


import argparse
import json
import os
import time
import zipfile

from get_ci_error_statistics import download_artifact, get_artifacts_links

from transformers import logging


a			:			List[Any]												=					logging.get_logger(__name__)


def 		lowercase_	(  _UpperCamelCase							,      _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = set()
			__lowercase			       = []

			def parse_line(_UpperCamelCase	):
						for line in fp:
									if isinstance(_UpperCamelCase							,      _UpperCamelCase	):
												__lowercase			       = line.decode('''UTF-8'''	)
									if "warnings summary (final)" in line:
												continue
									# This means we are outside the body of a warning
									elif not line.startswith(''' '''	):
												# process a single warning and move it to `selected_warnings`.
												if len(_UpperCamelCase	) > 0:
															__lowercase			       = '''\n'''.join(_UpperCamelCase	)
															# Only keep the warnings specified in `targets`
															if any(F': {x}: ' in warning for x in targets	):
																		selected_warnings.add(_UpperCamelCase	)
															buffer.clear()
												continue
									else:
												__lowercase			       = line.strip()
												buffer.append(_UpperCamelCase	)

			if from_gh:
						for filename in os.listdir(_UpperCamelCase	):
									__lowercase			       = os.path.join(_UpperCamelCase							,      _UpperCamelCase	)
									if not os.path.isdir(_UpperCamelCase	):
												# read the file
												if filename != "warnings.txt":
															continue
												with open(_UpperCamelCase	) as fp:
															parse_line(_UpperCamelCase	)
			else:
						try:
									with zipfile.ZipFile(_UpperCamelCase	) as z:
												for filename in z.namelist():
															if not os.path.isdir(_UpperCamelCase	):
																		# read the file
																		if filename != "warnings.txt":
																					continue
																		with z.open(_UpperCamelCase	) as fp:
																					parse_line(_UpperCamelCase	)
						except Exception:
									logger.warning(
									    F'{artifact_path} is either an invalid zip file or something else wrong. This file is skipped.'	)

			return selected_warnings


def 		lowercase_	(  _UpperCamelCase							,      _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = set()

			__lowercase			       = [os.path.join(_UpperCamelCase							,      _UpperCamelCase	) for p in os.listdir(_UpperCamelCase	) if (p.endswith('''.zip'''	) or from_gh)]
			for p in paths:
						selected_warnings.update(extract_warnings_from_single_artifact(_UpperCamelCase							,      _UpperCamelCase	)	)

			return selected_warnings


if __name__ == "__main__":


	def 		lowercase_	(  _UpperCamelCase	):


				'''simple docstring'''







				return values.split(''','''	)

	a			:			Any												=					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.''')
	# optional parameters
	parser.add_argument(
	    '''--targets''',
	    default='''DeprecationWarning,UserWarning,FutureWarning''',
	    type=list_str,
	    help='''Comma-separated list of target warning(s) which we want to extract.''',
	)
	parser.add_argument(
	    '''--from_gh''',
	    action='''store_true''',
	    help='''If running from a GitHub action workflow and collecting warnings from its artifacts.''',
	)

	a			:			str												=					parser.parse_args()

	a			:			Any												=					args.from_gh
	if from_gh:
		# The artifacts have to be downloaded using `actions/download-artifact@v3`
		pass
	else:
		os.makedirs(args.output_dir, exist_ok=True)

		# get download links
		a			:			Optional[int]												=					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)

		# download artifacts
		for idx, (name, url) in enumerate(artifacts.items()):
			print(name)
			print(url)
			print('''=''' * 80)
			download_artifact(name, url, args.output_dir, args.token)
			# Be gentle to GitHub
			time.sleep(1)

    # extract warnings from artifacts
	a			:			List[str]												=					extract_warnings(args.output_dir, args.targets)
	a			:			List[Any]												=					sorted(selected_warnings)
	with open(os.path.join(args.output_dir, '''selected_warnings.json'''), '''w''', encoding='''UTF-8''') as fp:
		json.dump(selected_warnings, fp, ensure_ascii=False, indent=4)






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


a			:			Optional[Any]												=					{
    '''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],
}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a			:			Optional[int]												=					['''LlamaTokenizer''']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a			:			Optional[int]												=					['''LlamaTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a			:			Any												=					[
	    '''LlamaForCausalLM''',
	    '''LlamaModel''',
	    '''LlamaPreTrainedModel''',
	    '''LlamaForSequenceClassification''',
	]


if TYPE_CHECKING:
	from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama import LlamaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama_fast import LlamaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
	import sys

	a			:			Dict												=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


