





import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / """utils"""))

from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


_UpperCAmelCase				:       Union[str, Any]	   =				get_tests_dir("""fixtures""")

class    lowerCAmelCase							(					unittest.TestCase			):
 def      A_	(      self  :      Dict	)			->	Tuple:
     # A mock response for an HTTP head request to emulate server down
     lowerCamelCase__    :      Optional[Any]					 =		mock.Mock()
     lowerCamelCase__    :      Dict					 =		500
     lowerCamelCase__    :      Any					 =		{}
     lowerCamelCase__    :      Any					 =		HTTPError
     lowerCamelCase__    :      int					 =		{}

     # Download this model to make sure it's in the cache.
     lowerCamelCase__    :      Any					 =		ViTImageProcessor.from_pretrained('hf-internal-testing/tiny-random-vit'	)
     # Under the mock environment we get a 500 error when trying to reach the model.
     with mock.patch('requests.Session.request'			,     return_value=UpperCAmelCase	) as mock_head:
         lowerCamelCase__    :      Tuple					 =		ViTImageProcessor.from_pretrained('hf-internal-testing/tiny-random-vit'	)
         # This check we did call the fake head request
         mock_head.assert_called()
 def      A_	(      self  :      Optional[int]	)			->	Tuple:
     # This test is for deprecated behavior and can be removed in v5
     lowerCamelCase__    :      Optional[Any]					 =		ViTImageProcessor.from_pretrained(
         'https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json'	)







 def      A_	(      self  :      str	)			->	Tuple:
     with self.assertRaises(UpperCAmelCase	):
         # config is in subfolder, the following should not work without specifying the subfolder
         lowerCamelCase__    :      List[Any]					 =		AutoImageProcessor.from_pretrained('hf-internal-testing/stable-diffusion-all-variants'	)

     lowerCamelCase__    :      List[str]					 =		AutoImageProcessor.from_pretrained(
         'hf-internal-testing/stable-diffusion-all-variants'			,     subfolder='feature_extractor'	)

     self.assertIsNotNone(UpperCAmelCase	)


@is_staging_test
class    lowerCAmelCase							(					unittest.TestCase			):
 @classmethod
 def      A_	(      cls  :      str	)			->	int:
     lowerCamelCase__    :      Union[str, Any]					 =		TOKEN
     HfFolder.save_token(UpperCAmelCase	)
 @classmethod
 def      A_	(      cls  :      Tuple	)			->	Dict:
     try:
         delete_repo(token=cls._token			,     repo_id='test-image-processor'	)
     except HTTPError:
         pass

     try:
         delete_repo(token=cls._token			,     repo_id='valid_org/test-image-processor-org'	)
     except HTTPError:
         pass

     try:
         delete_repo(token=cls._token			,     repo_id='test-dynamic-image-processor'	)
     except HTTPError:
         pass
 def      A_	(      self  :      Any	)			->	Dict:
     lowerCamelCase__    :      Dict					 =		ViTImageProcessor.from_pretrained(UpperCAmelCase	)
     image_processor.push_to_hub('test-image-processor'			,     use_auth_token=self._token	)

     lowerCamelCase__    :      Any					 =		ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""	)
     for k, v in image_processor.__dict__.items():
         self.assertEqual(UpperCAmelCase			,     getattr(UpperCAmelCase			,     UpperCAmelCase	)	)

     # Reset repo
     delete_repo(token=self._token			,     repo_id='test-image-processor'	)

     # Push to hub via save_pretrained
     with tempfile.TemporaryDirectory() as tmp_dir:
         image_processor.save_pretrained(
             UpperCAmelCase			,     repo_id='test-image-processor'			,     push_to_hub=UpperCAmelCase			,     use_auth_token=self._token	)

     lowerCamelCase__    :      Tuple					 =		ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""	)
     for k, v in image_processor.__dict__.items():
         self.assertEqual(UpperCAmelCase			,     getattr(UpperCAmelCase			,     UpperCAmelCase	)	)
 def      A_	(      self  :      List[Any]	)			->	Tuple:
     lowerCamelCase__    :      List[str]					 =		ViTImageProcessor.from_pretrained(UpperCAmelCase	)
     image_processor.push_to_hub('valid_org/test-image-processor'			,     use_auth_token=self._token	)

     lowerCamelCase__    :      List[str]					 =		ViTImageProcessor.from_pretrained('valid_org/test-image-processor'	)
     for k, v in image_processor.__dict__.items():
         self.assertEqual(UpperCAmelCase			,     getattr(UpperCAmelCase			,     UpperCAmelCase	)	)

     # Reset repo
     delete_repo(token=self._token			,     repo_id='valid_org/test-image-processor'	)

     # Push to hub via save_pretrained
     with tempfile.TemporaryDirectory() as tmp_dir:
         image_processor.save_pretrained(
             UpperCAmelCase			,     repo_id='valid_org/test-image-processor-org'			,     push_to_hub=UpperCAmelCase			,     use_auth_token=self._token	)

     lowerCamelCase__    :      Tuple					 =		ViTImageProcessor.from_pretrained('valid_org/test-image-processor-org'	)
     for k, v in image_processor.__dict__.items():
         self.assertEqual(UpperCAmelCase			,     getattr(UpperCAmelCase			,     UpperCAmelCase	)	)







 def      A_	(      self  :      List[str]	)			->	List[Any]:
     CustomImageProcessor.register_for_auto_class()
     lowerCamelCase__    :      Union[str, Any]					 =		CustomImageProcessor.from_pretrained(UpperCAmelCase	)

     image_processor.push_to_hub('test-dynamic-image-processor'			,     use_auth_token=self._token	)

     # This has added the proper auto_map field to the config
     self.assertDictEqual(
         image_processor.auto_map			,     {'AutoImageProcessor': 'custom_image_processing.CustomImageProcessor'}			,     )

     lowerCamelCase__    :      int					 =		AutoImageProcessor.from_pretrained(
         F"""{USER}/test-dynamic-image-processor"""			,     trust_remote_code=UpperCAmelCase	)
     # Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
     self.assertEqual(new_image_processor.__class__.__name__			,     'CustomImageProcessor'	)












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				:       Optional[int]	   =				logging.get_logger(__name__)


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase )			->     Dict:
    lowerCamelCase__    :      str					 =		set()
    lowerCamelCase__    :      Any					 =		[]

    def parse_line(_UpperCAmelCase ):
        for line in fp:
            if isinstance(_UpperCAmelCase						,	_UpperCAmelCase ):
                lowerCamelCase__    :      Any					 =		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:
                    lowerCamelCase__    :      str					 =		'\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:
                lowerCamelCase__    :      List[str]					 =		line.strip()
                buffer.append(_UpperCAmelCase )

    if from_gh:
        for filename in os.listdir(_UpperCAmelCase ):
            lowerCamelCase__    :      Dict					 =		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        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase )			->     Union[str, Any]:
    lowerCamelCase__    :      Tuple					 =		set()

    lowerCamelCase__    :      Optional[int]					 =		[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        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     Tuple:
        return values.split(',' )

    _UpperCAmelCase				:       List[str]	   =				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				:       Union[str, Any]	   =				parser.parse_args()

    _UpperCAmelCase				:       Dict	   =				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				:       Union[str, 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				:       Dict	   =				extract_warnings(args.output_dir, args.targets)
    _UpperCAmelCase				:       Optional[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)





