



'''simple docstring'''






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


UpperCamelCase__:     Tuple										=    logging.get_logger(__name__)


def 				snake_case_  (      _lowerCAmelCase						:		str     ,   _lowerCAmelCase						:		Tuple						)   ->     Union[str, Any]:
							UpperCAmelCase				: Dict											=	set()
							UpperCAmelCase				: Optional[int]											=	[]

							def parse_line(_lowerCAmelCase						:		Union[str, Any]						):
														for line in fp:
																					if isinstance(_lowerCAmelCase     ,   _lowerCAmelCase						):
																												UpperCAmelCase				: Dict											=	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(_lowerCAmelCase						) > 0:
																																			UpperCAmelCase				: Tuple											=	"\n".join(_lowerCAmelCase						)
																																			# Only keep the warnings specified in `targets`
																																			if any(f""": {x}: """ in warning for x in targets						):
																																										selected_warnings.add(_lowerCAmelCase						)
																																			buffer.clear()
																												continue
																					else:
																												UpperCAmelCase				: Union[str, Any]											=	line.strip()
																												buffer.append(_lowerCAmelCase						)

							if from_gh:
														for filename in os.listdir(_lowerCAmelCase						):
																					UpperCAmelCase				: Optional[Any]											=	os.path.join(_lowerCAmelCase     ,   _lowerCAmelCase						)
																					if not os.path.isdir(_lowerCAmelCase						):
																												# read the file
																												if filename != "warnings.txt":
																																			continue
																												with open(_lowerCAmelCase						) as fp:
																																			parse_line(_lowerCAmelCase						)
							else:
														try:
																					with zipfile.ZipFile(_lowerCAmelCase						) as z:
																												for filename in z.namelist():
																																			if not os.path.isdir(_lowerCAmelCase						):
																																										# read the file
																																										if filename != "warnings.txt":
																																																	continue
																																										with z.open(_lowerCAmelCase						) as fp:
																																																	parse_line(_lowerCAmelCase						)
														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 				snake_case_  (      _lowerCAmelCase						:		int     ,   _lowerCAmelCase						:		Dict						)   ->     List[str]:
							UpperCAmelCase				: Tuple											=	set()

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

							return selected_warnings


if __name__ == "__main__":


			def 				snake_case_  (      _lowerCAmelCase						:		Optional[Any]						)   ->     Dict:
										return values.split(''','''						)

			UpperCamelCase__:     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.",
			)

			UpperCamelCase__:     Any										=    parser.parse_args()

			UpperCamelCase__:     Optional[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
						UpperCamelCase__:     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)

						# 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
			UpperCamelCase__:     str										=    extract_warnings(args.output_dir, args.targets)
			UpperCamelCase__:     List[str]										=    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)










'''simple docstring'''






import math

import tensorflow as tf
from packaging import version


def 				snake_case_  (      _lowerCAmelCase						:		List[str]						)   ->     Dict:
							UpperCAmelCase				: Tuple											=	tf.convert_to_tensor(_lowerCAmelCase						)
							UpperCAmelCase				: Dict											=	0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0						)     ,   x.dtype						)						))

							return x * cdf


def 				snake_case_  (      _lowerCAmelCase						:		int						)   ->     List[Any]:
							UpperCAmelCase				: str											=	tf.convert_to_tensor(_lowerCAmelCase						)
							UpperCAmelCase				: Union[str, Any]											=	tf.cast(math.pi     ,   x.dtype						)
							UpperCAmelCase				: Tuple											=	tf.cast(0.0_4_4_7_1_5     ,   x.dtype						)
							UpperCAmelCase				: List[Any]											=	0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi						) * (x + coeff * tf.pow(_lowerCAmelCase     ,   3						))						))

							return x * cdf


def 				snake_case_  (      _lowerCAmelCase						:		Optional[Any]						)   ->     Any:
							UpperCAmelCase				: List[Any]											=	tf.convert_to_tensor(_lowerCAmelCase						)

							return x * tf.tanh(tf.math.softplus(_lowerCAmelCase						)						)


def 				snake_case_  (      _lowerCAmelCase						:		str						)   ->     Tuple:
							UpperCAmelCase				: Union[str, Any]											=	tf.convert_to_tensor(_lowerCAmelCase						)
							UpperCAmelCase				: Union[str, Any]											=	tf.cast(0.0_4_4_7_1_5     ,   x.dtype						)
							UpperCAmelCase				: Tuple											=	tf.cast(0.7_9_7_8_8_4_5_6_0_8     ,   x.dtype						)

							return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)						))


def 				snake_case_  (      _lowerCAmelCase						:		Optional[Any]						)   ->     Optional[int]:
							UpperCAmelCase				: str											=	tf.convert_to_tensor(_lowerCAmelCase						)
							UpperCAmelCase				: Optional[int]											=	tf.cast(1.7_0_2     ,   x.dtype						)
							return x * tf.math.sigmoid(coeff * x						)


def 				snake_case_  (      _lowerCAmelCase						:		Any						)   ->     Any:
							return tf.clip_by_value(_gelu(_lowerCAmelCase						)     ,   -10     ,   10						)


def 				snake_case_  (      _lowerCAmelCase						:		Dict     ,   _lowerCAmelCase						:		Optional[Any]=-1						)   ->     Union[str, Any]:
							UpperCAmelCase							,	UpperCAmelCase				: Optional[Any]											=	tf.split(_lowerCAmelCase     ,   2     ,   axis=_lowerCAmelCase						)
							return a * tf.math.sigmoid(_lowerCAmelCase						)


if version.parse(tf.version.VERSION) >= version.parse("2.4"):


						def 				snake_case_  (      _lowerCAmelCase						:		Tuple						)   ->     Any:
													return tf.keras.activations.gelu(_lowerCAmelCase     ,   approximate=_lowerCAmelCase						)

						UpperCamelCase__:     List[Any]										=    tf.keras.activations.gelu




						UpperCamelCase__:     List[Any]										=    approximate_gelu_wrap
else:
						UpperCamelCase__:     List[str]										=    _gelu
						UpperCamelCase__:     Tuple										=    _gelu_new


UpperCamelCase__:     List[Any]										=    {
    "gelu": gelu,
    "gelu_10": gelu_aa,
    "gelu_fast": gelu_fast,
    "gelu_new": gelu_new,
    "glu": glu,
    "mish": mish,
    "quick_gelu": quick_gelu,
    "relu": tf.keras.activations.relu,
    "sigmoid": tf.keras.activations.sigmoid,
    "silu": tf.keras.activations.swish,
    "swish": tf.keras.activations.swish,
    "tanh": tf.keras.activations.tanh,
}




def 				snake_case_  (      _lowerCAmelCase						:		Dict						)   ->     List[Any]:
							if activation_string in ACTaFN:
														return ACTaFN[activation_string]
							else:
														raise KeyError(f"""function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()						)}"""						)





