

'''simple docstring'''
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


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

from test_module.custom_configuration import CustomConfig  # noqa E402


_lowerCamelCase      					=     get_tests_dir("""fixtures/dummy-config.json""")
class 					_snake_case		(unittest.TestCase):






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  0






			def 		UpperCamelCase__							(  self     ):
				self.assertIsNotNone(transformers.models.auto.__spec__     )
				self.assertIsNotNone(importlib.util.find_spec("transformers.models.auto"     )     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  AutoConfig.from_pretrained("bert-base-uncased"     )
				self.assertIsInstance(_snake_case			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      List[str]						=  AutoConfig.from_pretrained(_snake_case     )
				self.assertIsInstance(_snake_case			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Tuple						=  AutoConfig.from_pretrained(_snake_case     )
				self.assertIsInstance(_snake_case			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  AutoConfig.for_model("roberta"     )
				self.assertIsInstance(_snake_case			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				with tempfile.TemporaryDirectory() as tmp_dir:
					# This model name contains bert and roberta, but roberta ends up being picked.
					UpperCAmelCase_     :      List[str]						=  os.path.join(_snake_case			,"fake-roberta"     )
					os.makedirs(_snake_case			,exist_ok=_snake_case     )
					with open(os.path.join(_snake_case			,"config.json"     )			,"w"     ) as f:
						f.write(json.dumps({}     )     )
					UpperCAmelCase_     :      Union[str, Any]						=  AutoConfig.from_pretrained(_snake_case     )
					self.assertEqual(type(_snake_case     )			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				try:
					AutoConfig.register("custom"			,_snake_case     )
					# Wrong model type will raise an error
					with self.assertRaises(_snake_case     ):
						AutoConfig.register("model"			,_snake_case     )
					# Trying to register something existing in the Transformers library will raise an error
					with self.assertRaises(_snake_case     ):
						AutoConfig.register("bert"			,_snake_case     )

					# Now that the config is registered, it can be used as any other config with the auto-API
					UpperCAmelCase_     :      Union[str, Any]						=  CustomConfig()
					with tempfile.TemporaryDirectory() as tmp_dir:
						config.save_pretrained(_snake_case     )
						UpperCAmelCase_     :      Union[str, Any]						=  AutoConfig.from_pretrained(_snake_case     )
						self.assertIsInstance(_snake_case			,_snake_case     )

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






			def 		UpperCamelCase__							(  self     ):
				with self.assertRaisesRegex(
				    _snake_case			,"bert-base is not a local folder and is not a valid model identifier"     ):
					UpperCAmelCase_     :      int						=  AutoConfig.from_pretrained("bert-base"     )






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






			def 		UpperCamelCase__							(  self     ):
				with self.assertRaisesRegex(
				    _snake_case			,"hf-internal-testing/no-config-test-repo does not appear to have a file named config.json."			,):
					UpperCAmelCase_     :      Any						=  AutoConfig.from_pretrained("hf-internal-testing/no-config-test-repo"     )






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

				UpperCAmelCase_     :      Optional[int]						=  AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"			,trust_remote_code=_snake_case     )
				self.assertEqual(config.__class__.__name__			,"NewModelConfig"     )

				# Test config can be reloaded.
				with tempfile.TemporaryDirectory() as tmp_dir:
					config.save_pretrained(_snake_case     )
					UpperCAmelCase_     :      Any						=  AutoConfig.from_pretrained(_snake_case			,trust_remote_code=_snake_case     )
				self.assertEqual(reloaded_config.__class__.__name__			,"NewModelConfig"     )






			def 		UpperCamelCase__							(  self     ):
				class 					_snake_case		(__SCREAMING_SNAKE_CASE):
							__A  :	Optional[int]        ="new-model"

				try:
					AutoConfig.register("new-model"			,_snake_case     )
					# If remote code is not set, the default is to use local
					UpperCAmelCase_     :      Optional[int]						=  AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"     )
					self.assertEqual(config.__class__.__name__			,"NewModelConfigLocal"     )

					# If remote code is disabled, we load the local one.
					UpperCAmelCase_     :      Optional[int]						=  AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"			,trust_remote_code=_snake_case     )
					self.assertEqual(config.__class__.__name__			,"NewModelConfigLocal"     )

					# If remote is enabled, we load from the Hub
					UpperCAmelCase_     :      Any						=  AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"			,trust_remote_code=_snake_case     )
					self.assertEqual(config.__class__.__name__			,"NewModelConfig"     )

				finally:
					if "new-model" in CONFIG_MAPPING._extra_content:
						del CONFIG_MAPPING._extra_content["new-model"]












'''simple docstring'''



import copy
import random

from transformers import CLIPTokenizer
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):




      def __init__(	self			, *lowerCamelCase			, **lowerCamelCase   )				->Union[str, Any]:



         '''simple docstring'''
         super().__init__(*lowerCamelCase			, **lowerCamelCase   )
         __a					  =     {}




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )				->Dict:



         '''simple docstring'''
         __a					  =     super().add_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
         if num_added_tokens == 0:
            raise ValueError(
                F"""The tokenizer already contains the token {placeholder_token}. Please pass a different"""
                ' `placeholder_token` that is not already in the tokenizer.'   )




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=1			, **lowerCamelCase   )				->List[str]:



         '''simple docstring'''
         __a					  =     []
         if num_vec_per_token == 1:
            self.try_adding_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
            output.append(lowerCamelCase   )
         else:
            __a					  =     []
            for i in range(lowerCamelCase   ):
               __a					  =     placeholder_token + F"""_{i}"""
               self.try_adding_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
               output.append(lowerCamelCase   )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
         for token in self.token_map:
            if token in placeholder_token:
               raise ValueError(
                   F"""The tokenizer already has placeholder token {token} that can get confused with"""
                   F""" {placeholder_token}keep placeholder tokens independent"""   )
         __a					  =     output




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0   )				->int:



         '''simple docstring'''
         if isinstance(lowerCamelCase			, lowerCamelCase   ):
            __a					  =     []
            for i in range(len(lowerCamelCase   )   ):
               output.append(self.replace_placeholder_tokens_in_text(text[i]			, vector_shuffle=lowerCamelCase   )   )
            return output
         for placeholder_token in self.token_map:
            if placeholder_token in text:
               __a					  =     self.token_map[placeholder_token]
               __a					  =     tokens[: 1 + int(len(lowerCamelCase   ) * prop_tokens_to_load   )]
               if vector_shuffle:
                  __a					  =     copy.copy(lowerCamelCase   )
                  random.shuffle(lowerCamelCase   )
               __a					  =     text.replace(lowerCamelCase			, ' '.join(lowerCamelCase   )   )
         return text




      def __call__(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0			, **lowerCamelCase   )				->Optional[int]:



         '''simple docstring'''
         return super().__call__(
             self.replace_placeholder_tokens_in_text(
                 lowerCamelCase			, vector_shuffle=lowerCamelCase			, prop_tokens_to_load=lowerCamelCase   )			, *lowerCamelCase			, **lowerCamelCase			, )






      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0			, **lowerCamelCase   )				->List[Any]:



         '''simple docstring'''
         return super().encode(
             self.replace_placeholder_tokens_in_text(
                 lowerCamelCase			, vector_shuffle=lowerCamelCase			, prop_tokens_to_load=lowerCamelCase   )			, *lowerCamelCase			, **lowerCamelCase			, )