


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
    from PIL import Image

    from transformers import (
        AutoProcessor,
        BertTokenizerFast,
        BlipImageProcessor,
        GPTaTokenizer,
        InstructBlipProcessor,
        PreTrainedTokenizerFast,
    )







@require_vision
class     _lowercase				(							unittest.TestCase):


       """simple docstring"""




       def 		lowerCAmelCase  (     self							:    Any ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						tempfile.mkdtemp()

             lowerCamelCase__	:       Optional[int]					=						BlipImageProcessor()
             lowerCamelCase__	:       Tuple					=						GPTaTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model" )
             lowerCamelCase__	:       Optional[Any]					=						BertTokenizerFast.from_pretrained("hf-internal-testing/tiny-random-bert" )

             lowerCamelCase__	:       List[str]					=						InstructBlipProcessor(__lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase )

             processor.save_pretrained(self.tmpdirname )





       def 		lowerCAmelCase  (     self							:    List[str]      ,   **__lowerCamelCase							:    Dict ):


             '''simple docstring'''



             return AutoProcessor.from_pretrained(self.tmpdirname      ,   **__lowerCamelCase ).tokenizer





       def 		lowerCAmelCase  (     self							:    Dict      ,   **__lowerCamelCase							:    Dict ):


             '''simple docstring'''



             return AutoProcessor.from_pretrained(self.tmpdirname      ,   **__lowerCamelCase ).image_processor





       def 		lowerCAmelCase  (     self							:    Optional[int]      ,   **__lowerCamelCase							:    int ):


             '''simple docstring'''



             return AutoProcessor.from_pretrained(self.tmpdirname      ,   **__lowerCamelCase ).qformer_tokenizer





       def 		lowerCAmelCase  (     self							:    Dict ):


             '''simple docstring'''



             shutil.rmtree(self.tmpdirname )





       def 		lowerCAmelCase  (     self							:    int ):


             '''simple docstring'''



             lowerCamelCase__	:       int					=						[np.random.randint(255      ,   size=(3, 30, 400)      ,   dtype=np.uinta )]

             lowerCamelCase__	:       Optional[int]					=						[Image.fromarray(np.moveaxis(__lowerCamelCase      ,   0      ,   -1 ) ) for x in image_inputs]

             return image_inputs





       def 		lowerCAmelCase  (     self							:    Union[str, Any] ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						InstructBlipProcessor(
                 tokenizer=self.get_tokenizer()      ,   image_processor=self.get_image_processor()      ,   qformer_tokenizer=self.get_qformer_tokenizer()      ,   )
             processor.save_pretrained(self.tmpdirname )

             lowerCamelCase__	:       str					=						self.get_tokenizer(bos_token="(BOS)"      ,   eos_token="(EOS)" )
             lowerCamelCase__	:       str					=						self.get_image_processor(do_normalize=__lowerCamelCase      ,   padding_value=1.0 )

             lowerCamelCase__	:       Union[str, Any]					=						InstructBlipProcessor.from_pretrained(
                 self.tmpdirname      ,   bos_token="(BOS)"      ,   eos_token="(EOS)"      ,   do_normalize=__lowerCamelCase      ,   padding_value=1.0 )

             self.assertEqual(processor.tokenizer.get_vocab()      ,   tokenizer_add_kwargs.get_vocab() )
             self.assertIsInstance(processor.tokenizer      ,   __lowerCamelCase )

             self.assertEqual(processor.image_processor.to_json_string()      ,   image_processor_add_kwargs.to_json_string() )
             self.assertIsInstance(processor.image_processor      ,   __lowerCamelCase )
             self.assertIsInstance(processor.qformer_tokenizer      ,   __lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    Dict ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						self.get_image_processor()
             lowerCamelCase__	:       str					=						self.get_tokenizer()
             lowerCamelCase__	:       Optional[int]					=						self.get_qformer_tokenizer()

             lowerCamelCase__	:       Dict					=						InstructBlipProcessor(
                 tokenizer=__lowerCamelCase      ,   image_processor=__lowerCamelCase      ,   qformer_tokenizer=__lowerCamelCase )

             lowerCamelCase__	:       Union[str, Any]					=						self.prepare_image_inputs()

             lowerCamelCase__	:       Union[str, Any]					=						image_processor(__lowerCamelCase      ,   return_tensors="np" )
             lowerCamelCase__	:       Optional[int]					=						processor(images=__lowerCamelCase      ,   return_tensors="np" )

             for key in input_feat_extract.keys():
                   self.assertAlmostEqual(input_feat_extract[key].sum()      ,   input_processor[key].sum()      ,   delta=1E-2 )





       def 		lowerCAmelCase  (     self							:    str ):


             '''simple docstring'''



             lowerCamelCase__	:       str					=						self.get_image_processor()
             lowerCamelCase__	:       Dict					=						self.get_tokenizer()
             lowerCamelCase__	:       Any					=						self.get_qformer_tokenizer()

             lowerCamelCase__	:       int					=						InstructBlipProcessor(
                 tokenizer=__lowerCamelCase      ,   image_processor=__lowerCamelCase      ,   qformer_tokenizer=__lowerCamelCase )

             lowerCamelCase__	:       str					=						"lower newer"

             lowerCamelCase__	:       Optional[int]					=						processor(text=__lowerCamelCase )

             lowerCamelCase__	:       Union[str, Any]					=						tokenizer(__lowerCamelCase      ,   return_token_type_ids=__lowerCamelCase )
             lowerCamelCase__	:       List[Any]					=						qformer_tokenizer(__lowerCamelCase      ,   return_token_type_ids=__lowerCamelCase )

             for key in encoded_tokens.keys():
                   self.assertListEqual(encoded_tokens[key]      ,   encoded_processor[key] )

             for key in encoded_tokens_qformer.keys():
                   self.assertListEqual(encoded_tokens_qformer[key]      ,   encoded_processor["qformer_" + key] )





       def 		lowerCAmelCase  (     self							:    Tuple ):


             '''simple docstring'''



             lowerCamelCase__	:       int					=						self.get_image_processor()
             lowerCamelCase__	:       Tuple					=						self.get_tokenizer()
             lowerCamelCase__	:       List[str]					=						self.get_qformer_tokenizer()

             lowerCamelCase__	:       Dict					=						InstructBlipProcessor(
                 tokenizer=__lowerCamelCase      ,   image_processor=__lowerCamelCase      ,   qformer_tokenizer=__lowerCamelCase )

             lowerCamelCase__	:       Dict					=						"lower newer"
             lowerCamelCase__	:       List[str]					=						self.prepare_image_inputs()

             lowerCamelCase__	:       List[str]					=						processor(text=__lowerCamelCase      ,   images=__lowerCamelCase )

             self.assertListEqual(
                 list(inputs.keys() )      ,   ["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]      ,   )

             # test if it raises when no input is passed
             with pytest.raises(__lowerCamelCase ):
                   processor()





       def 		lowerCAmelCase  (     self							:    str ):


             '''simple docstring'''



             lowerCamelCase__	:       Optional[Any]					=						self.get_image_processor()
             lowerCamelCase__	:       Optional[Any]					=						self.get_tokenizer()
             lowerCamelCase__	:       Optional[Any]					=						self.get_qformer_tokenizer()

             lowerCamelCase__	:       str					=						InstructBlipProcessor(
                 tokenizer=__lowerCamelCase      ,   image_processor=__lowerCamelCase      ,   qformer_tokenizer=__lowerCamelCase )

             lowerCamelCase__	:       Optional[Any]					=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

             lowerCamelCase__	:       int					=						processor.batch_decode(__lowerCamelCase )
             lowerCamelCase__	:       Tuple					=						tokenizer.batch_decode(__lowerCamelCase )

             self.assertListEqual(__lowerCamelCase      ,   __lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    int ):


             '''simple docstring'''



             lowerCamelCase__	:       Any					=						self.get_image_processor()
             lowerCamelCase__	:       Dict					=						self.get_tokenizer()
             lowerCamelCase__	:       Union[str, Any]					=						self.get_qformer_tokenizer()

             lowerCamelCase__	:       str					=						InstructBlipProcessor(
                 tokenizer=__lowerCamelCase      ,   image_processor=__lowerCamelCase      ,   qformer_tokenizer=__lowerCamelCase )

             lowerCamelCase__	:       Dict					=						"lower newer"
             lowerCamelCase__	:       Union[str, Any]					=						self.prepare_image_inputs()

             lowerCamelCase__	:       Any					=						processor(text=__lowerCamelCase      ,   images=__lowerCamelCase )

             self.assertListEqual(
                 list(inputs.keys() )      ,   ["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]      ,   )






import os
from datetime import datetime as dt

from github import Github


A   :					Union[str, Any]	=      [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "enhancement",
    "new pipeline/model",
    "new scheduler",
    "wip",
]

def    lowercase_	(	):

      """simple docstring"""




      lowerCamelCase__	:       Optional[int]					=						Github(os.environ["GITHUB_TOKEN"]		)
      lowerCamelCase__	:       str					=						g.get_repo("huggingface/diffusers"		)
      lowerCamelCase__	:       Optional[int]					=						repo.get_issues(state="open"		)

      for issue in open_issues:
            lowerCamelCase__	:       str					=						sorted(issue.get_comments()					,      key=lambda _A		: i.created_at					,      reverse=_A		)
            lowerCamelCase__	:       str					=						comments[0] if len(_A		) > 0 else None
            if (
                last_comment is not None
                and last_comment.user.login == "github-actions[bot]"
                and (dt.utcnow() - issue.updated_at).days > 7
                and (dt.utcnow() - issue.created_at).days >= 30
                and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()		)
            ):
                  # Closes the issue after 7 days of inactivity since the Stalebot notification.
                  issue.edit(state="closed"		)
            elif (
                "stale" in issue.get_labels()
                and last_comment is not None
                and last_comment.user.login != "github-actions[bot]"
            ):
                  # Opens the issue if someone other than Stalebot commented.
                  issue.edit(state="open"		)
                  issue.remove_from_labels("stale"		)
            elif (
                (dt.utcnow() - issue.updated_at).days > 23
                and (dt.utcnow() - issue.created_at).days >= 30
                and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()		)
            ):
                  # Post a Stalebot notification after 23 days of inactivity.
                  issue.create_comment(
                      "This issue has been automatically marked as stale because it has not had "
                      "recent activity. If you think this still needs to be addressed "
                      "please comment on this thread.\n\nPlease note that issues that do not follow the "
                      "[contributing guidelines](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md) "
                      "are likely to be ignored."		)
                  issue.add_to_labels("stale"		)


if __name__ == "__main__":
    main()


