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        lowercase_   (					unittest.TestCase		):



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Dict    =   0



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



							def 	UpperCamelCase	(						self    ):
													with tempfile.TemporaryDirectory() as tmpdirname:
																			_snake_case						:					Tuple    =   Path(lowercase_    ) / "preprocessor_config.json"
																			_snake_case						:					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"    )    )

																			_snake_case						:					Optional[int]    =   AutoImageProcessor.from_pretrained(lowercase_    )
																			self.assertIsInstance(lowercase_				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													# Ensure we can load the image processor from the feature extractor config
													with tempfile.TemporaryDirectory() as tmpdirname:
																			_snake_case						:					str    =   Path(lowercase_    ) / "preprocessor_config.json"
																			_snake_case						:					List[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"    )    )

																			_snake_case						:					Optional[int]    =   AutoImageProcessor.from_pretrained(lowercase_    )
																			self.assertIsInstance(lowercase_				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													with tempfile.TemporaryDirectory() as tmpdirname:
																			_snake_case						:					int    =   CLIPConfig()

																			# Create a dummy config file with image_proceesor_type
																			_snake_case						:					Optional[Any]    =   Path(lowercase_    ) / "preprocessor_config.json"
																			_snake_case						:					List[str]    =   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
																			_snake_case						:					Union[str, Any]    =   AutoImageProcessor.from_pretrained(lowercase_    ).to_dict()

																			config_dict.pop("image_processor_type"    )
																			_snake_case						:					Union[str, Any]    =   CLIPImageProcessor(**lowercase_    )

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

																			_snake_case						:					Tuple    =   AutoImageProcessor.from_pretrained(lowercase_    )

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

													self.assertIsInstance(lowercase_				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													with tempfile.TemporaryDirectory() as tmpdirname:
																			_snake_case						:					str    =   Path(lowercase_    ) / "preprocessor_config.json"
																			json.dump(
																			    {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}				,    open(lowercase_				,    "w"    )				,    )

																			_snake_case						:					Dict    =   AutoImageProcessor.from_pretrained(lowercase_    )
																			self.assertIsInstance(lowercase_				,    lowercase_    )



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



							def 	UpperCamelCase	(						self    ):
													with self.assertRaisesRegex(
													    lowercase_				,    R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"    ):
																			_snake_case						:					List[Any]    =   AutoImageProcessor.from_pretrained(lowercase_				,    revision="aaaaaa"    )



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



							def 	UpperCamelCase	(						self    ):
													# If remote code is not set, we will time out when asking whether to load the model.
													with self.assertRaises(lowercase_    ):
																			_snake_case						:					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_    ):
																			_snake_case						:					Dict    =   AutoImageProcessor.from_pretrained(
																			    "hf-internal-testing/test_dynamic_image_processor"				,    trust_remote_code=lowercase_    )

													_snake_case						:					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_    )
																			_snake_case						:					Optional[int]    =   AutoImageProcessor.from_pretrained(lowercase_				,    trust_remote_code=lowercase_    )
													self.assertEqual(reloaded_image_processor.__class__.__name__				,    "NewImageProcessor"    )



							def 	UpperCamelCase	(						self    ):
													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:
																									_snake_case						:					Optional[int]    =   Path(lowercase_    ) / "preprocessor_config.json"
																									_snake_case						:					Tuple    =   Path(lowercase_    ) / "config.json"
																									json.dump(
																									    {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}				,    open(lowercase_				,    "w"    )				,    )
																									json.dump({"model_type": "clip"}				,    open(lowercase_				,    "w"    )    )

																									_snake_case						:					List[Any]    =   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_    )
																									_snake_case						:					Dict    =   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 	UpperCamelCase	(						self    ):



													class        lowercase_   (					__snake_case		):
																				_lowerCamelCase						=		True

													try:
																			AutoConfig.register("custom"				,    lowercase_    )
																			AutoImageProcessor.register(lowercase_				,    lowercase_    )
																			# If remote code is not set, the default is to use local
																			_snake_case						:					Optional[Any]    =   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.
																			_snake_case						:					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
																			_snake_case						:					Any    =   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]
import logging

from transformers import PretrainedConfig


__SCREAMING_SNAKE_CASE						:   Any         =			logging.getLogger(__name__)


__SCREAMING_SNAKE_CASE						:   int         =			{
    'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}



class        lowercase_   (					__snake_case		):
							_lowerCamelCase						=		'bertabs'



							def __init__(						self				,    lowercase_=30_522				,    lowercase_=512				,    lowercase_=6				,    lowercase_=512				,    lowercase_=8				,    lowercase_=512				,    lowercase_=0.2				,    lowercase_=6				,    lowercase_=768				,    lowercase_=8				,    lowercase_=2_048				,    lowercase_=0.2				,    **lowercase_				,    ):
													super().__init__(**lowercase_    )

													_snake_case						:					List[Any]    =   vocab_size
													_snake_case						:					int    =   max_pos

													_snake_case						:					Tuple    =   enc_layers
													_snake_case						:					Optional[Any]    =   enc_hidden_size
													_snake_case						:					Union[str, Any]    =   enc_heads
													_snake_case						:					str    =   enc_ff_size
													_snake_case						:					Any    =   enc_dropout

													_snake_case						:					Tuple    =   dec_layers
													_snake_case						:					Optional[Any]    =   dec_hidden_size
													_snake_case						:					Dict    =   dec_heads
													_snake_case						:					str    =   dec_ff_size
													_snake_case						:					List[str]    =   dec_dropout