





"""simple docstring"""





import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase__     			=			get_tests_dir('''fixtures/test_sentencepiece.model''')





@require_sentencepiece
@require_tokenizers
class        _lowerCamelCase      (       __SCREAMING_SNAKE_CASE  ,			unittest.TestCase ):
						UpperCAmelCase_ =			XLMRobertaTokenizer
						UpperCAmelCase_ =			XLMRobertaTokenizerFast
						UpperCAmelCase_ =			True
						UpperCAmelCase_ =			True


						def     snake_case_   (self		) ->   str:
								super().setUp()

								# We have a SentencePiece fixture for testing
								UpperCamelCase   =	XLMRobertaTokenizer(__snake_case   ,							keep_accents=__snake_case		)
								tokenizer.save_pretrained(self.tmpdirname		)


						def     snake_case_   (self		) ->   List[str]:
								UpperCamelCase   =	'''<pad>'''
								UpperCamelCase   =	1

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case		)   ,							__snake_case		)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case		)   ,							__snake_case		)


						def     snake_case_   (self		) ->   int:
								UpperCamelCase   =	list(self.get_tokenizer().get_vocab().keys()		)

								self.assertEqual(vocab_keys[0]   ,							"<s>"		)
								self.assertEqual(vocab_keys[1]   ,							"<pad>"		)
								self.assertEqual(vocab_keys[-1]   ,							"<mask>"		)
								self.assertEqual(len(__snake_case		)   ,							10_02		)


						def     snake_case_   (self		) ->   List[Any]:
								self.assertEqual(self.get_tokenizer().vocab_size   ,							10_02		)


						def     snake_case_   (self		) ->   Any:
								UpperCamelCase   =	XLMRobertaTokenizer(__snake_case   ,							keep_accents=__snake_case		)

								UpperCamelCase   =	tokenizer.tokenize("This is a test"		)
								self.assertListEqual(__snake_case   ,							["▁This", "▁is", "▁a", "▁t", "est"]		)

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(__snake_case		)   ,							[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]   ,							)

								UpperCamelCase   =	tokenizer.tokenize("I was born in 92000, and this is falsé."		)
								self.assertListEqual(
								    __snake_case   ,							[
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "9",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "é",
								        ".",
								    ]   ,							)
								UpperCamelCase   =	tokenizer.convert_tokens_to_ids(__snake_case		)
								self.assertListEqual(
								    __snake_case   ,							[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
								    ]   ,							)

								UpperCamelCase   =	tokenizer.convert_ids_to_tokens(__snake_case		)
								self.assertListEqual(
								    __snake_case   ,							[
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "<unk>",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "<unk>",
								        ".",
								    ]   ,							)


						def     snake_case_   (self		) ->   Optional[Any]:
								if not self.test_slow_tokenizer:
										# as we don't have a slow version, we can't compare the outputs between slow and fast versions
										return

								UpperCamelCase   =	(self.rust_tokenizer_class, '''hf-internal-testing/tiny-xlm-roberta''', {})
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"		):
												UpperCamelCase   =	self.rust_tokenizer_class.from_pretrained(__snake_case   ,							**__snake_case		)
												UpperCamelCase   =	self.tokenizer_class.from_pretrained(__snake_case   ,							**__snake_case		)

												UpperCamelCase   =	tempfile.mkdtemp()

												UpperCamelCase   =	tokenizer_r.save_pretrained(__snake_case		)
												UpperCamelCase   =	tokenizer_p.save_pretrained(__snake_case		)

												# Checks it save with the same files + the tokenizer.json file for the fast one
												self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files		)		)
												UpperCamelCase   =	tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f		)
												self.assertSequenceEqual(__snake_case   ,							__snake_case		)

												# Checks everything loads correctly in the same way
												UpperCamelCase   =	tokenizer_r.from_pretrained(__snake_case		)
												UpperCamelCase   =	tokenizer_p.from_pretrained(__snake_case		)

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
														self.assertTrue(hasattr(__snake_case   ,							__snake_case		)		)
														# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
														# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

												shutil.rmtree(__snake_case		)

												# Save tokenizer rust, legacy_format=True
												UpperCamelCase   =	tempfile.mkdtemp()

												UpperCamelCase   =	tokenizer_r.save_pretrained(__snake_case   ,							legacy_format=__snake_case		)
												UpperCamelCase   =	tokenizer_p.save_pretrained(__snake_case		)

												# Checks it save with the same files
												self.assertSequenceEqual(__snake_case   ,							__snake_case		)

												# Checks everything loads correctly in the same way
												UpperCamelCase   =	tokenizer_r.from_pretrained(__snake_case		)
												UpperCamelCase   =	tokenizer_p.from_pretrained(__snake_case		)

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
														self.assertTrue(hasattr(__snake_case   ,							__snake_case		)		)

												shutil.rmtree(__snake_case		)

												# Save tokenizer rust, legacy_format=False
												UpperCamelCase   =	tempfile.mkdtemp()

												UpperCamelCase   =	tokenizer_r.save_pretrained(__snake_case   ,							legacy_format=__snake_case		)
												UpperCamelCase   =	tokenizer_p.save_pretrained(__snake_case		)

												# Checks it saved the tokenizer.json file
												self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files		)		)

												# Checks everything loads correctly in the same way
												UpperCamelCase   =	tokenizer_r.from_pretrained(__snake_case		)
												UpperCamelCase   =	tokenizer_p.from_pretrained(__snake_case		)

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
														self.assertTrue(hasattr(__snake_case   ,							__snake_case		)		)

												shutil.rmtree(__snake_case		)


						@cached_property
						def     snake_case_   (self		) ->   Dict:
								return XLMRobertaTokenizer.from_pretrained("xlm-roberta-base"		)


						def     snake_case_   (self		) ->   Tuple:
								with tempfile.NamedTemporaryFile() as f:
										shutil.copyfile(__snake_case   ,							f.name		)
										UpperCamelCase   =	XLMRobertaTokenizer(f.name   ,							keep_accents=__snake_case		)
										UpperCamelCase   =	pickle.dumps(__snake_case		)
								pickle.loads(__snake_case		)


						def     snake_case_   (self		) ->   Any:
								if not self.test_rust_tokenizer:
										return

								UpperCamelCase   =	self.get_tokenizer()
								UpperCamelCase   =	self.get_rust_tokenizer()

								UpperCamelCase   =	'''I was born in 92000, and this is falsé.'''

								UpperCamelCase   =	tokenizer.tokenize(__snake_case		)
								UpperCamelCase   =	rust_tokenizer.tokenize(__snake_case		)
								self.assertListEqual(__snake_case   ,							__snake_case		)

								UpperCamelCase   =	tokenizer.encode(__snake_case   ,							add_special_tokens=__snake_case		)
								UpperCamelCase   =	rust_tokenizer.encode(__snake_case   ,							add_special_tokens=__snake_case		)
								self.assertListEqual(__snake_case   ,							__snake_case		)

								UpperCamelCase   =	self.get_rust_tokenizer()
								UpperCamelCase   =	tokenizer.encode(__snake_case		)
								UpperCamelCase   =	rust_tokenizer.encode(__snake_case		)
								self.assertListEqual(__snake_case   ,							__snake_case		)


						@slow
						def     snake_case_   (self		) ->   List[Any]:
								UpperCamelCase   =	'''Hello World!'''
								UpperCamelCase   =	[0, 3_53_78, 66_61, 38, 2]
								# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
								# xlmr.eval()
								# xlmr.encode(symbols)

								self.assertListEqual(__snake_case   ,							self.big_tokenizer.encode(__snake_case		)		)


						@slow
						def     snake_case_   (self		) ->   int:
								UpperCamelCase   =	(
								    '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
								    ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
								)
								UpperCamelCase   =	[
								    0,
								    32_93,
								    83,
								    10,
								    45_52,
								    49_89,
								    79_86,
								    6_78,
								    10,
								    59_15,
								    1_11,
								    17_94_59,
								    12_48_50,
								    4,
								    60_44,
								    2_37,
								    12,
								    6,
								    5,
								    6,
								    4,
								    67_80,
								    7_05,
								    15,
								    13_88,
								    44,
								    3_78,
								    1_01_14,
								    7_11,
								    1_52,
								    20,
								    6,
								    5,
								    2_23_76,
								    6_42,
								    12_21,
								    1_51_90,
								    3_41_53,
								    4_50,
								    56_08,
								    9_59,
								    11_19,
								    5_77_02,
								    1_36,
								    1_86,
								    47,
								    10_98,
								    2_93_67,
								    47,
								    # 4426, # What fairseq tokenizes from "<unk>": "_<"
								    # 3678, # What fairseq tokenizes from "<unk>": "unk"
								    # 2740, # What fairseq tokenizes from "<unk>": ">"
								    3,  # What we tokenize from "<unk>": "<unk>"
								    6,  # Residue from the tokenization: an extra sentencepiece underline
								    4,
								    60_44,
								    2_37,
								    62_84,
								    5_09_01,
								    5_28,
								    31,
								    90,
								    34,
								    9_27,
								    2,
								]
								# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
								# xlmr.eval()
								# xlmr.encode(symbols)

								self.assertListEqual(__snake_case   ,							self.big_tokenizer.encode(__snake_case		)		)




						@slow
						def     snake_case_   (self		) ->   str:
								# fmt: off
								UpperCamelCase   =	{'''input_ids''': [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=__snake_case   ,							model_name="xlm-roberta-base"   ,							revision="d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"   ,							)













"""simple docstring"""





import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	test_file.split(os.path.sep    )
		if components[0:2] != ["tests", "models"]:
				raise ValueError(
				    "`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got "
				    F"{test_file} instead."    )
		UpperCamelCase   =	components[-1]
		if not test_fn.endswith("py"    ):
				raise ValueError(F"`test_file` should be a python file. Got {test_fn} instead."    )
		if not test_fn.startswith("test_modeling_"    ):
				raise ValueError(
				    F"`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead."    )

		UpperCamelCase   =	components[:-1] + [test_fn.replace(".py"  ,	""    )]
		UpperCamelCase   =	".".join(_SCREAMING_SNAKE_CASE    )

		return test_module_path


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_module_path(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	importlib.import_module(_SCREAMING_SNAKE_CASE    )

		return test_module


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	[]
		UpperCamelCase   =	get_test_module(_SCREAMING_SNAKE_CASE    )
		for attr in dir(_SCREAMING_SNAKE_CASE    ):
				if attr.endswith("ModelTester"    ):
						tester_classes.append(getattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )    )

    # sort with class names
		return sorted(_SCREAMING_SNAKE_CASE  ,	key=lambda _SCREAMING_SNAKE_CASE    : x.__name__    )


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	[]
		UpperCamelCase   =	get_test_module(_SCREAMING_SNAKE_CASE    )
		for attr in dir(_SCREAMING_SNAKE_CASE    ):
				UpperCamelCase   =	getattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
				# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
				# `all_model_classes` is not empty (which also excludes other special classes).
				UpperCamelCase   =	getattr(_SCREAMING_SNAKE_CASE  ,	"all_model_classes"  ,	[]    )
				if len(_SCREAMING_SNAKE_CASE    ) > 0:
						test_classes.append(_SCREAMING_SNAKE_CASE    )

    # sort with class names
		return sorted(_SCREAMING_SNAKE_CASE  ,	key=lambda _SCREAMING_SNAKE_CASE    : x.__name__    )


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_test_classes(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	set()
		for test_class in test_classes:
				model_classes.update(test_class.all_model_classes    )

		# sort with class names
		return sorted(_SCREAMING_SNAKE_CASE  ,	key=lambda _SCREAMING_SNAKE_CASE    : x.__name__    )


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	test_class()
		if hasattr(_SCREAMING_SNAKE_CASE  ,	"setUp"    ):
				test.setUp()

		UpperCamelCase   =	None
		if hasattr(_SCREAMING_SNAKE_CASE  ,	"model_tester"    ):
				# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
				if test.model_tester is not None:
						UpperCamelCase   =	test.model_tester.__class__

		return model_tester


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_test_classes(_SCREAMING_SNAKE_CASE    )

		UpperCamelCase   =	[]
		for test_class in test_classes:
				if model_class in test_class.all_model_classes:
						target_test_classes.append(_SCREAMING_SNAKE_CASE    )

    # sort with class names
		return sorted(_SCREAMING_SNAKE_CASE  ,	key=lambda _SCREAMING_SNAKE_CASE    : x.__name__    )


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_test_classes_for_model(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )

		UpperCamelCase   =	[]
		for test_class in test_classes:
				UpperCamelCase   =	get_model_tester_from_test_class(_SCREAMING_SNAKE_CASE    )
				if tester_class is not None:
						tester_classes.append(_SCREAMING_SNAKE_CASE    )

    # sort with class names
		return sorted(_SCREAMING_SNAKE_CASE  ,	key=lambda _SCREAMING_SNAKE_CASE    : x.__name__    )


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_test_classes(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	{test_class: get_model_tester_from_test_class(_SCREAMING_SNAKE_CASE    ) for test_class in test_classes}
		return test_tester_mapping


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_model_classes(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	{
		    model_class: get_test_classes_for_model(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ) for model_class in model_classes
		}
		return model_test_mapping


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	get_model_classes(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	{
		    model_class: get_tester_classes_for_model(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ) for model_class in model_classes
		}
		return model_to_tester_mapping






def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		if isinstance(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):
				return o
		elif isinstance(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):
				return o.__name__
		elif isinstance(_SCREAMING_SNAKE_CASE  ,	(list, tuple)    ):
				return [to_json(_SCREAMING_SNAKE_CASE    ) for x in o]
		elif isinstance(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):
				return {to_json(_SCREAMING_SNAKE_CASE    ): to_json(_SCREAMING_SNAKE_CASE    ) for k, v in o.items()}
		else:
				return o






