





"""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        __UpperCamelCase				(						unittest.TestCase						):






							def     __a   (   self      )	-> str:
								a      :		Dict	=				0






							def     __a   (   self      )	-> List[str]:
								a      :		List[str]	=				AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32"      )
								self.assertIsInstance(lowerCAmelCase__      ,					lowerCAmelCase__      )






							def     __a   (   self      )	-> Any:
								with tempfile.TemporaryDirectory() as tmpdirname:
									a      :		List[str]	=				Path(lowerCAmelCase__      ) / "preprocessor_config.json"
									a      :		Optional[Any]	=				Path(lowerCAmelCase__      ) / "config.json"
									json.dump(
									    {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}      ,					open(lowerCAmelCase__      ,					"w"      )      ,					)
									json.dump({"model_type": "clip"}      ,					open(lowerCAmelCase__      ,					"w"      )      )

									a      :		Dict	=				AutoImageProcessor.from_pretrained(lowerCAmelCase__      )
									self.assertIsInstance(lowerCAmelCase__      ,					lowerCAmelCase__      )






							def     __a   (   self      )	-> Optional[Any]:
								# Ensure we can load the image processor from the feature extractor config
								with tempfile.TemporaryDirectory() as tmpdirname:
									a      :		Union[str, Any]	=				Path(lowerCAmelCase__      ) / "preprocessor_config.json"
									a      :		str	=				Path(lowerCAmelCase__      ) / "config.json"
									json.dump(
									    {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}      ,					open(lowerCAmelCase__      ,					"w"      )      ,					)
									json.dump({"model_type": "clip"}      ,					open(lowerCAmelCase__      ,					"w"      )      )

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






							def     __a   (   self      )	-> Any:
								with tempfile.TemporaryDirectory() as tmpdirname:
									a      :		Optional[Any]	=				CLIPConfig()

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

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

									config_dict.pop("image_processor_type"      )
									a      :		Optional[int]	=				CLIPImageProcessor(**lowerCAmelCase__      )

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

									a      :		str	=				AutoImageProcessor.from_pretrained(lowerCAmelCase__      )

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

								self.assertIsInstance(lowerCAmelCase__      ,					lowerCAmelCase__      )






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

									a      :		List[Any]	=				AutoImageProcessor.from_pretrained(lowerCAmelCase__      )
									self.assertIsInstance(lowerCAmelCase__      ,					lowerCAmelCase__      )






							def     __a   (   self      )	-> Any:
								with self.assertRaisesRegex(
								    lowerCAmelCase__      ,					"clip-base is not a local folder and is not a valid model identifier"      ):
									a      :		Union[str, Any]	=				AutoImageProcessor.from_pretrained("clip-base"      )






							def     __a   (   self      )	-> Union[str, Any]:
								with self.assertRaisesRegex(
								    lowerCAmelCase__      ,					R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"      ):
									a      :		Union[str, Any]	=				AutoImageProcessor.from_pretrained(lowerCAmelCase__      ,					revision="aaaaaa"      )






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






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

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

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






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

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

										a      :		Optional[int]	=				CustomImageProcessor.from_pretrained(lowerCAmelCase__      )

									# 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(lowerCAmelCase__      )
										a      :		List[Any]	=				AutoImageProcessor.from_pretrained(lowerCAmelCase__      )
										self.assertIsInstance(lowerCAmelCase__      ,					lowerCAmelCase__      )

								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     __a   (   self      )	-> int:


								class        __UpperCamelCase				(						a__						):
															lowerCamelCase   :					Tuple      					=True

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

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




def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list					) ->int:






	'''simple docstring'''






	if not grid or not grid[0]:
		raise TypeError("The grid does not contain the appropriate information"					)

	for cell_n in range(1    ,       len(grid[0]					)					):
		grid[0][cell_n] += grid[0][cell_n - 1]
	a      :		Union[str, Any]	=				grid[0]

	for row_n in range(1    ,       len(_lowercase					)					):
		a      :		Optional[Any]	=				grid[row_n]
		a      :		Tuple	=				fill_row(_lowercase    ,       _lowercase					)
		a      :		List[Any]	=				grid[row_n]

	return grid[-1][-1]






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list    ,       _lowercase						:    list					) ->list:






	'''simple docstring'''






	current_row[0] += row_above[0]
	for cell_n in range(1    ,       len(_lowercase					)					):
		current_row[cell_n] += min(current_row[cell_n - 1]    ,       row_above[cell_n]					)

	return current_row


if __name__ == "__main__":
		import doctest

		doctest.testmod()


