

import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer

def 						UpperCamelCase					(lowercase_: List[Any]    ,      lowercase_: Tuple    ,      lowercase_: Optional[int]    ,      lowercase_: Dict    ,      lowercase_: Optional[int]=True    ,      lowercase_: Union[str, Any]="pt"					)     ->      str:
	A__							:    int        =		{"""add_prefix_space""": True} if isinstance(_A    ,      _A					) and not line.startswith(""" """					) else {}
	A__							:    Optional[int]        =		padding_side
	return tokenizer(
	    [line]    ,      max_length=_A    ,      padding="""max_length""" if pad_to_max_length else None    ,      truncation=_A    ,      return_tensors=_A    ,      add_special_tokens=_A    ,      **_A    ,      )

def 						UpperCamelCase					(lowercase_: Union[str, Any]    ,      lowercase_: str    ,      lowercase_: int=None    ,      )     ->      Dict:
	A__							:    Tuple        =		input_ids.ne(_A					).any(dim=0					)
	if attention_mask is None:
		return input_ids[:, keep_column_mask]
	else:
		return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])



class     _a						(UpperCAmelCase__				):


					'''simple docstring'''






					def __init__( self    ,       A__    ,       A__    ,       A__    ,       A__    ,       A__="train"    ,       A__=None    ,       A__=None    ,       A__=None    ,       A__=""    ,       ):
						super().__init__()
						A__							:    List[str]        =		Path(__lowercase			).joinpath(type_path + """.source"""			)
						A__							:    List[Any]        =		Path(__lowercase			).joinpath(type_path + """.target"""			)
						A__							:    str        =		self.get_char_lens(self.src_file			)
						A__							:    List[str]        =		max_source_length
						A__							:    str        =		max_target_length
						assert min(self.src_lens			) > 0, F"""found empty line in {self.src_file}"""
						A__							:    Tuple        =		tokenizer
						A__							:    List[Any]        =		prefix
						if n_obs is not None:
							A__							:    Optional[int]        =		self.src_lens[:n_obs]
						A__							:    str        =		src_lang
						A__							:    Optional[int]        =		tgt_lang






					def __len__( self			):
						return len(self.src_lens			)






					def __getitem__( self    ,       A__			):
						A__							:    Dict        =		index + 1  # linecache starts at 1
						A__							:    Union[str, Any]        =		self.prefix + linecache.getline(str(self.src_file			)    ,       __lowercase			).rstrip("""\n"""			)
						A__							:    List[Any]        =		linecache.getline(str(self.tgt_file			)    ,       __lowercase			).rstrip("""\n"""			)
						assert source_line, F"""empty source line for index {index}"""
						assert tgt_line, F"""empty tgt line for index {index}"""

						# Need to add eos token manually for T5
						if isinstance(self.tokenizer    ,       __lowercase			):
							source_line += self.tokenizer.eos_token
							tgt_line += self.tokenizer.eos_token

						# Pad source and target to the right
						A__							:    Dict        =		(
						    self.tokenizer.question_encoder if isinstance(self.tokenizer    ,       __lowercase			) else self.tokenizer
						)
						A__							:    Tuple        =		self.tokenizer.generator if isinstance(self.tokenizer    ,       __lowercase			) else self.tokenizer

						A__							:    List[Any]        =		encode_line(__lowercase    ,       __lowercase    ,       self.max_source_length    ,       """right"""			)
						A__							:    Union[str, Any]        =		encode_line(__lowercase    ,       __lowercase    ,       self.max_target_length    ,       """right"""			)

						A__							:    str        =		source_inputs["""input_ids"""].squeeze()
						A__							:    Any        =		target_inputs["""input_ids"""].squeeze()
						A__							:    List[str]        =		source_inputs["""attention_mask"""].squeeze()
						return {
						    "input_ids": source_ids,
						    "attention_mask": src_mask,
						    "decoder_input_ids": target_ids,
						}






					@staticmethod
					def   __A			( A__			):
						return [len(__lowercase			) for x in Path(__lowercase			).open().readlines()]






					def   __A			( self    ,       A__			):
						A__							:    Optional[int]        =		torch.stack([x["""input_ids"""] for x in batch]			)
						A__							:    str        =		torch.stack([x["""attention_mask"""] for x in batch]			)
						A__							:    Dict        =		torch.stack([x["""decoder_input_ids"""] for x in batch]			)
						A__							:    Tuple        =		(
						    self.tokenizer.generator.pad_token_id
						    if isinstance(self.tokenizer    ,       __lowercase			)
						    else self.tokenizer.pad_token_id
						)
						A__							:    Tuple        =		(
						    self.tokenizer.question_encoder.pad_token_id
						    if isinstance(self.tokenizer    ,       __lowercase			)
						    else self.tokenizer.pad_token_id
						)
						A__							:    Optional[int]        =		trim_batch(__lowercase    ,       __lowercase			)
						A__   ,   A__							:    str        =		trim_batch(__lowercase    ,       __lowercase    ,       attention_mask=__lowercase			)
						A__							:    Any        =		{
						    """input_ids""": source_ids,
						    """attention_mask""": source_mask,
						    """decoder_input_ids""": y,
						}
						return batch



A_       : str         =			getLogger(__name__)

def 						UpperCamelCase					(lowercase_: str					)     ->      Dict:
	return list(itertools.chain.from_iterable(_A					)					)

def 						UpperCamelCase					(lowercase_: List[Any]					)     ->      Any:
	A__							:    Optional[int]        =		get_git_info()
	save_json(_A    ,      os.path.join(_A    ,      """git_log.json"""					)					)

def 						UpperCamelCase					(lowercase_: Optional[int]    ,      lowercase_: Dict    ,      lowercase_: Dict=4    ,      **lowercase_: Optional[Any]					)     ->      List[Any]:





	with open(_A    ,      """w"""					) as f:
		json.dump(_A    ,      _A    ,      indent=_A    ,      **_A					)

def 						UpperCamelCase					(lowercase_: Optional[int]					)     ->      Optional[int]:





	with open(_A					) as f:
		return json.load(_A					)

def 						UpperCamelCase					()     ->      Optional[Any]:
	A__							:    Tuple        =		git.Repo(search_parent_directories=_A					)
	A__							:    Dict        =		{
	    """repo_id""": str(_A					),
	    """repo_sha""": str(repo.head.object.hexsha					),
	    """repo_branch""": str(repo.active_branch					),
	    """hostname""": str(socket.gethostname()					),
	}
	return repo_infos

def 						UpperCamelCase					(lowercase_: List[str]    ,      lowercase_: Union[str, Any]					)     ->      Optional[int]:
	return list(map(_A    ,      _A					)					)

def 						UpperCamelCase					(lowercase_: Any    ,      lowercase_: int					)     ->      Optional[int]:





	with open(_A    ,      """wb"""					) as f:
		return pickle.dump(_A    ,      _A					)

def 						UpperCamelCase					(lowercase_: Optional[int]					)     ->      Dict:





	def remove_articles(lowercase_: int					):
		return re.sub(r"""\b(a|an|the)\b"""    ,      """ """    ,      _A					)

	def white_space_fix(lowercase_: Union[str, Any]					):
		return " ".join(text.split()					)

	def remove_punc(lowercase_: Optional[Any]					):
		A__							:    Optional[Any]        =		set(string.punctuation					)
		return "".join(ch for ch in text if ch not in exclude					)

	def lower(lowercase_: Optional[Any]					):
		return text.lower()

	return white_space_fix(remove_articles(remove_punc(lower(_A					)					)					)					)

def 						UpperCamelCase					(lowercase_: List[str]    ,      lowercase_: Any					)     ->      List[Any]:
	A__							:    Tuple        =		normalize_answer(_A					).split()
	A__							:    str        =		normalize_answer(_A					).split()
	A__							:    Dict        =		Counter(_A					) & Counter(_A					)
	A__							:    Any        =		sum(common.values()					)
	if num_same == 0:
		return 0
	A__							:    List[str]        =		1.0 * num_same / len(_A					)
	A__							:    Union[str, Any]        =		1.0 * num_same / len(_A					)
	A__							:    Any        =		(2 * precision * recall) / (precision + recall)
	return fa

def 						UpperCamelCase					(lowercase_: str    ,      lowercase_: Optional[Any]					)     ->      Union[str, Any]:
	return normalize_answer(_A					) == normalize_answer(_A					)

def 						UpperCamelCase					(lowercase_: Tuple    ,      lowercase_: List[Any]					)     ->      List[str]:
	assert len(_A					) == len(_A					)
	A__							:    List[Any]        =		0
	for hypo, pred in zip(_A    ,      _A					):
		em += exact_match_score(_A    ,      _A					)
	if len(_A					) > 0:
		em /= len(_A					)
	return {"em": em}

def 						UpperCamelCase					(lowercase_: Tuple					)     ->      List[Any]:
	return model_prefix.startswith("""rag"""					)


def 						UpperCamelCase					(lowercase_: Optional[int]    ,      lowercase_: Any    ,      lowercase_: List[Any]					)     ->      List[str]:
	A__							:    Tuple        =		{p: p for p in extra_params}
	# T5 models don't have `dropout` param, they have `dropout_rate` instead
	A__							:    int        =		"""dropout_rate"""
	for p in extra_params:
		if getattr(_A    ,      _A    ,      _A					):
			if not hasattr(_A    ,      _A					) and not hasattr(_A    ,      equivalent_param[p]					):
				logger.info("""config doesn't have a `{}` attribute""".format(_A					)					)
				delattr(_A    ,      _A					)
				continue
			A__							:    Optional[int]        =		p if hasattr(_A    ,      _A					) else equivalent_param[p]
			setattr(_A    ,      _A    ,      getattr(_A    ,      _A					)					)
			delattr(_A    ,      _A					)
	return hparams, config









import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     None
	if token is not None:
		snake_case_		    =     {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

	snake_case_		    =     f"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
	snake_case_		    =     requests.get(_A     ,	headers=_A							).json()
	snake_case_		    =     {}

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

		for i in range(_A							):
			snake_case_		    =     requests.get(url + f"&page={i + 2}"     ,	headers=_A							).json()
			job_links.update({job["name"]: job["html_url"] for job in result["jobs"]}							)

		return job_links
	except Exception:
		print(f"Unknown error, could not fetch links:\n{traceback.format_exc()}"							)

	return {}


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     None
	if token is not None:
		snake_case_		    =     {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

	snake_case_		    =     f"https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"
	snake_case_		    =     requests.get(_A     ,	headers=_A							).json()
	snake_case_		    =     {}

	try:
		artifacts.update({artifact["name"]: artifact["archive_download_url"] for artifact in result["artifacts"]}							)
		snake_case_		    =     math.ceil((result["total_count"] - 100) / 100							)

		for i in range(_A							):
			snake_case_		    =     requests.get(url + f"&page={i + 2}"     ,	headers=_A							).json()
			artifacts.update({artifact["name"]: artifact["archive_download_url"] for artifact in result["artifacts"]}							)

		return artifacts
	except Exception:
		print(f"Unknown error, could not fetch links:\n{traceback.format_exc()}"							)

	return {}


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A     ,	_A							):







	'''simple docstring'''





	snake_case_		    =     None
	if token is not None:
		snake_case_		    =     {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

	snake_case_		    =     requests.get(_A     ,	headers=_A     ,	allow_redirects=_A							)
	snake_case_		    =     result.headers["Location"]
	snake_case_		    =     requests.get(_A     ,	allow_redirects=_A							)
	snake_case_		    =     os.path.join(_A     ,	f"{artifact_name}.zip"							)
	with open(_A     ,	"wb"							) as fp:
		fp.write(response.content							)


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     []
	snake_case_		    =     []
	snake_case_		    =     None

	with zipfile.ZipFile(_A							) as z:
		for filename in z.namelist():
			if not os.path.isdir(_A							):
				# read the file
				if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
					with z.open(_A							) as f:
						for line in f:
							snake_case_		    =     line.decode("UTF-8"							).strip()
							if filename == "failures_line.txt":
								try:
									# `error_line` is the place where `error` occurs
									snake_case_		    =     line[: line.index(": "							)]
									snake_case_		    =     line[line.index(": "							) + len(": "							) :]
									errors.append([error_line, error]							)
								except Exception:
									# skip un-related lines
									pass
							elif filename == "summary_short.txt" and line.startswith("FAILED "							):
								# `test` is the test method that failed
								snake_case_		    =     line[len("FAILED "							) :]
								failed_tests.append(_A							)
							elif filename == "job_name.txt":
								snake_case_		    =     line

	if len(_A							) != len(_A							):
		raise ValueError(
		    f"`errors` and `failed_tests` should have the same number of elements. Got {len(_A							)} for `errors` "
		    f"and {len(_A							)} for `failed_tests` instead. The test reports in {artifact_zip_path} have some"
		    " problem."							)

	snake_case_		    =     None
	if job_name and job_links:
		snake_case_		    =     job_links.get(_A     ,	_A							)

	# A list with elements of the form (line of error, error, failed test)
	snake_case_		    =     [x + [y] + [job_link] for x, y in zip(_A     ,	_A							)]

	return result


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     []

	snake_case_		    =     [os.path.join(_A     ,	_A							) for p in os.listdir(_A							) if p.endswith(".zip"							)]
	for p in paths:
		errors.extend(get_errors_from_single_artifact(_A     ,	job_links=_A							)							)

	return errors


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     Counter()
	counter.update([x[1] for x in logs]							)
	snake_case_		    =     counter.most_common()
	snake_case_		    =     {}
	for error, count in counts:
		if error_filter is None or error not in error_filter:
			snake_case_		    =     {"count": count, "failed_tests": [(x[2], x[0]) for x in logs if x[1] == error]}

	snake_case_		    =     dict(sorted(r.items()     ,	key=lambda _A							: item[1]["count"]     ,	reverse=_A							)							)
	return r


def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     test.split("::"							)[0]
	if test.startswith("tests/models/"							):
		snake_case_		    =     test.split("/"							)[2]
	else:
		snake_case_		    =     None

	return test


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     [(x[0], x[1], get_model(x[2]							)) for x in logs]
	snake_case_		    =     [x for x in logs if x[2] is not None]
	snake_case_		    =     {x[2] for x in logs}

	snake_case_		    =     {}
	for test in tests:
		snake_case_		    =     Counter()
		# count by errors in `test`
		counter.update([x[1] for x in logs if x[2] == test]							)
		snake_case_		    =     counter.most_common()
		snake_case_		    =     {error: count for error, count in counts if (error_filter is None or error not in error_filter)}
		snake_case_		    =     sum(error_counts.values()							)
		if n_errors > 0:
			snake_case_		    =     {"count": n_errors, "errors": error_counts}

	snake_case_		    =     dict(sorted(r.items()     ,	key=lambda _A							: item[1]["count"]     ,	reverse=_A							)							)
	return r


def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     "| no. | error | status |"
	snake_case_		    =     "|-:|:-|:-|"
	snake_case_		    =     [header, sep]
	for error in reduced_by_error:
		snake_case_		    =     reduced_by_error[error]["count"]
		snake_case_		    =     f"| {count} | {error[:100]} |  |"
		lines.append(_A							)

	return "\n".join(_A							)


def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     "| model | no. of errors | major error | count |"
	snake_case_		    =     "|-:|-:|-:|-:|"
	snake_case_		    =     [header, sep]
	for model in reduced_by_model:
		snake_case_		    =     reduced_by_model[model]["count"]
		snake_case_    ,      snake_case_		    =     list(reduced_by_model[model]["errors"].items()							)[0]
		snake_case_		    =     f"| {model} | {count} | {error[:60]} | {_count} |"
		lines.append(_A							)

	return "\n".join(_A							)


if __name__ == "__main__":
		lowercase__				:     int 		=						argparse.ArgumentParser()
		# Required parameters
		parser.add_argument("--workflow_run_id", type=str, required=True, help="A GitHub Actions workflow run id.")
		parser.add_argument(
		    "--output_dir",
		    type=str,
		    required=True,
		    help="Where to store the downloaded artifacts and other result files.",
		)
		parser.add_argument("--token", default=None, type=str, help="A token that has actions:read permission.")
		lowercase__				:     int 		=						parser.parse_args()

		os.makedirs(args.output_dir, exist_ok=True)

		lowercase__				:     Optional[Any] 		=						get_job_links(args.workflow_run_id, token=args.token)
		lowercase__				:     List[Any] 		=						{}
		# To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
		# For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
		if _job_links:
				for k, v in _job_links.items():
						# This is how GitHub actions combine job names.
						if " / " in k:
								lowercase__				:     Tuple 		=						k.find(" / ")
								lowercase__				:     Union[str, Any] 		=						k[index + len(" / ") :]
						lowercase__				:     Union[str, Any] 		=						v
		with open(os.path.join(args.output_dir, "job_links.json"), "w", encoding="UTF-8") as fp:
				json.dump(job_links, fp, ensure_ascii=False, indent=4)

		lowercase__				:     Any 		=						get_artifacts_links(args.workflow_run_id, token=args.token)
		with open(os.path.join(args.output_dir, "artifacts.json"), "w", encoding="UTF-8") as fp:
				json.dump(artifacts, fp, ensure_ascii=False, indent=4)

		for idx, (name, url) in enumerate(artifacts.items()):
				download_artifact(name, url, args.output_dir, args.token)
				# Be gentle to GitHub
				time.sleep(1)

		lowercase__				:     List[Any] 		=						get_all_errors(args.output_dir, job_links=job_links)

		# `e[1]` is the error
		lowercase__				:     str 		=						Counter()
		counter.update([e[1] for e in errors])

		# print the top 30 most common test errors
		lowercase__				:     Union[str, Any] 		=						counter.most_common(30)
		for item in most_common:
				print(item)

		with open(os.path.join(args.output_dir, "errors.json"), "w", encoding="UTF-8") as fp:
				json.dump(errors, fp, ensure_ascii=False, indent=4)

		lowercase__				:     int 		=						reduce_by_error(errors)
		lowercase__				:     List[str] 		=						reduce_by_model(errors)

		lowercase__				:     Tuple 		=						make_github_table(reduced_by_error)
		lowercase__				:     Optional[int] 		=						make_github_table_per_model(reduced_by_model)

		with open(os.path.join(args.output_dir, "reduced_by_error.txt"), "w", encoding="UTF-8") as fp:
				fp.write(sa)
		with open(os.path.join(args.output_dir, "reduced_by_model.txt"), "w", encoding="UTF-8") as fp:
				fp.write(sa)
