



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

import requests





def 							A     (					_UpperCAmelCase    :       List[str]							,       _UpperCAmelCase    :       Any=None   )    ->			Union[str, Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       None
			if token is not None:
						_UpperCAmelCase			=       {'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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

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

						for i in range(_UpperCAmelCase   ):
									_UpperCAmelCase			=       requests.get(url + F"&page={i + 2}"							,       headers=_UpperCAmelCase   ).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 							A     (					_UpperCAmelCase    :       Dict							,       _UpperCAmelCase    :       Dict=None   )    ->			List[str]:







			'''simple docstring'''
			_UpperCAmelCase			=       None
			if token is not None:
						_UpperCAmelCase			=       {'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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

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

						for i in range(_UpperCAmelCase   ):
									_UpperCAmelCase			=       requests.get(url + F"&page={i + 2}"							,       headers=_UpperCAmelCase   ).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 							A     (					_UpperCAmelCase    :       Tuple							,       _UpperCAmelCase    :       List[str]							,       _UpperCAmelCase    :       Dict							,       _UpperCAmelCase    :       List[str]   )    ->			Union[str, Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       None
			if token is not None:
						_UpperCAmelCase			=       {'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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





def 							A     (					_UpperCAmelCase    :       List[Any]							,       _UpperCAmelCase    :       List[Any]=None   )    ->			Dict:







			'''simple docstring'''
			_UpperCAmelCase			=       []
			_UpperCAmelCase			=       []
			_UpperCAmelCase			=       None

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

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

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

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

			return result





def 							A     (					_UpperCAmelCase    :       Tuple							,       _UpperCAmelCase    :       Union[str, Any]=None   )    ->			Optional[Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       []

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

			return errors





def 							A     (					_UpperCAmelCase    :       Any							,       _UpperCAmelCase    :       Tuple=None   )    ->			Dict:







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

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





def 							A     (					_UpperCAmelCase    :       List[Any]   )    ->			Union[str, Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       test.split('::'   )[0]
			if test.startswith('tests/models/'   ):
						_UpperCAmelCase			=       test.split('/'   )[2]
			else:
						_UpperCAmelCase			=       None

			return test





def 							A     (					_UpperCAmelCase    :       Optional[Any]							,       _UpperCAmelCase    :       Union[str, Any]=None   )    ->			Union[str, Any]:







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

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

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





def 							A     (					_UpperCAmelCase    :       Optional[int]   )    ->			Tuple:







			'''simple docstring'''
			_UpperCAmelCase			=       '| no. | error | status |'
			_UpperCAmelCase			=       '|-:|:-|:-|'
			_UpperCAmelCase			=       [header, sep]
			for error in reduced_by_error:
						_UpperCAmelCase			=       reduced_by_error[error]['count']
						_UpperCAmelCase			=       F"| {count} | {error[:100]} |  |"
						lines.append(_UpperCAmelCase   )

			return "\n".join(_UpperCAmelCase   )





def 							A     (					_UpperCAmelCase    :       List[str]   )    ->			Union[str, Any]:







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

			return "\n".join(_UpperCAmelCase   )


if __name__ == "__main__":
							UpperCAmelCase__       =	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.")
							UpperCAmelCase__       =	parser.parse_args()

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

							UpperCAmelCase__       =	get_job_links(args.workflow_run_id, token=args.token)
							UpperCAmelCase__       =	{}
							# 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:
																												UpperCAmelCase__       =	k.find(" / ")
																												UpperCAmelCase__       =	k[index + len(" / ") :]
																					UpperCAmelCase__       =	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)

							UpperCAmelCase__       =	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)

							UpperCAmelCase__       =	get_all_errors(args.output_dir, job_links=job_links)

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

							# print the top 30 most common test errors
							UpperCAmelCase__       =	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)

							UpperCAmelCase__       =	reduce_by_error(errors)
							UpperCAmelCase__       =	reduce_by_model(errors)

							UpperCAmelCase__       =	make_github_table(reduced_by_error)
							UpperCAmelCase__       =	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)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase__       =	{
    "configuration_clip": [
        "CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPConfig",
        "CLIPOnnxConfig",
        "CLIPTextConfig",
        "CLIPVisionConfig",
    ],
    "processing_clip": ["CLIPProcessor"],
    "tokenization_clip": ["CLIPTokenizer"],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	["CLIPTokenizerFast"]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	["CLIPFeatureExtractor"]
							UpperCAmelCase__       =	["CLIPImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "CLIPModel",
							    "CLIPPreTrainedModel",
							    "CLIPTextModel",
							    "CLIPTextModelWithProjection",
							    "CLIPVisionModel",
							    "CLIPVisionModelWithProjection",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "TFCLIPModel",
							    "TFCLIPPreTrainedModel",
							    "TFCLIPTextModel",
							    "TFCLIPVisionModel",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "FlaxCLIPModel",
							    "FlaxCLIPPreTrainedModel",
							    "FlaxCLIPTextModel",
							    "FlaxCLIPTextPreTrainedModel",
							    "FlaxCLIPVisionModel",
							    "FlaxCLIPVisionPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_clip import (
							    CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    CLIPConfig,
							    CLIPOnnxConfig,
							    CLIPTextConfig,
							    CLIPVisionConfig,
							)
							from .processing_clip import CLIPProcessor
							from .tokenization_clip import CLIPTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_clip_fast import CLIPTokenizerFast

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clip import CLIPFeatureExtractor
														from .image_processing_clip import CLIPImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_clip import (
														    CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CLIPModel,
														    CLIPPreTrainedModel,
														    CLIPTextModel,
														    CLIPTextModelWithProjection,
														    CLIPVisionModel,
														    CLIPVisionModelWithProjection,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_clip import (
														    TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFCLIPModel,
														    TFCLIPPreTrainedModel,
														    TFCLIPTextModel,
														    TFCLIPVisionModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_clip import (
														    FlaxCLIPModel,
														    FlaxCLIPPreTrainedModel,
														    FlaxCLIPTextModel,
														    FlaxCLIPTextPreTrainedModel,
														    FlaxCLIPVisionModel,
														    FlaxCLIPVisionPreTrainedModel,
														)


else:
							import sys

							UpperCAmelCase__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
