
'''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


_lowercase			:  str   							=	get_tests_dir("fixtures/test_sentencepiece.model")






@require_sentencepiece
@require_tokenizers
class 			lowerCAmelCase__       (  lowerCamelCase_   ,						unittest.TestCase					):
					lowerCAmelCase_					       =					XLMRobertaTokenizer
					lowerCAmelCase_					       =					XLMRobertaTokenizerFast
					lowerCAmelCase_					       =					True
					lowerCAmelCase_					       =					True






					def      _snake_case   (       self		):


											"""simple docstring"""





											super().setUp()

											# We have a SentencePiece fixture for testing
											lowercase_     :					Union[str, Any]													=	XLMRobertaTokenizer(__SCREAMING_SNAKE_CASE    ,							keep_accents=__SCREAMING_SNAKE_CASE		)
											tokenizer.save_pretrained(self.tmpdirname		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Optional[int]													=	'''<pad>'''
											lowercase_     :					int													=	1

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






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					int													=	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(__SCREAMING_SNAKE_CASE		)    ,							10_02		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											self.assertEqual(self.get_tokenizer().vocab_size    ,							10_02		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					str													=	XLMRobertaTokenizer(__SCREAMING_SNAKE_CASE    ,							keep_accents=__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Optional[Any]													=	tokenizer.tokenize('''This is a test'''		)
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']		)

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

											lowercase_     :					str													=	tokenizer.tokenize('''I was born in 92000, and this is falsé.'''		)
											self.assertListEqual(
											    __SCREAMING_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''',
											        '''.''',
											    ]    ,							)
											lowercase_     :					List[str]													=	tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(
											    __SCREAMING_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 ^
											    ]    ,							)

											lowercase_     :					List[Any]													=	tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(
											    __SCREAMING_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		):


											"""simple docstring"""





											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

											lowercase_     :					List[Any]													=	(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})'''		):
																							lowercase_     :					List[Any]													=	self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Tuple													=	self.tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)

																							lowercase_     :					List[str]													=	tempfile.mkdtemp()

																							lowercase_     :					int													=	tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Optional[int]													=	tokenizer_p.save_pretrained(__SCREAMING_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		)		)
																							lowercase_     :					Tuple													=	tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f		)
																							self.assertSequenceEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

																							# Checks everything loads correctly in the same way
																							lowercase_     :					Dict													=	tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Optional[int]													=	tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE		)

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

																							# Save tokenizer rust, legacy_format=True
																							lowercase_     :					Union[str, Any]													=	tempfile.mkdtemp()

																							lowercase_     :					Any													=	tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE    ,							legacy_format=__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Any													=	tokenizer_p.save_pretrained(__SCREAMING_SNAKE_CASE		)

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

																							# Checks everything loads correctly in the same way
																							lowercase_     :					str													=	tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Any													=	tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE		)

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

																							shutil.rmtree(__SCREAMING_SNAKE_CASE		)

																							# Save tokenizer rust, legacy_format=False
																							lowercase_     :					List[Any]													=	tempfile.mkdtemp()

																							lowercase_     :					Dict													=	tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE    ,							legacy_format=__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Any													=	tokenizer_p.save_pretrained(__SCREAMING_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
																							lowercase_     :					Union[str, Any]													=	tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Dict													=	tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE		)

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

																							shutil.rmtree(__SCREAMING_SNAKE_CASE		)






					@cached_property
					def      _snake_case   (       self		):


											"""simple docstring"""





											return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											with tempfile.NamedTemporaryFile() as f:
																	shutil.copyfile(__SCREAMING_SNAKE_CASE    ,							f.name		)
																	lowercase_     :					Optional[Any]													=	XLMRobertaTokenizer(f.name    ,							keep_accents=__SCREAMING_SNAKE_CASE		)
																	lowercase_     :					Dict													=	pickle.dumps(__SCREAMING_SNAKE_CASE		)
											pickle.loads(__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											if not self.test_rust_tokenizer:
																	return

											lowercase_     :					Optional[int]													=	self.get_tokenizer()
											lowercase_     :					Dict													=	self.get_rust_tokenizer()

											lowercase_     :					List[str]													=	'''I was born in 92000, and this is falsé.'''

											lowercase_     :					List[str]													=	tokenizer.tokenize(__SCREAMING_SNAKE_CASE		)
											lowercase_     :					Optional[int]													=	rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Any													=	tokenizer.encode(__SCREAMING_SNAKE_CASE    ,							add_special_tokens=__SCREAMING_SNAKE_CASE		)
											lowercase_     :					str													=	rust_tokenizer.encode(__SCREAMING_SNAKE_CASE    ,							add_special_tokens=__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					List[str]													=	self.get_rust_tokenizer()
											lowercase_     :					Optional[int]													=	tokenizer.encode(__SCREAMING_SNAKE_CASE		)
											lowercase_     :					Union[str, Any]													=	rust_tokenizer.encode(__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)






					@slow
					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Dict													=	'''Hello World!'''
											lowercase_     :					Optional[Any]													=	[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(__SCREAMING_SNAKE_CASE    ,							self.big_tokenizer.encode(__SCREAMING_SNAKE_CASE		)		)






					@slow
					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Dict													=	(
											    '''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'''
											)
											lowercase_     :					Tuple													=	[
											    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(__SCREAMING_SNAKE_CASE    ,							self.big_tokenizer.encode(__SCREAMING_SNAKE_CASE		)		)






					@slow
					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Optional[int]													=	{'''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=__SCREAMING_SNAKE_CASE    ,							model_name='''xlm-roberta-base'''    ,							revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''    ,							)





'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase			:  Any   							=	logging.get_logger(__name__)

_lowercase			:  Dict   							=	{
    "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}






class 			lowerCAmelCase__       (  lowerCamelCase_					):
					lowerCAmelCase_					       =					'''gpt_neox'''






					def __init__(       self    ,							__SCREAMING_SNAKE_CASE=5_04_32    ,							__SCREAMING_SNAKE_CASE=61_44    ,							__SCREAMING_SNAKE_CASE=44    ,							__SCREAMING_SNAKE_CASE=64    ,							__SCREAMING_SNAKE_CASE=2_45_76    ,							__SCREAMING_SNAKE_CASE="gelu"    ,							__SCREAMING_SNAKE_CASE=0.25    ,							__SCREAMING_SNAKE_CASE=1_00_00    ,							__SCREAMING_SNAKE_CASE=0.0    ,							__SCREAMING_SNAKE_CASE=0.0    ,							__SCREAMING_SNAKE_CASE=0.1    ,							__SCREAMING_SNAKE_CASE=20_48    ,							__SCREAMING_SNAKE_CASE=0.02    ,							__SCREAMING_SNAKE_CASE=1E-5    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE=0    ,							__SCREAMING_SNAKE_CASE=2    ,							__SCREAMING_SNAKE_CASE=False    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE=None    ,							**__SCREAMING_SNAKE_CASE    ,							):


											"""simple docstring"""





											super().__init__(bos_token_id=__SCREAMING_SNAKE_CASE    ,							eos_token_id=__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
											lowercase_     :					Optional[Any]													=	vocab_size
											lowercase_     :					Optional[Any]													=	max_position_embeddings
											lowercase_     :					Optional[int]													=	hidden_size
											lowercase_     :					Tuple													=	num_hidden_layers
											lowercase_     :					Any													=	num_attention_heads
											lowercase_     :					str													=	intermediate_size
											lowercase_     :					Any													=	hidden_act
											lowercase_     :					Tuple													=	rotary_pct
											lowercase_     :					Optional[Any]													=	rotary_emb_base
											lowercase_     :					Any													=	attention_dropout
											lowercase_     :					str													=	hidden_dropout
											lowercase_     :					Dict													=	classifier_dropout
											lowercase_     :					Tuple													=	initializer_range
											lowercase_     :					List[str]													=	layer_norm_eps
											lowercase_     :					Union[str, Any]													=	use_cache
											lowercase_     :					int													=	tie_word_embeddings
											lowercase_     :					Tuple													=	use_parallel_residual
											lowercase_     :					Optional[Any]													=	rope_scaling
											self._rope_scaling_validation()

											if self.hidden_size % self.num_attention_heads != 0:
																	raise ValueError(
																	    '''The hidden size is not divisble by the number of attention heads! Make sure to update them!'''		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											if self.rope_scaling is None:
																	return

											if not isinstance(self.rope_scaling    ,							__SCREAMING_SNAKE_CASE		) or len(self.rope_scaling		) != 2:
																	raise ValueError(
																	    '''`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '''
																	    F'''got {self.rope_scaling}'''		)
											lowercase_     :					List[Any]													=	self.rope_scaling.get('''type'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					int													=	self.rope_scaling.get('''factor'''    ,							__SCREAMING_SNAKE_CASE		)
											if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
																	raise ValueError(
																	    F'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''		)
											if rope_scaling_factor is None or not isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) or rope_scaling_factor <= 1.0:
																	raise ValueError(F'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''		)



