




import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


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

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402






class  _lowerCAmelCase     (  unittest.TestCase	):

      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Any		       =     0

      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Union[str, Any]		       =     AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''		)
        self.assertIsInstance(__UpperCAmelCase      ,				__UpperCAmelCase		)

      def 	__magic_name__(   self		):
        with tempfile.TemporaryDirectory() as tmpdirname:
          lowerCAmelCase__				:  Tuple		       =     Path(__UpperCAmelCase		) / '''preprocessor_config.json'''
          lowerCAmelCase__				:  List[str]		       =     Path(__UpperCAmelCase		) / '''config.json'''
          json.dump(
              {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)      ,				)
          json.dump({'''model_type''': '''clip'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)		)

          lowerCAmelCase__				:  int		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase		)
          self.assertIsInstance(__UpperCAmelCase      ,				__UpperCAmelCase		)

      def 	__magic_name__(   self		):
        # Ensure we can load the image processor from the feature extractor config
        with tempfile.TemporaryDirectory() as tmpdirname:
          lowerCAmelCase__				:  List[Any]		       =     Path(__UpperCAmelCase		) / '''preprocessor_config.json'''
          lowerCAmelCase__				:  Dict		       =     Path(__UpperCAmelCase		) / '''config.json'''
          json.dump(
              {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)      ,				)
          json.dump({'''model_type''': '''clip'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)		)

          lowerCAmelCase__				:  Optional[int]		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase		)
          self.assertIsInstance(__UpperCAmelCase      ,				__UpperCAmelCase		)

      def 	__magic_name__(   self		):
        with tempfile.TemporaryDirectory() as tmpdirname:
          lowerCAmelCase__				:  Union[str, Any]		       =     CLIPConfig()

          # Create a dummy config file with image_proceesor_type
          lowerCAmelCase__				:  List[Any]		       =     Path(__UpperCAmelCase		) / '''preprocessor_config.json'''
          lowerCAmelCase__				:  List[str]		       =     Path(__UpperCAmelCase		) / '''config.json'''
          json.dump(
              {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)      ,				)
          json.dump({'''model_type''': '''clip'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)		)

          # remove image_processor_type to make sure config.json alone is enough to load image processor locally
          lowerCAmelCase__				:  List[Any]		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase		).to_dict()

          config_dict.pop('''image_processor_type'''		)
          lowerCAmelCase__				:  int		       =     CLIPImageProcessor(**__UpperCAmelCase		)

          # save in new folder
          model_config.save_pretrained(__UpperCAmelCase		)
          config.save_pretrained(__UpperCAmelCase		)

          lowerCAmelCase__				:  Dict		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase		)

          # make sure private variable is not incorrectly saved
          lowerCAmelCase__				:  int		       =     json.loads(config.to_json_string()		)
          self.assertTrue('''_processor_class''' not in dict_as_saved		)

        self.assertIsInstance(__UpperCAmelCase      ,				__UpperCAmelCase		)

      def 	__magic_name__(   self		):
        with tempfile.TemporaryDirectory() as tmpdirname:
          lowerCAmelCase__				:  List[str]		       =     Path(__UpperCAmelCase		) / '''preprocessor_config.json'''
          json.dump(
              {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)      ,				)

          lowerCAmelCase__				:  Optional[Any]		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase		)
          self.assertIsInstance(__UpperCAmelCase      ,				__UpperCAmelCase		)

      def 	__magic_name__(   self		):
        with self.assertRaisesRegex(
            __UpperCAmelCase      ,				'''clip-base is not a local folder and is not a valid model identifier'''		):
          lowerCAmelCase__				:  Optional[Any]		       =     AutoImageProcessor.from_pretrained('''clip-base'''		)

      def 	__magic_name__(   self		):
        with self.assertRaisesRegex(
            __UpperCAmelCase      ,				R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''		):
          lowerCAmelCase__				:  Optional[int]		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase      ,				revision='''aaaaaa'''		)

      def 	__magic_name__(   self		):
        with self.assertRaisesRegex(
            __UpperCAmelCase      ,				'''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''      ,				):
          lowerCAmelCase__				:  Optional[Any]		       =     AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''		)

      def 	__magic_name__(   self		):
        # If remote code is not set, we will time out when asking whether to load the model.
        with self.assertRaises(__UpperCAmelCase		):
          lowerCAmelCase__				:  List[str]		       =     AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''		)
        # If remote code is disabled, we can't load this config.
        with self.assertRaises(__UpperCAmelCase		):
          lowerCAmelCase__				:  Any		       =     AutoImageProcessor.from_pretrained(
              '''hf-internal-testing/test_dynamic_image_processor'''      ,				trust_remote_code=__UpperCAmelCase		)

        lowerCAmelCase__				:  Optional[int]		       =     AutoImageProcessor.from_pretrained(
            '''hf-internal-testing/test_dynamic_image_processor'''      ,				trust_remote_code=__UpperCAmelCase		)
        self.assertEqual(image_processor.__class__.__name__      ,				'''NewImageProcessor'''		)

        # Test image processor can be reloaded.
        with tempfile.TemporaryDirectory() as tmp_dir:
          image_processor.save_pretrained(__UpperCAmelCase		)
          lowerCAmelCase__				:  Union[str, Any]		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase      ,				trust_remote_code=__UpperCAmelCase		)
        self.assertEqual(reloaded_image_processor.__class__.__name__      ,				'''NewImageProcessor'''		)

      def 	__magic_name__(   self		):
        try:
          AutoConfig.register('''custom'''      ,				__UpperCAmelCase		)
          AutoImageProcessor.register(__UpperCAmelCase      ,				__UpperCAmelCase		)
          # Trying to register something existing in the Transformers library will raise an error
          with self.assertRaises(__UpperCAmelCase		):
            AutoImageProcessor.register(__UpperCAmelCase      ,				__UpperCAmelCase		)

          with tempfile.TemporaryDirectory() as tmpdirname:
            lowerCAmelCase__				:  str		       =     Path(__UpperCAmelCase		) / '''preprocessor_config.json'''
            lowerCAmelCase__				:  int		       =     Path(__UpperCAmelCase		) / '''config.json'''
            json.dump(
                {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)      ,				)
            json.dump({'''model_type''': '''clip'''}      ,				open(__UpperCAmelCase      ,				'''w'''		)		)

            lowerCAmelCase__				:  Optional[Any]		       =     CustomImageProcessor.from_pretrained(__UpperCAmelCase		)

          # Now that the config is registered, it can be used as any other config with the auto-API
          with tempfile.TemporaryDirectory() as tmp_dir:
            image_processor.save_pretrained(__UpperCAmelCase		)
            lowerCAmelCase__				:  Any		       =     AutoImageProcessor.from_pretrained(__UpperCAmelCase		)
            self.assertIsInstance(__UpperCAmelCase      ,				__UpperCAmelCase		)

        finally:
          if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
          if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
            del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]







      def 	__magic_name__(   self		):






        class  _lowerCAmelCase     (  _lowercase	):
              A__		     =		True

        try:
          AutoConfig.register('''custom'''      ,				__UpperCAmelCase		)
          AutoImageProcessor.register(__UpperCAmelCase      ,				__UpperCAmelCase		)
          # If remote code is not set, the default is to use local
          lowerCAmelCase__				:  Tuple		       =     AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''		)
          self.assertEqual(image_processor.__class__.__name__      ,				'''NewImageProcessor'''		)
          self.assertTrue(image_processor.is_local		)

          # If remote code is disabled, we load the local one.
          lowerCAmelCase__				:  List[str]		       =     AutoImageProcessor.from_pretrained(
              '''hf-internal-testing/test_dynamic_image_processor'''      ,				trust_remote_code=__UpperCAmelCase		)
          self.assertEqual(image_processor.__class__.__name__      ,				'''NewImageProcessor'''		)
          self.assertTrue(image_processor.is_local		)

          # If remote is enabled, we load from the Hub
          lowerCAmelCase__				:  str		       =     AutoImageProcessor.from_pretrained(
              '''hf-internal-testing/test_dynamic_image_processor'''      ,				trust_remote_code=__UpperCAmelCase		)
          self.assertEqual(image_processor.__class__.__name__      ,				'''NewImageProcessor'''		)
          self.assertTrue(not hasattr(__UpperCAmelCase      ,				'''is_local'''		)		)

        finally:
          if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
          if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
            del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]







from collections.abc import Callable






class  _lowerCAmelCase     :

      def __init__(   self      ,				__UpperCAmelCase = None		):
        # Stores actual heap items.
        lowerCAmelCase__				:  list		       =     []
        # Stores indexes of each item for supporting updates and deletion.
        lowerCAmelCase__				:  dict		       =     {}
        # Stores current size of heap.
        lowerCAmelCase__				:  Any		       =     0
        # Stores function used to evaluate the score of an item on which basis ordering
        # will be done.
        lowerCAmelCase__				:  Union[str, Any]		       =     key or (lambda __UpperCAmelCase		: x)

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        return int((i - 1) / 2		) if i > 0 else None

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Optional[Any]		       =     int(2 * i + 1		)
        return left if 0 < left < self.size else None

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  List[str]		       =     int(2 * i + 2		)
        return right if 0 < right < self.size else None

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase		):
        lowerCAmelCase__       ,			lowerCAmelCase__				:  List[str]		       =     (
            self.pos_map[self.arr[j][0]],
            self.pos_map[self.arr[i][0]],
        )
        # Then swap the items in the list.
        lowerCAmelCase__       ,			lowerCAmelCase__				:  Any		       =     self.arr[j], self.arr[i]

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase		):
        return self.arr[i][1] < self.arr[j][1]

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Optional[int]		       =     self._left(__UpperCAmelCase		)
        lowerCAmelCase__				:  Any		       =     self._right(__UpperCAmelCase		)
        lowerCAmelCase__				:  str		       =     i

        if left is not None and not self._cmp(__UpperCAmelCase      ,				__UpperCAmelCase		):
          lowerCAmelCase__				:  Dict		       =     left
        if right is not None and not self._cmp(__UpperCAmelCase      ,				__UpperCAmelCase		):
          lowerCAmelCase__				:  List[str]		       =     right

        return valid_parent

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Tuple		       =     self._parent(__UpperCAmelCase		)
        while parent is not None and not self._cmp(__UpperCAmelCase      ,				__UpperCAmelCase		):
          self._swap(__UpperCAmelCase      ,				__UpperCAmelCase		)
          lowerCAmelCase__       ,			lowerCAmelCase__				:  Dict		       =     parent, self._parent(__UpperCAmelCase		)

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  str		       =     self._get_valid_parent(__UpperCAmelCase		)
        while valid_parent != index:
          self._swap(__UpperCAmelCase      ,				__UpperCAmelCase		)
          lowerCAmelCase__       ,			lowerCAmelCase__				:  List[Any]		       =     valid_parent, self._get_valid_parent(__UpperCAmelCase		)

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase		):
        if item not in self.pos_map:
          return
        lowerCAmelCase__				:  Tuple		       =     self.pos_map[item]
        lowerCAmelCase__				:  Any		       =     [item, self.key(__UpperCAmelCase		)]
        # Make sure heap is right in both up and down direction.
        # Ideally only one of them will make any change.
        self._heapify_up(__UpperCAmelCase		)
        self._heapify_down(__UpperCAmelCase		)

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        if item not in self.pos_map:
          return
        lowerCAmelCase__				:  Tuple		       =     self.pos_map[item]
        del self.pos_map[item]
        lowerCAmelCase__				:  Tuple		       =     self.arr[self.size - 1]
        lowerCAmelCase__				:  int		       =     index
        self.size -= 1
        # Make sure heap is right in both up and down direction. Ideally only one
        # of them will make any change- so no performance loss in calling both.
        if self.size > index:
          self._heapify_up(__UpperCAmelCase		)
          self._heapify_down(__UpperCAmelCase		)

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Optional[int]		       =     len(self.arr		)
        if arr_len == self.size:
          self.arr.append([item, self.key(__UpperCAmelCase		)]		)
        else:
          lowerCAmelCase__				:  str		       =     [item, self.key(__UpperCAmelCase		)]
        lowerCAmelCase__				:  Optional[Any]		       =     self.size
        self.size += 1
        self._heapify_up(self.size - 1		)

      def 	__magic_name__(   self		):
        return self.arr[0] if self.size else None







      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  int		       =     self.get_top()
        if top_item_tuple:
          self.delete_item(top_item_tuple[0]		)
        return top_item_tuple



def      __lowerCAmelCase			(					)     ->	None:
  pass


if __name__ == "__main__":
     import doctest

     doctest.testmod()

