				:       Dict[str, Artifact]	  =						{}

	A__				:       int	  =						filter(os.path.isdir       , os.listdir()   )
	for directory in directories:
		A__				:       Dict	  =						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__":
	A_			:					str    			=     get_job_links()
	A_			:					Dict    			=     retrieve_available_artifacts()

	A_			:					int    			=     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'
	A_			:					int    			=     {
	    v: {
	        'failed': [],
	        'failures': {},
	    }
	    for v in docs.values()
	}

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

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

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

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

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

						A_			:					Optional[int]    			=     all_failures[test] if test in all_failures else 'N/A'
						A_			:					List[str]    			=     failure
						break

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



