


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


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






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Dict    =				test_results.split(" "	)

  lowerCamelCase :					Any    =				0
  lowerCamelCase :					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.
  lowerCamelCase :					str    =				expressions[-2] if "=" in expressions[-1] else expressions[-1]

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

  return failed, success, time_spent






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Dict    =				{}
  lowerCamelCase :					List[str]    =				None
  lowerCamelCase :					Dict    =				False
  for line in failures_short_lines.split("\n"	):
    if re.search(r"_ \[doctest\]"      ,						SCREAMING_SNAKE_CASE_	):
      lowerCamelCase :					Dict    =				True
      lowerCamelCase :					int    =				line.split(" "	)[2]
    elif in_error and not line.split(" "	)[0].isdigit():
      lowerCamelCase :					str    =				line
      lowerCamelCase :					str    =				False

  return failures
class 	UpperCAmelCase_					:

   '''simple docstring'''




   def __init__(		self						,				__A						,				__A ):






     """simple docstring"""





     lowerCamelCase :					str    =				title

     lowerCamelCase :					str    =				doc_test_results["time_spent"].split("," )[0]
     lowerCamelCase :					Any    =				doc_test_results["success"]
     lowerCamelCase :					Tuple    =				doc_test_results["failures"]
     lowerCamelCase :					Dict    =				self.n_success + self.n_failures

     # Failures and success of the modeling tests
     lowerCamelCase :					Any    =				doc_test_results






   @property
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					str    =				[self._time_spent]
     lowerCamelCase :					Tuple    =				0

     for time in time_spent:
       lowerCamelCase :					Tuple    =				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:
         lowerCamelCase :					Optional[Any]    =				[0, 0, time_parts[0]]

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

     lowerCamelCase    ,	lowerCamelCase    ,	lowerCamelCase :					Any    =				total_secs // 3600, (total_secs % 3600) // 60, total_secs % 60
     return F"""{int(__A )}h{int(__A )}m{int(__A )}s"""






   @property
   def _snake_case    (		self ):






     """simple docstring"""





     return {"type": "header", "text": {"type": "plain_text", "text": self.title}}






   @property
   def _snake_case    (		self ):






     """simple docstring"""





     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 _snake_case    (		self ):






     """simple docstring"""





     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 _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Tuple    =				40
     lowerCamelCase :					List[str]    =				{k: v["failed"] for k, v in doc_test_results.items() if isinstance(__A						,				__A )}

     lowerCamelCase :					List[Any]    =				""
     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 _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Dict    =				[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 _snake_case    (		):






     """simple docstring"""





     lowerCamelCase :					Dict    =				[
         {
             "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 _snake_case    (		self ):






     """simple docstring"""





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

     lowerCamelCase :					List[Any]    =				F"""{self.n_failures} failures out of {self.n_tests} tests,""" if self.n_failures else "All tests passed."

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






   def _snake_case    (		self						,				__A						,				__A						,				__A						,				__A ):






     """simple docstring"""





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

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

     if job_link is not None:
       lowerCamelCase :					Union[str, Any]    =				{
           "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 _snake_case    (		self ):






     """simple docstring"""





     if self.thread_ts is None:
       raise ValueError("Can only post reply if a post has been made." )

     lowerCamelCase :					Optional[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" )

     lowerCamelCase :					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"] ):
         lowerCamelCase :					List[str]    =				F"""*Num failures* :{len(job_result['failed'] )} \n"""
         lowerCamelCase :					str    =				job_result["failures"]
         lowerCamelCase :					Union[str, Any]    =				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 		lowercase_(  ):


  '''simple docstring'''

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

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

    for i in range(SCREAMING_SNAKE_CASE_	):
      lowerCamelCase :					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."      ,						SCREAMING_SNAKE_CASE_	)

  return {}






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Union[str, Any]    =				{}

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

  return _artifact






def 		lowercase_(  ):


  '''simple docstring'''

  class 	UpperCAmelCase_					:

     '''simple docstring'''




     def __init__(		self						,				__A ):






       """simple docstring"""





       lowerCamelCase :					str    =				name
       lowerCamelCase :					List[Any]    =				[]






     def __str__(		self ):






       """simple docstring"""





       return self.name






     def _snake_case    (		self						,				__A ):






       """simple docstring"""





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



  lowerCamelCase :					Dict[str, Artifact]    =				{}

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

      _available_artifacts[artifact_name].add_path(SCREAMING_SNAKE_CASE_	)

  return _available_artifacts


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

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

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

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

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

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

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

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

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







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_snake_case             =     {
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     ['''SqueezeBertTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     [
       '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SqueezeBertForMaskedLM''',
       '''SqueezeBertForMultipleChoice''',
       '''SqueezeBertForQuestionAnswering''',
       '''SqueezeBertForSequenceClassification''',
       '''SqueezeBertForTokenClassification''',
       '''SqueezeBertModel''',
       '''SqueezeBertModule''',
       '''SqueezeBertPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_squeezebert import (
       SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SqueezeBertConfig,
       SqueezeBertOnnxConfig,
   )
   from .tokenization_squeezebert import SqueezeBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_squeezebert import (
          SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          SqueezeBertForMaskedLM,
          SqueezeBertForMultipleChoice,
          SqueezeBertForQuestionAnswering,
          SqueezeBertForSequenceClassification,
          SqueezeBertForTokenClassification,
          SqueezeBertModel,
          SqueezeBertModule,
          SqueezeBertPreTrainedModel,
      )

else:
   import sys

   _snake_case             =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



