'''simple docstring'''





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 			__A (					unittest.TestCase      ):



    def    _lowercase		(self       :       List[str]					):
         UpperCAmelCase_			       =  0



    def    _lowercase		(self       :       Tuple					):
         UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32"					)
         self.assertIsInstance(__a  ,     __a					)



    def    _lowercase		(self       :       str					):
         with tempfile.TemporaryDirectory() as tmpdirname:
              UpperCAmelCase_			       =  Path(__a					) / "preprocessor_config.json"
              UpperCAmelCase_			       =  Path(__a					) / "config.json"
              json.dump(
                  {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}  ,     open(__a  ,     "w"					)  ,     )
              json.dump({"model_type": "clip"}  ,     open(__a  ,     "w"					)					)

              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a					)
              self.assertIsInstance(__a  ,     __a					)



    def    _lowercase		(self       :       Dict					):
         # Ensure we can load the image processor from the feature extractor config
         with tempfile.TemporaryDirectory() as tmpdirname:
              UpperCAmelCase_			       =  Path(__a					) / "preprocessor_config.json"
              UpperCAmelCase_			       =  Path(__a					) / "config.json"
              json.dump(
                  {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}  ,     open(__a  ,     "w"					)  ,     )
              json.dump({"model_type": "clip"}  ,     open(__a  ,     "w"					)					)

              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a					)
              self.assertIsInstance(__a  ,     __a					)



    def    _lowercase		(self       :       List[str]					):
         with tempfile.TemporaryDirectory() as tmpdirname:
              UpperCAmelCase_			       =  CLIPConfig()

              # Create a dummy config file with image_proceesor_type
              UpperCAmelCase_			       =  Path(__a					) / "preprocessor_config.json"
              UpperCAmelCase_			       =  Path(__a					) / "config.json"
              json.dump(
                  {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}  ,     open(__a  ,     "w"					)  ,     )
              json.dump({"model_type": "clip"}  ,     open(__a  ,     "w"					)					)

              # remove image_processor_type to make sure config.json alone is enough to load image processor locally
              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a					).to_dict()

              config_dict.pop("image_processor_type"					)
              UpperCAmelCase_			       =  CLIPImageProcessor(**__a					)

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

              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a					)

              # make sure private variable is not incorrectly saved
              UpperCAmelCase_			       =  json.loads(config.to_json_string()					)
              self.assertTrue("_processor_class" not in dict_as_saved					)

         self.assertIsInstance(__a  ,     __a					)



    def    _lowercase		(self       :       int					):
         with tempfile.TemporaryDirectory() as tmpdirname:
              UpperCAmelCase_			       =  Path(__a					) / "preprocessor_config.json"
              json.dump(
                  {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}  ,     open(__a  ,     "w"					)  ,     )

              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a					)
              self.assertIsInstance(__a  ,     __a					)



    def    _lowercase		(self       :       Tuple					):
         with self.assertRaisesRegex(
             __a  ,     "clip-base is not a local folder and is not a valid model identifier"					):
              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained("clip-base"					)



    def    _lowercase		(self       :       Optional[int]					):
         with self.assertRaisesRegex(
             __a  ,     r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"					):
              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a  ,     revision="aaaaaa"					)



    def    _lowercase		(self       :       Union[str, Any]					):
         with self.assertRaisesRegex(
             __a  ,     "hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."  ,     ):
              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained("hf-internal-testing/config-no-model"					)



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

         UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(
             "hf-internal-testing/test_dynamic_image_processor"  ,     trust_remote_code=__a					)
         self.assertEqual(image_processor.__class__.__name__  ,     "NewImageProcessor"					)

         # Test image processor can be reloaded.
         with tempfile.TemporaryDirectory() as tmp_dir:
              image_processor.save_pretrained(__a					)
              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a  ,     trust_remote_code=__a					)
         self.assertEqual(reloaded_image_processor.__class__.__name__  ,     "NewImageProcessor"					)



    def    _lowercase		(self       :       Optional[int]					):
         try:
              AutoConfig.register("custom"  ,     __a					)
              AutoImageProcessor.register(__a  ,     __a					)
              # Trying to register something existing in the Transformers library will raise an error
              with self.assertRaises(__a					):
                   AutoImageProcessor.register(__a  ,     __a					)

              with tempfile.TemporaryDirectory() as tmpdirname:
                   UpperCAmelCase_			       =  Path(__a					) / "preprocessor_config.json"
                   UpperCAmelCase_			       =  Path(__a					) / "config.json"
                   json.dump(
                       {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}  ,     open(__a  ,     "w"					)  ,     )
                   json.dump({"model_type": "clip"}  ,     open(__a  ,     "w"					)					)

                   UpperCAmelCase_			       =  CustomImageProcessor.from_pretrained(__a					)

              # 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(__a					)
                   UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(__a					)
                   self.assertIsInstance(__a  ,     __a					)

         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    _lowercase		(self       :       Optional[int]					):




         class 			__A (					UpperCamelCase__      ):
             a__			:		str			  =    True

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

              # If remote is enabled, we load from the Hub
              UpperCAmelCase_			       =  AutoImageProcessor.from_pretrained(
                  "hf-internal-testing/test_dynamic_image_processor"  ,     trust_remote_code=__a					)
              self.assertEqual(image_processor.__class__.__name__  ,     "NewImageProcessor"					)
              self.assertTrue(not hasattr(__a  ,     "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]








'''simple docstring'''
from ...utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_torch_available,
    is_transformers_available,
)


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
					from .multicontrolnet import MultiControlNetModel
					from .pipeline_controlnet import StableDiffusionControlNetPipeline
					from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
					from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
					from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline


