





"""simple docstring"""






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

def       __A (     a_  :Optional[int])						->						int:
				__a	:  Optional[Any]         =					test_results.split(''' ''')

				__a	:  int         =					0
				__a	:  int         =					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	:  Tuple         =					expressions[-2] if '''=''' in expressions[-1] else expressions[-1]

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

				return failed, success, time_spent

def       __A (     a_  :Optional[Any])						->						Tuple:
				__a	:  str         =					{}
				__a	:  Any         =					None
				__a	:  str         =					False
				for line in failures_short_lines.split('''\n'''):
								if re.search(R'''_ \[doctest\]'''				,    a_):
												__a	:  List[Any]         =					True
												__a	:  List[Any]         =					line.split(''' ''')[2]
								elif in_error and not line.split(''' ''')[0].isdigit():
												__a	:  str         =					line
												__a	:  int         =					False

				return failures




class 			__lowercase     :







					'''simple docstring'''




					def __init__(  self		,     _UpperCAmelCase		,     _UpperCAmelCase       ):
									__a	:  List[str]         =					title

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

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







					@property
					def 	_lowerCamelCase						(  self       ):
									__a	:  List[str]         =					[self._time_spent]
									__a	:  List[Any]         =					0

									for time in time_spent:
													__a	:  int         =					time.split(''':'''       )

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

													__a    ,  __a    ,  __a	:  List[str]         =					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(_UpperCAmelCase       )}h{int(_UpperCAmelCase       )}m{int(_UpperCAmelCase       )}s"""







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







					@property
					def 	_lowerCamelCase						(  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 	_lowerCamelCase						(  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 	_lowerCamelCase						(  self       ):
									__a	:  Any         =					40
									__a	:  int         =					{k: v['''failed'''] for k, v in doc_test_results.items() if isinstance(_UpperCAmelCase		,     _UpperCAmelCase       )}

									__a	:  str         =					''''''
									for category, failures in category_failures.items():
													if len(_UpperCAmelCase       ) == 0:
																	continue

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

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

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







					@property
					def 	_lowerCamelCase						(  self       ):
									__a	:  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(_UpperCAmelCase       )







					@staticmethod
					def 	_lowerCamelCase						(  ):
									__a	:  Optional[int]         =					[
									    {
									        '''type''': '''section''',
									        '''text''': {
									            '''type''': '''plain_text''',
									            '''text''': '''There was an issue running the tests.''',
									        },
									        '''accessory''': {
									            '''type''': '''button''',
									            '''text''': {'''type''': '''plain_text''', '''text''': '''Check Action results''', '''emoji''': True},
									            '''url''': f"""https://github.com/huggingface/transformers/actions/runs/{os.environ["GITHUB_RUN_ID"]}""",
									        },
									    }
									]

									print('''Sending the following payload'''       )
									print(json.dumps({'''blocks''': json.loads(_UpperCAmelCase       )}       )       )

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







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

									__a	:  Union[str, Any]         =					f"""{self.n_failures} failures out of {self.n_tests} tests,""" if self.n_failures else '''All tests passed.'''

									__a	:  int         =					client.chat_postMessage(
									    channel=os.environ['''CI_SLACK_CHANNEL_ID_DAILY''']		,     blocks=self.payload		,     text=_UpperCAmelCase		,     )







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase		,     _UpperCAmelCase		,     _UpperCAmelCase		,     _UpperCAmelCase       ):
									__a	:  Optional[Any]         =					''''''
									for key, value in failures.items():
													__a	:  Tuple         =					value[:200] + ''' [Truncated]''' if len(_UpperCAmelCase       ) > 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	:  List[str]         =					{
													    '''type''': '''button''',
													    '''text''': {'''type''': '''plain_text''', '''text''': '''GitHub Action job''', '''emoji''': True},
													    '''url''': job_link,
													}

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







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

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

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

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

																	time.sleep(1       )






def       __A (     )						->						Union[str, Any]:
				__a	:  List[str]         =					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	:  List[Any]         =					requests.get(a_).json()
				__a	:  List[str]         =					{}

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

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

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

				return {}

def       __A (     a_  :str)						->						List[str]:
				__a	:  List[str]         =					{}

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

				return _artifact

def       __A (     )						->						List[Any]:




				class 			__lowercase     :







									'''simple docstring'''




									def __init__(  self		,     _UpperCAmelCase       ):
													__a	:  str         =					name
													__a	:  List[str]         =					[]







									def __str__(  self       ):
													return self.name







									def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
													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	:  Union[str, Any]         =					directory
								if artifact_name not in _available_artifacts:
												__a	:  Any         =					Artifact(a_)

												_available_artifacts[artifact_name].add_path(a_)

				return _available_artifacts


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

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

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

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

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

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

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

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

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






"""simple docstring"""






import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter

from transformers import HfArgumentParser

def       __A (     a_  :List[Any]=None				,    a_  :Tuple=None)						->						List[Any]:
				return field(default_factory=lambda: default				,    metadata=a_)




@dataclass
class 			__lowercase     :







					'''simple docstring'''




					__lowerCAmelCase					=					field(
					    metadata={'''help''': '''The csv file to plot.'''}				, )
					__lowerCAmelCase					=					field(
					    default=_UpperCamelCase				, metadata={'''help''': '''Whether to plot along batch size or sequence length. Defaults to sequence length.'''}				, )
					__lowerCAmelCase					=					field(
					    default=_UpperCamelCase				, metadata={'''help''': '''Whether the csv file has time results or memory results. Defaults to memory results.'''}				, )
					__lowerCAmelCase					=					field(
					    default=_UpperCamelCase				, metadata={'''help''': '''Disable logarithmic scale when plotting'''}				, )
					__lowerCAmelCase					=					field(
					    default=_UpperCamelCase				, metadata={
					        '''help''': '''Whether the csv file has training results or inference results. Defaults to inference results.'''
					    }				, )
					__lowerCAmelCase					=					field(
					    default=_UpperCamelCase				, metadata={'''help''': '''Filename under which the plot will be saved. If unused no plot is saved.'''}				, )
					__lowerCAmelCase					=					list_field(
					    default=_UpperCamelCase				, metadata={'''help''': '''List of model names that are used instead of the ones in the csv file.'''}							)






def       __A (     a_  :Optional[Any])						->						Any:
				try:
								int(a_)
								return True
				except ValueError:
								return False

def       __A (     a_  :List[Any])						->						Any:
				try:
								float(a_)
								return True
				except ValueError:
								return False




class 			__lowercase     :







					'''simple docstring'''




					def __init__(  self		,     _UpperCAmelCase       ):
									__a	:  Dict         =					args
									__a	:  Tuple         =					defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}       )

									with open(self.args.csv_file		,     newline=''''''       ) as csv_file:
													__a	:  int         =					csv.DictReader(_UpperCAmelCase       )
													for row in reader:
																	__a	:  Union[str, Any]         =					row['''model''']
																	self.result_dict[model_name]["bsz"].append(int(row['''batch_size''']       )       )
																	self.result_dict[model_name]["seq_len"].append(int(row['''sequence_length''']       )       )
																	if can_convert_to_int(row['''result''']       ):
																					# value is not None
																					__a	:  Optional[int]         =					int(row['''result''']       )
																	elif can_convert_to_float(row['''result''']       ):
																					# value is not None
																					__a	:  Optional[Any]         =					float(row['''result''']       )







					def 	_lowerCamelCase						(  self       ):
									__a    ,  __a	:  Optional[int]         =					plt.subplots()
									__a	:  str         =					'''Time usage''' if self.args.is_time else '''Memory usage'''
									__a	:  str         =					title_str + ''' for training''' if self.args.is_train else title_str + ''' for inference'''

									if not self.args.no_log_scale:
													# set logarithm scales
													ax.set_xscale('''log'''       )
													ax.set_yscale('''log'''       )

									for axis in [ax.xaxis, ax.yaxis]:
													axis.set_major_formatter(ScalarFormatter()       )

									for model_name_idx, model_name in enumerate(self.result_dict.keys()       ):
													__a	:  str         =					sorted(set(self.result_dict[model_name]['''bsz''']       )       )
													__a	:  Dict         =					sorted(set(self.result_dict[model_name]['''seq_len''']       )       )
													__a	:  Dict         =					self.result_dict[model_name]['''result''']

													((__a)    ,  (__a))	:  List[Any]         =					(
													    (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
													)

													__a	:  Any         =					(
													    model_name if self.args.short_model_names is None else self.args.short_model_names[model_name_idx]
													)

													for inner_loop_value in inner_loop_array:
																	if self.args.plot_along_batch:
																					__a	:  Optional[int]         =					np.asarray(
																					    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]		,     dtype=_UpperCAmelCase		,     )
																	else:
																					__a	:  Dict         =					np.asarray(
																					    [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]		,     dtype=np.floataa		,     )

																	((__a)    ,  (__a))	:  Union[str, Any]         =					(
																	    ('''batch_size''', '''len''') if self.args.plot_along_batch else ('''in #tokens''', '''bsz''')
																	)

																	__a	:  Any         =					np.asarray(_UpperCAmelCase		,     _UpperCAmelCase       )[: len(_UpperCAmelCase       )]
																	plt.scatter(
																	    _UpperCAmelCase		,     _UpperCAmelCase		,     label=f"""{label_model_name} - {inner_loop_label}: {inner_loop_value}"""       )
																	plt.plot(_UpperCAmelCase		,     _UpperCAmelCase		,     '''--'''       )

													title_str += f""" {label_model_name} vs."""

									__a	:  Optional[Any]         =					title_str[:-4]
									__a	:  Optional[int]         =					'''Time in s''' if self.args.is_time else '''Memory in MB'''

									# plot
									plt.title(_UpperCAmelCase       )
									plt.xlabel(_UpperCAmelCase       )
									plt.ylabel(_UpperCAmelCase       )
									plt.legend()

									if self.args.figure_png_file is not None:
													plt.savefig(self.args.figure_png_file       )
									else:
													plt.show()






def       __A (     )						->						List[str]:
				__a	:  List[str]         =					HfArgumentParser(a_)
				__a	:  Optional[int]         =					parser.parse_args_into_dataclasses()[0]
				__a	:  Tuple         =					Plot(args=a_)
				plot.plot()


if __name__ == "__main__":
		main()