



"""simple docstring"""

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

import requests





def       __magic_name__    (   _lowerCamelCase				: Dict  ,       _lowerCamelCase				: List[str]=None					):
							__a		:		Union[str, Any]									=       None
							if token is not None:
														__a		:		Optional[int]									=       {"""Accept""": """application/vnd.github+json""", """Authorization""": F'''Bearer {token}'''}

							__a		:		Optional[int]									=       F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'''
							__a		:		Any									=       requests.get(_lowerCamelCase  ,       headers=_lowerCamelCase					).json()
							__a		:		int									=       {}

							try:
														job_links.update({job["""name"""]: job["""html_url"""] for job in result["""jobs"""]}					)
														__a		:		Tuple									=       math.ceil((result["""total_count"""] - 1_0_0) / 1_0_0					)

														for i in range(_lowerCamelCase					):
																					__a		:		List[str]									=       requests.get(url + F'''&page={i + 2}'''  ,       headers=_lowerCamelCase					).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       __magic_name__    (   _lowerCamelCase				: Optional[Any]  ,       _lowerCamelCase				: Tuple=None					):
							__a		:		str									=       None
							if token is not None:
														__a		:		int									=       {"""Accept""": """application/vnd.github+json""", """Authorization""": F'''Bearer {token}'''}

							__a		:		int									=       F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'''
							__a		:		int									=       requests.get(_lowerCamelCase  ,       headers=_lowerCamelCase					).json()
							__a		:		Union[str, Any]									=       {}

							try:
														artifacts.update({artifact["""name"""]: artifact["""archive_download_url"""] for artifact in result["""artifacts"""]}					)
														__a		:		Optional[int]									=       math.ceil((result["""total_count"""] - 1_0_0) / 1_0_0					)

														for i in range(_lowerCamelCase					):
																					__a		:		Any									=       requests.get(url + F'''&page={i + 2}'''  ,       headers=_lowerCamelCase					).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       __magic_name__    (   _lowerCamelCase				: Any  ,       _lowerCamelCase				: List[str]  ,       _lowerCamelCase				: Union[str, Any]  ,       _lowerCamelCase				: Tuple					):
							__a		:		Union[str, Any]									=       None
							if token is not None:
														__a		:		Union[str, Any]									=       {"""Accept""": """application/vnd.github+json""", """Authorization""": F'''Bearer {token}'''}

							__a		:		Union[str, Any]									=       requests.get(_lowerCamelCase  ,       headers=_lowerCamelCase  ,       allow_redirects=_lowerCamelCase					)
							__a		:		List[str]									=       result.headers["""Location"""]
							__a		:		Optional[int]									=       requests.get(_lowerCamelCase  ,       allow_redirects=_lowerCamelCase					)
							__a		:		List[Any]									=       os.path.join(_lowerCamelCase  ,       F'''{artifact_name}.zip'''					)
							with open(_lowerCamelCase  ,       """wb"""					) as fp:
														fp.write(response.content					)





def       __magic_name__    (   _lowerCamelCase				: str  ,       _lowerCamelCase				: int=None					):
							__a		:		List[Any]									=       []
							__a		:		Optional[Any]									=       []
							__a		:		Optional[int]									=       None

							with zipfile.ZipFile(_lowerCamelCase					) as z:
														for filename in z.namelist():
																					if not os.path.isdir(_lowerCamelCase					):
																												# read the file
																												if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
																																			with z.open(_lowerCamelCase					) as f:
																																										for line in f:
																																																	__a		:		Optional[Any]									=       line.decode("""UTF-8"""					).strip()
																																																	if filename == "failures_line.txt":
																																																								try:
																																																															# `error_line` is the place where `error` occurs
																																																															__a		:		List[str]									=       line[: line.index(""": """					)]
																																																															__a		:		Any									=       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
																																																								__a		:		List[Any]									=       line[len("""FAILED """					) :]
																																																								failed_tests.append(_lowerCamelCase					)
																																																	elif filename == "job_name.txt":
																																																								__a		:		Union[str, Any]									=       line

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

							__a		:		List[Any]									=       None
							if job_name and job_links:
														__a		:		int									=       job_links.get(_lowerCamelCase  ,       _lowerCamelCase					)

							# A list with elements of the form (line of error, error, failed test)
							__a		:		Optional[Any]									=       [x + [y] + [job_link] for x, y in zip(_lowerCamelCase  ,       _lowerCamelCase					)]

							return result





def       __magic_name__    (   _lowerCamelCase				: str  ,       _lowerCamelCase				: List[Any]=None					):
							__a		:		int									=       []

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

							return errors





def       __magic_name__    (   _lowerCamelCase				: Union[str, Any]  ,       _lowerCamelCase				: int=None					):
							__a		:		Optional[int]									=       Counter()
							counter.update([x[1] for x in logs]					)
							__a		:		Dict									=       counter.most_common()
							__a		:		Any									=       {}
							for error, count in counts:
														if error_filter is None or error not in error_filter:
																					__a		:		List[str]									=       {"""count""": count, """failed_tests""": [(x[2], x[0]) for x in logs if x[1] == error]}

							__a		:		List[Any]									=       dict(sorted(r.items()  ,       key=lambda _lowerCamelCase					: item[1]["count"]  ,       reverse=_lowerCamelCase					)					)
							return r





def       __magic_name__    (   _lowerCamelCase				: Dict					):
							__a		:		List[Any]									=       test.split("""::"""					)[0]
							if test.startswith("""tests/models/"""					):
														__a		:		Optional[int]									=       test.split("""/"""					)[2]
							else:
														__a		:		str									=       None

							return test





def       __magic_name__    (   _lowerCamelCase				: List[Any]  ,       _lowerCamelCase				: int=None					):
							__a		:		Union[str, Any]									=       [(x[0], x[1], get_model(x[2]					)) for x in logs]
							__a		:		List[Any]									=       [x for x in logs if x[2] is not None]
							__a		:		Optional[Any]									=       {x[2] for x in logs}

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

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





def       __magic_name__    (   _lowerCamelCase				: int					):
							__a		:		Optional[int]									=       """| no. | error | status |"""
							__a		:		Optional[Any]									=       """|-:|:-|:-|"""
							__a		:		int									=       [header, sep]
							for error in reduced_by_error:
														__a		:		Optional[int]									=       reduced_by_error[error]["""count"""]
														__a		:		Union[str, Any]									=       F'''| {count} | {error[:1_0_0]} |  |'''
														lines.append(_lowerCamelCase					)

							return "\n".join(_lowerCamelCase					)





def       __magic_name__    (   _lowerCamelCase				: Union[str, Any]					):
							__a		:		Optional[Any]									=       """| model | no. of errors | major error | count |"""
							__a		:		Optional[Any]									=       """|-:|-:|-:|-:|"""
							__a		:		Optional[int]									=       [header, sep]
							for model in reduced_by_model:
														__a		:		List[str]									=       reduced_by_model[model]["""count"""]
														__a							,     __a		:		str									=       list(reduced_by_model[model]["""errors"""].items()					)[0]
														__a		:		Optional[Any]									=       F'''| {model} | {count} | {error[:6_0]} | {_count} |'''
														lines.append(_lowerCamelCase					)

							return "\n".join(_lowerCamelCase					)


if __name__ == "__main__":
	lowercase__			   =  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__			   =  parser.parse_args()

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

	lowercase__			   =  get_job_links(args.workflow_run_id, token=args.token)
	lowercase__			   =  {}
	# 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__			   =  k.find(" / ")
				lowercase__			   =  k[index + len(" / ") :]
			lowercase__			   =  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__			   =  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__			   =  get_all_errors(args.output_dir, job_links=job_links)

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

	# print the top 30 most common test errors
	lowercase__			   =  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__			   =  reduce_by_error(errors)
	lowercase__			   =  reduce_by_model(errors)

	lowercase__			   =  make_github_table(reduced_by_error)
	lowercase__			   =  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)






"""simple docstring"""

import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class SCREAMING_SNAKE_CASE__					(		__snake_case     ,					unittest.TestCase      ):
						_lowerCAmelCase							=					LEDTokenizer
						_lowerCAmelCase							=					LEDTokenizerFast
						_lowerCAmelCase							=					True



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													super().setUp()
													__a		:		str									=       [
													    """l""",
													    """o""",
													    """w""",
													    """e""",
													    """r""",
													    """s""",
													    """t""",
													    """i""",
													    """d""",
													    """n""",
													    """\u0120""",
													    """\u0120l""",
													    """\u0120n""",
													    """\u0120lo""",
													    """\u0120low""",
													    """er""",
													    """\u0120lowest""",
													    """\u0120newer""",
													    """\u0120wider""",
													    """<unk>""",
													]
													__a		:		int									=       dict(zip(_lowercase						,     range(len(_lowercase							)							)							)							)
													__a		:		Optional[int]									=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
													__a		:		List[Any]									=       {"""unk_token""": """<unk>"""}

													__a		:		Union[str, Any]									=       os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES["""vocab_file"""]							)
													__a		:		Union[str, Any]									=       os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES["""merges_file"""]							)
													with open(self.vocab_file						,     """w"""						,     encoding="""utf-8"""							) as fp:
																				fp.write(json.dumps(_lowercase							) + """\n"""							)
													with open(self.merges_file						,     """w"""						,     encoding="""utf-8"""							) as fp:
																				fp.write("""\n""".join(_lowercase							)							)



						def     lowerCAmelCase__(self						,     **_lowercase							):





													'''simple docstring'''

													kwargs.update(self.special_tokens_map							)
													return self.tokenizer_class.from_pretrained(self.tmpdirname						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     **_lowercase							):





													'''simple docstring'''

													kwargs.update(self.special_tokens_map							)
													return self.rust_tokenizer_class.from_pretrained(self.tmpdirname						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													return "lower newer", "lower newer"



						@cached_property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""							)



						@cached_property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Any									=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
													__a		:		List[str]									=       [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Optional[int]									=       tokenizer(_lowercase						,     max_length=len(_lowercase							)						,     padding=_lowercase						,     return_tensors="""pt"""							)
																				self.assertIsInstance(_lowercase						,     _lowercase							)

																				self.assertEqual((2, 9)						,     batch.input_ids.shape							)
																				self.assertEqual((2, 9)						,     batch.attention_mask.shape							)
																				__a		:		Dict									=       batch.input_ids.tolist()[0]
																				self.assertListEqual(_lowercase						,     _lowercase							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Union[str, Any]									=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Tuple									=       tokenizer(_lowercase						,     padding=_lowercase						,     return_tensors="""pt"""							)
																				self.assertIn("""input_ids"""						,     _lowercase							)
																				self.assertIn("""attention_mask"""						,     _lowercase							)
																				self.assertNotIn("""labels"""						,     _lowercase							)
																				self.assertNotIn("""decoder_attention_mask"""						,     _lowercase							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Optional[Any]									=       [
													    """Summary of the text.""",
													    """Another summary.""",
													]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Dict									=       tokenizer(text_target=_lowercase						,     max_length=32						,     padding="""max_length"""						,     return_tensors="""pt"""							)
																				self.assertEqual(32						,     targets["""input_ids"""].shape[1]							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Optional[int]									=       tokenizer(
																				    ["""I am a small frog""" * 1024, """I am a small frog"""]						,     padding=_lowercase						,     truncation=_lowercase						,     return_tensors="""pt"""							)
																				self.assertIsInstance(_lowercase						,     _lowercase							)
																				self.assertEqual(batch.input_ids.shape						,     (2, 5122)							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Tuple									=       ["""A long paragraph for summarization."""]
													__a		:		Dict									=       [
													    """Summary of the text.""",
													]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		int									=       tokenizer(_lowercase						,     return_tensors="""pt"""							)
																				__a		:		Dict									=       tokenizer(text_target=_lowercase						,     return_tensors="""pt"""							)
																				__a		:		List[str]									=       inputs["""input_ids"""]
																				__a		:		List[Any]									=       targets["""input_ids"""]
																				self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()							)
																				self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()							)
																				self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()							)
																				self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Optional[Any]									=       ["""Summary of the text.""", """Another summary."""]
																				__a		:		List[Any]									=       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

																				__a		:		Union[str, Any]									=       tokenizer(_lowercase						,     padding=_lowercase							)
																				__a		:		Tuple									=       [[0] * len(_lowercase							) for x in encoded_output["""input_ids"""]]
																				__a		:		Union[str, Any]									=       tokenizer.pad(_lowercase							)
																				self.assertSequenceEqual(outputs["""global_attention_mask"""]						,     _lowercase							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													pass





						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																				with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
																											__a		:		Dict									=       self.rust_tokenizer_class.from_pretrained(_lowercase						,     **_lowercase							)
																											__a		:		Union[str, Any]									=       self.tokenizer_class.from_pretrained(_lowercase						,     **_lowercase							)
																											__a		:		Union[str, Any]									=       """A, <mask> AllenNLP sentence."""
																											__a		:		Dict									=       tokenizer_r.encode_plus(_lowercase						,     add_special_tokens=_lowercase						,     return_token_type_ids=_lowercase							)
																											__a		:		Tuple									=       tokenizer_p.encode_plus(_lowercase						,     add_special_tokens=_lowercase						,     return_token_type_ids=_lowercase							)
																											self.assertEqual(sum(tokens_r["""token_type_ids"""]							)						,     sum(tokens_p["""token_type_ids"""]							)							)
																											self.assertEqual(
																											    sum(tokens_r["""attention_mask"""]							) / len(tokens_r["""attention_mask"""]							)						,     sum(tokens_p["""attention_mask"""]							) / len(tokens_p["""attention_mask"""]							)						,     )

																											__a		:		Tuple									=       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]							)
																											__a		:		Any									=       tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]							)
																											self.assertSequenceEqual(tokens_p["""input_ids"""]						,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)
																											self.assertSequenceEqual(tokens_r["""input_ids"""]						,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)

																											self.assertSequenceEqual(
																											    _lowercase						,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]							)
																											self.assertSequenceEqual(
																											    _lowercase						,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]							)

