



"""simple docstring"""






import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand


def     _lowercase       (						__snake_case			)		->     Optional[int]:
   return EnvironmentCommand()


def     _lowercase       (						__snake_case			)		->     str:
   return EnvironmentCommand(args.accelerate_config_file			)





class     A__     (						__lowercase							):




 '''simple docstring'''





 @staticmethod
 def 							_SCREAMING_SNAKE_CASE     (  _SCREAMING_SNAKE_CASE:	ArgumentParser)       -> Any:

    """simple docstring"""

    __lowerCAmelCase   :						Dict				= parser.add_parser("env")
    download_parser.set_defaults(func=_SCREAMING_SNAKE_CASE)
    download_parser.add_argument(
        "--accelerate-config_file" ,    default=_SCREAMING_SNAKE_CASE ,    help="The accelerate config file to use for the default values in the launching script." ,    )
    download_parser.set_defaults(func=_SCREAMING_SNAKE_CASE)

 def __init__(  self:	int ,    _SCREAMING_SNAKE_CASE:	List[str] ,    *_SCREAMING_SNAKE_CASE:	Any)       -> None:

    """simple docstring"""

    __lowerCAmelCase   :						Dict				= accelerate_config_file

 def 							_SCREAMING_SNAKE_CASE     (  self:	Tuple)       -> Optional[int]:

    """simple docstring"""

    __lowerCAmelCase   :						Any				= "not installed"
    if is_safetensors_available():
       import safetensors

       __lowerCAmelCase   :						Union[str, Any]				= safetensors.__version__
    elif importlib.util.find_spec("safetensors") is not None:
       import safetensors

       __lowerCAmelCase   :						Tuple				= F"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

    __lowerCAmelCase   :						Optional[int]				= "not installed"
    __lowerCAmelCase   :						Tuple				= "not found"
    if is_accelerate_available():
       import accelerate
       from accelerate.commands.config import default_config_file, load_config_from_file

       __lowerCAmelCase   :						List[Any]				= accelerate.__version__
       # Get the default from the config file.
       if self._accelerate_config_file is not None or os.path.isfile(_SCREAMING_SNAKE_CASE):
          __lowerCAmelCase   :						Union[str, Any]				= load_config_from_file(self._accelerate_config_file).to_dict()

       __lowerCAmelCase   :						Any				= (
           "\n".join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()])
           if isinstance(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
           else F"""\t{accelerate_config}"""
       )

    __lowerCAmelCase   :						Optional[int]				= "not installed"
    __lowerCAmelCase   :						Any				= "NA"
    if is_torch_available():
       import torch

       __lowerCAmelCase   :						List[Any]				= torch.__version__
       __lowerCAmelCase   :						List[Any]				= torch.cuda.is_available()

    __lowerCAmelCase   :						Any				= "not installed"
    __lowerCAmelCase   :						Union[str, Any]				= "NA"
    if is_tf_available():
       import tensorflow as tf

       __lowerCAmelCase   :						Union[str, Any]				= tf.__version__
       try:
          # deprecated in v2.1
          __lowerCAmelCase   :						Tuple				= tf.test.is_gpu_available()
       except AttributeError:
          # returns list of devices, convert to bool
          __lowerCAmelCase   :						str				= bool(tf.config.list_physical_devices("GPU"))

    __lowerCAmelCase   :						Any				= "not installed"
    __lowerCAmelCase   :						Optional[int]				= "not installed"
    __lowerCAmelCase   :						Union[str, Any]				= "not installed"
    __lowerCAmelCase   :						List[Any]				= "NA"
    if is_flax_available():
       import flax
       import jax
       import jaxlib

       __lowerCAmelCase   :						int				= flax.__version__
       __lowerCAmelCase   :						Any				= jax.__version__
       __lowerCAmelCase   :						int				= jaxlib.__version__
       __lowerCAmelCase   :						int				= jax.lib.xla_bridge.get_backend().platform

    __lowerCAmelCase   :						Dict				= {
        "`transformers` version": version,
        "Platform": platform.platform(),
        "Python version": platform.python_version(),
        "Huggingface_hub version": huggingface_hub.__version__,
        "Safetensors version": F"""{safetensors_version}""",
        "Accelerate version": F"""{accelerate_version}""",
        "Accelerate config": F"""{accelerate_config_str}""",
        "PyTorch version (GPU?)": F"""{pt_version} ({pt_cuda_available})""",
        "Tensorflow version (GPU?)": F"""{tf_version} ({tf_cuda_available})""",
        "Flax version (CPU?/GPU?/TPU?)": F"""{flax_version} ({jax_backend})""",
        "Jax version": F"""{jax_version}""",
        "JaxLib version": F"""{jaxlib_version}""",
        "Using GPU in script?": "<fill in>",
        "Using distributed or parallel set-up in script?": "<fill in>",
    }

    print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n")
    print(self.format_dict(_SCREAMING_SNAKE_CASE))

    return info







 @staticmethod
 def 							_SCREAMING_SNAKE_CASE     (  _SCREAMING_SNAKE_CASE:	Optional[int])       -> List[Any]:

    """simple docstring"""

    return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]) + "\n"




"""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


__snake_case							:     Tuple   =					logging.get_logger(__name__)


def     _lowercase       (						__snake_case      ,__snake_case			)		->     Dict:
			__lowerCAmelCase   :						Optional[Any]				= set()
			__lowerCAmelCase   :						List[Any]				= []

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

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

			__lowerCAmelCase   :						str				= [os.path.join(__snake_case      ,__snake_case			) for p in os.listdir(__snake_case			) if (p.endswith(".zip"			) or from_gh)]
			for p in paths:
						selected_warnings.update(extract_warnings_from_single_artifact(__snake_case      ,__snake_case			)			)

			return selected_warnings


if __name__ == "__main__":


	def     _lowercase       (						__snake_case			)		->     Optional[Any]:
				return values.split(","			)

	__snake_case							:     Optional[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.')
	# 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.',
	)

	__snake_case							:     Tuple   =					parser.parse_args()

	__snake_case							:     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
		__snake_case							:     str   =					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
	__snake_case							:     Tuple   =					extract_warnings(args.output_dir, args.targets)
	__snake_case							:     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)