






from collections import deque

from .hash_table import HashTable





class     SCREAMING_SNAKE_CASE					(			snake_case       ):





							"""simple docstring"""

							def __init__(	self: Dict		,  *__A: Tuple		,  **__A: int )     ->					List[str]:
												super().__init__(*snake_case__		,  **snake_case__ )

							def    __A			(	self: Dict		,  __A: str		,  __A: Any )     ->					List[Any]:
												_A										=			deque([] ) if self.values[key] is None else self.values[key]
												self.values[key].appendleft(snake_case__ )
												_A										=			self.values[key]

							def    __A			(	self: List[str] )     ->					Optional[Any]:
												return (
												    sum(self.charge_factor - len(snake_case__ ) for slot in self.values )
												    / self.size_table
												    * self.charge_factor
												)



							def    __A			(	self: Dict		,  __A: str		,  __A: str=None )     ->					Optional[Any]:




												if not (
												    len(self.values[key] ) == self.charge_factor and self.values.count(snake_case__ ) == 0
												):
																	return key
												return super()._collision_resolution(snake_case__		,  snake_case__ )





'''simple docstring'''





import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    FEATURE_EXTRACTOR_MAPPING,
    AutoConfig,
    AutoFeatureExtractor,
    WavaVecaConfig,
    WavaVecaFeatureExtractor,
)
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
from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


SCREAMING_SNAKE_CASE     =       get_tests_dir("""fixtures""")
SCREAMING_SNAKE_CASE     =       get_tests_dir("""fixtures/dummy_feature_extractor_config.json""")
SCREAMING_SNAKE_CASE     =       get_tests_dir("""fixtures/dummy-config.json""")






class 							UpperCAmelCase_							(    unittest.TestCase				):

 '''simple docstring'''







 def 							UpperCamelCase  (					self		:  int ):



   '''simple docstring'''




   UpperCAmelCase__      :					Any				       =							0







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



   '''simple docstring'''




   UpperCAmelCase__      :					Optional[int]				       =							AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h" )
   self.assertIsInstance(snake_case__			,				snake_case__ )







 def 							UpperCamelCase  (					self		:  int ):



   '''simple docstring'''




   UpperCAmelCase__      :					Optional[int]				       =							AutoFeatureExtractor.from_pretrained(snake_case__ )
   self.assertIsInstance(snake_case__			,				snake_case__ )







 def 							UpperCamelCase  (					self		:  List[Any] ):



   '''simple docstring'''




   with tempfile.TemporaryDirectory() as tmpdirname:
     UpperCAmelCase__      :					Optional[Any]				       =							WavaVecaConfig()

     # remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
     UpperCAmelCase__      :					Any				       =							AutoFeatureExtractor.from_pretrained(snake_case__ ).to_dict()

     config_dict.pop("feature_extractor_type" )
     UpperCAmelCase__      :					Union[str, Any]				       =							WavaVecaFeatureExtractor(**snake_case__ )

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

     UpperCAmelCase__      :					Tuple				       =							AutoFeatureExtractor.from_pretrained(snake_case__ )

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

   self.assertIsInstance(snake_case__			,				snake_case__ )







 def 							UpperCamelCase  (					self		:  int ):



   '''simple docstring'''




   UpperCAmelCase__      :					Any				       =							AutoFeatureExtractor.from_pretrained(snake_case__ )
   self.assertIsInstance(snake_case__			,				snake_case__ )







 def 							UpperCamelCase  (					self		:  Tuple ):



   '''simple docstring'''




   with self.assertRaisesRegex(
       snake_case__			,				"bert-base is not a local folder and is not a valid model identifier" ):
     UpperCAmelCase__      :					Optional[int]				       =							AutoFeatureExtractor.from_pretrained("bert-base" )







 def 							UpperCamelCase  (					self		:  Any ):



   '''simple docstring'''




   with self.assertRaisesRegex(
       snake_case__			,				R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)" ):
     UpperCAmelCase__      :					List[str]				       =							AutoFeatureExtractor.from_pretrained(snake_case__			,				revision="aaaaaa" )







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



   '''simple docstring'''




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







 def 							UpperCamelCase  (					self		:  Optional[Any] ):



   '''simple docstring'''




   with self.assertRaises(snake_case__ ):
     UpperCAmelCase__      :					List[str]				       =							AutoFeatureExtractor.from_pretrained(
         "hf-internal-testing/test_dynamic_feature_extractor" )
   # If remote code is disabled, we can't load this config.
   with self.assertRaises(snake_case__ ):
     UpperCAmelCase__      :					Any				       =							AutoFeatureExtractor.from_pretrained(
         "hf-internal-testing/test_dynamic_feature_extractor"			,				trust_remote_code=snake_case__ )

   UpperCAmelCase__      :					Optional[Any]				       =							AutoFeatureExtractor.from_pretrained(
       "hf-internal-testing/test_dynamic_feature_extractor"			,				trust_remote_code=snake_case__ )
   self.assertEqual(feature_extractor.__class__.__name__			,				"NewFeatureExtractor" )

   # Test feature extractor can be reloaded.
   with tempfile.TemporaryDirectory() as tmp_dir:
     feature_extractor.save_pretrained(snake_case__ )
     UpperCAmelCase__      :					Any				       =							AutoFeatureExtractor.from_pretrained(snake_case__			,				trust_remote_code=snake_case__ )
   self.assertEqual(reloaded_feature_extractor.__class__.__name__			,				"NewFeatureExtractor" )







 def 							UpperCamelCase  (					self		:  str ):



   '''simple docstring'''




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

     # Now that the config is registered, it can be used as any other config with the auto-API
     UpperCAmelCase__      :					str				       =							CustomFeatureExtractor.from_pretrained(snake_case__ )
     with tempfile.TemporaryDirectory() as tmp_dir:
       feature_extractor.save_pretrained(snake_case__ )
       UpperCAmelCase__      :					Optional[int]				       =							AutoFeatureExtractor.from_pretrained(snake_case__ )
       self.assertIsInstance(snake_case__			,				snake_case__ )

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







 def 							UpperCamelCase  (					self		:  str ):



   '''simple docstring'''




   class 							UpperCAmelCase_							(    A				):

    '''simple docstring'''
    lowercase_					:    Optional[Any]				=							True

   try:
     AutoConfig.register("custom"			,				snake_case__ )
     AutoFeatureExtractor.register(snake_case__			,				snake_case__ )
     # If remote code is not set, the default is to use local
     UpperCAmelCase__      :					Any				       =							AutoFeatureExtractor.from_pretrained(
         "hf-internal-testing/test_dynamic_feature_extractor" )
     self.assertEqual(feature_extractor.__class__.__name__			,				"NewFeatureExtractor" )
     self.assertTrue(feature_extractor.is_local )

     # If remote code is disabled, we load the local one.
     UpperCAmelCase__      :					Optional[int]				       =							AutoFeatureExtractor.from_pretrained(
         "hf-internal-testing/test_dynamic_feature_extractor"			,				trust_remote_code=snake_case__ )
     self.assertEqual(feature_extractor.__class__.__name__			,				"NewFeatureExtractor" )
     self.assertTrue(feature_extractor.is_local )

     # If remote is enabled, we load from the Hub
     UpperCAmelCase__      :					int				       =							AutoFeatureExtractor.from_pretrained(
         "hf-internal-testing/test_dynamic_feature_extractor"			,				trust_remote_code=snake_case__ )
     self.assertEqual(feature_extractor.__class__.__name__			,				"NewFeatureExtractor" )
     self.assertTrue(not hasattr(snake_case__			,				"is_local" ) )

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



