


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       :      Dict	=	WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"])





def   _lowerCAmelCase				(   UpperCamelCase__:     Any						) ->   Optional[Any]:





	"""simple docstring"""







	A								=				test_results.split(""" """						)

	A								=				0
	A								=				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								=				expressions[-2] if """=""" in expressions[-1] else expressions[-1]

	for i, expression in enumerate(UpperCamelCase__						):
		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				(   UpperCamelCase__:     int						) ->   Dict:





	"""simple docstring"""







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

	return failures






class       _UpperCamelCase    :

				"""simple docstring"""







				def __init__(						self				,   a__				,   a__   )	->				Union[str, Any]:
					A								=				title

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

					# Failures and success of the modeling tests
					A								=				doc_test_results

				@property
				def      _UpperCAmelCase					(						self   )	->				str:
					A								=				[self._time_spent]
					A								=				0

					for time in time_spent:
						A								=				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								=				[0, 0, time_parts[0]]

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

					A					,			A					,			A								=				total_secs // 3600, (total_secs % 3600) // 60, total_secs % 60
					return f'{int(a__   )}h{int(a__   )}m{int(a__   )}s'

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

				@property
				def      _UpperCAmelCase					(						self   )	->				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      _UpperCAmelCase					(						self   )	->				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      _UpperCAmelCase					(						self   )	->				Dict:
					A								=				40
					A								=				{k: v["""failed"""] for k, v in doc_test_results.items() if isinstance(a__				,   a__   )}

					A								=				""""""
					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      _UpperCAmelCase					(						self   )	->				str:
					A								=				[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      _UpperCAmelCase					(						)	->				int:
					A								=				[
					    {
					        """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      _UpperCAmelCase					(						self   )	->				List[str]:
					print("""Sending the following payload"""   )
					print(json.dumps({"""blocks""": json.loads(self.payload   )}   )   )

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

					A								=				client.chat_postMessage(
					    channel=os.environ["""CI_SLACK_CHANNEL_ID_DAILY"""]				,   blocks=self.payload				,   text=a__				,   )

				def      _UpperCAmelCase					(						self				,   a__				,   a__				,   a__				,   a__   )	->				Union[str, Any]:
					A								=				""""""
					for key, value in failures.items():
						A								=				value[:200] + """ [Truncated]""" if len(a__   ) > 250 else value
						failures_text += f'*{key}*\n_{value}_\n\n'

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

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

					A								=				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								=				sorted(self.doc_test_results.items()				,   key=lambda a__   : t[0]   )
					for job, job_result in sorted_dict:
						if len(job_result["""failures"""]   ):
							A								=				f'*Num failures* :{len(job_result["failed"]   )} \n'
							A								=				job_result["""failures"""]
							A								=				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   _lowerCAmelCase				(   ) ->   Tuple:





	"""simple docstring"""







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

	try:
		jobs.update({job["""name"""]: job["""html_url"""] for job in result["""jobs"""]}						)
		A								=				math.ceil((result["""total_count"""] - 1_00) / 1_00						)

		for i in range(UpperCamelCase__						):
			A								=				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."""							,					UpperCamelCase__						)

	return {}





def   _lowerCAmelCase				(   UpperCamelCase__:     str						) ->   int:





	"""simple docstring"""







	A								=				{}

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

	return _artifact





def   _lowerCAmelCase				(   ) ->   List[Any]:





	"""simple docstring"""







	class       _UpperCamelCase    :

					"""simple docstring"""







					def __init__(						self				,   a__   )	->				Tuple:
						A								=				name
						A								=				[]

					def __str__(						self   )	->				Any:
						return self.name

					def      _UpperCAmelCase					(						self				,   a__   )	->				int:
						self.paths.append({"""name""": self.name, """path""": path}   )
	A								=				{}

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

			_available_artifacts[artifact_name].add_path(UpperCamelCase__						)

	return _available_artifacts


if __name__ == "__main__":
				_lowercase       :      Union[str, Any]	=	get_job_links()
				_lowercase       :      Optional[Any]	=	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       :      Tuple	=	{
				    v: {
				        "failed": [],
				        "failures": {},
				    }
				    for v in docs.values()
				}

				# Link to the GitHub Action job
				_lowercase       :      Tuple	=	github_actions_job_links.get("run_doctests")

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

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

																if "::" in line:
																				_lowercase	,							_lowercase       :      int	=	line.split("::")
																else:
																				_lowercase	,							_lowercase       :      Optional[int]	=	line, line

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

																								_lowercase       :      Optional[int]	=	all_failures[test] if test in all_failures else "N/A"
																								_lowercase       :      str	=	failure
																								break

				_lowercase       :      Tuple	=	Message("🤗 Results of the doc tests.", doc_test_results)
				message.post()
				message.post_reply()







import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class       _UpperCamelCase    (					__snake_case				):

				"""simple docstring"""







				lowerCAmelCase 		= ['image_processor', 'tokenizer']
				lowerCAmelCase 		= 'ViltImageProcessor'
				lowerCAmelCase 		= ('BertTokenizer', 'BertTokenizerFast')

				def __init__(						self				,   a__=None				,   a__=None				,   **a__   )	->				Any:
					A								=				None
					if "feature_extractor" in kwargs:
						warnings.warn(
						    """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
						    """ instead."""				,   a__				,   )
						A								=				kwargs.pop("""feature_extractor"""   )

					A								=				image_processor if image_processor is not None else feature_extractor
					if image_processor is None:
						raise ValueError("""You need to specify an `image_processor`."""   )
					if tokenizer is None:
						raise ValueError("""You need to specify a `tokenizer`."""   )

					super().__init__(a__				,   a__   )
					A								=				self.image_processor

				def __call__(						self				,   a__				,   a__ = None				,   a__ = True				,   a__ = False				,   a__ = None				,   a__ = None				,   a__ = 0				,   a__ = None				,   a__ = None				,   a__ = None				,   a__ = False				,   a__ = False				,   a__ = False				,   a__ = False				,   a__ = True				,   a__ = None				,   **a__				,   )	->				BatchEncoding:
					A								=				self.tokenizer(
					    text=a__				,   add_special_tokens=a__				,   padding=a__				,   truncation=a__				,   max_length=a__				,   stride=a__				,   pad_to_multiple_of=a__				,   return_token_type_ids=a__				,   return_attention_mask=a__				,   return_overflowing_tokens=a__				,   return_special_tokens_mask=a__				,   return_offsets_mapping=a__				,   return_length=a__				,   verbose=a__				,   return_tensors=a__				,   **a__				,   )
					# add pixel_values + pixel_mask
					A								=				self.image_processor(a__				,   return_tensors=a__   )
					encoding.update(a__   )

					return encoding

				def      _UpperCAmelCase					(						self				,   *a__				,   **a__   )	->				Union[str, Any]:
					return self.tokenizer.batch_decode(*a__				,   **a__   )

				def      _UpperCAmelCase					(						self				,   *a__				,   **a__   )	->				Any:
					return self.tokenizer.decode(*a__				,   **a__   )

				@property
				def      _UpperCAmelCase					(						self   )	->				int:
					A								=				self.tokenizer.model_input_names
					A								=				self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )

				@property
				def      _UpperCAmelCase					(						self   )	->				str:
					warnings.warn(
					    """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""				,   a__				,   )
					return self.image_processor_class

				@property
				def      _UpperCAmelCase					(						self   )	->				str:
					warnings.warn(
					    """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""				,   a__				,   )
					return self.image_processor



