'''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 					__magic_name__		(					unittest.TestCase):







   def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
          lowercase_      :    int       		= 0







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
          lowercase_      :    int       		= AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""					)
          self.assertIsInstance(lowercase_       ,    lowercase_					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):

          with tempfile.TemporaryDirectory() as tmpdirname:
                 lowercase_      :    Optional[Any]       		= Path(lowercase_					) / """preprocessor_config.json"""
                 lowercase_      :    Optional[int]       		= Path(lowercase_					) / """config.json"""
                 json.dump(
                     {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}       ,    open(lowercase_       ,    """w"""					)       ,    )
                 json.dump({"""model_type""": """clip"""}       ,    open(lowercase_       ,    """w"""					)					)

                 lowercase_      :    Tuple       		= AutoImageProcessor.from_pretrained(lowercase_					)
                 self.assertIsInstance(lowercase_       ,    lowercase_					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):

          with tempfile.TemporaryDirectory() as tmpdirname:
                 lowercase_      :    Tuple       		= Path(lowercase_					) / """preprocessor_config.json"""
                 lowercase_      :    Union[str, Any]       		= Path(lowercase_					) / """config.json"""
                 json.dump(
                     {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}       ,    open(lowercase_       ,    """w"""					)       ,    )
                 json.dump({"""model_type""": """clip"""}       ,    open(lowercase_       ,    """w"""					)					)

                 lowercase_      :    int       		= AutoImageProcessor.from_pretrained(lowercase_					)
                 self.assertIsInstance(lowercase_       ,    lowercase_					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):

          with tempfile.TemporaryDirectory() as tmpdirname:
                 lowercase_      :    Tuple       		= CLIPConfig()

                 # Create a dummy config file with image_proceesor_type
                 lowercase_      :    Union[str, Any]       		= Path(lowercase_					) / """preprocessor_config.json"""
                 lowercase_      :    Optional[int]       		= Path(lowercase_					) / """config.json"""
                 json.dump(
                     {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}       ,    open(lowercase_       ,    """w"""					)       ,    )
                 json.dump({"""model_type""": """clip"""}       ,    open(lowercase_       ,    """w"""					)					)

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

                 config_dict.pop("""image_processor_type"""					)
                 lowercase_      :    List[Any]       		= CLIPImageProcessor(**lowercase_					)

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

                 lowercase_      :    Optional[Any]       		= AutoImageProcessor.from_pretrained(lowercase_					)

                 # make sure private variable is not incorrectly saved
                 lowercase_      :    Optional[int]       		= json.loads(config.to_json_string()					)
                 self.assertTrue("""_processor_class""" not in dict_as_saved					)

          self.assertIsInstance(lowercase_       ,    lowercase_					)







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

          with tempfile.TemporaryDirectory() as tmpdirname:
                 lowercase_      :    Optional[int]       		= Path(lowercase_					) / """preprocessor_config.json"""
                 json.dump(
                     {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}       ,    open(lowercase_       ,    """w"""					)       ,    )

                 lowercase_      :    Any       		= AutoImageProcessor.from_pretrained(lowercase_					)
                 self.assertIsInstance(lowercase_       ,    lowercase_					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						str					):

          with self.assertRaisesRegex(
              lowercase_       ,    """clip-base is not a local folder and is not a valid model identifier"""					):
                 lowercase_      :    Optional[Any]       		= AutoImageProcessor.from_pretrained("""clip-base"""					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):

          with self.assertRaisesRegex(
              lowercase_       ,    r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""					):
                 lowercase_      :    int       		= AutoImageProcessor.from_pretrained(lowercase_       ,    revision="""aaaaaa"""					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple					):

          with self.assertRaisesRegex(
              lowercase_       ,    """hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""       ,    ):
                 lowercase_      :    str       		= AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""					)







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

          with self.assertRaises(lowercase_					):
                 lowercase_      :    Tuple       		= AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""					)
          # If remote code is disabled, we can't load this config.
          with self.assertRaises(lowercase_					):
                 lowercase_      :    List[str]       		= AutoImageProcessor.from_pretrained(
                     """hf-internal-testing/test_dynamic_image_processor"""       ,    trust_remote_code=lowercase_					)

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

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







   def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):

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

                 with tempfile.TemporaryDirectory() as tmpdirname:
                        lowercase_      :    List[Any]       		= Path(lowercase_					) / """preprocessor_config.json"""
                        lowercase_      :    Optional[Any]       		= Path(lowercase_					) / """config.json"""
                        json.dump(
                            {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}       ,    open(lowercase_       ,    """w"""					)       ,    )
                        json.dump({"""model_type""": """clip"""}       ,    open(lowercase_       ,    """w"""					)					)

                        lowercase_      :    Optional[int]       		= CustomImageProcessor.from_pretrained(lowercase_					)

                 # 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(lowercase_					)
                        lowercase_      :    Any       		= AutoImageProcessor.from_pretrained(lowercase_					)
                        self.assertIsInstance(lowercase_       ,    lowercase_					)

          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 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):





          class 					__magic_name__		(					_UpperCAmelCase):
             UpperCamelCase__       = True

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

                 # If remote is enabled, we load from the Hub
                 lowercase_      :    Optional[int]       		= AutoImageProcessor.from_pretrained(
                     """hf-internal-testing/test_dynamic_image_processor"""       ,    trust_remote_code=lowercase_					)
                 self.assertEqual(image_processor.__class__.__name__       ,    """NewImageProcessor"""					)
                 self.assertTrue(not hasattr(lowercase_       ,    """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 typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_lowercase		:				Optional[Any]	       =		{
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase		:				Any	       =		[
						    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SwiftFormerForImageClassification",
						    "SwiftFormerModel",
						    "SwiftFormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_swiftformer import (
						    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SwiftFormerConfig,
						    SwiftFormerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_swiftformer import (
												    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SwiftFormerForImageClassification,
												    SwiftFormerModel,
												    SwiftFormerPreTrainedModel,
												)

else:
						import sys

						_lowercase		:				Optional[int]	       =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





