



"""simple docstring"""





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


__lowerCAmelCase							:       Optional[int]          =       logging.get_logger(__name__)

__lowerCAmelCase							:       Union[str, Any]          =       {
    '''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     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase      	=							'''gpt_neox'''





		def __init__(       self				,     _lowercase=5_0_4_3_2				,     _lowercase=6_1_4_4				,     _lowercase=4_4				,     _lowercase=6_4				,     _lowercase=2_4_5_7_6				,     _lowercase="gelu"				,     _lowercase=0.25				,     _lowercase=1_0_0_0_0				,     _lowercase=0.0				,     _lowercase=0.0				,     _lowercase=0.1				,     _lowercase=2_0_4_8				,     _lowercase=0.02				,     _lowercase=1E-5				,     _lowercase=True				,     _lowercase=0				,     _lowercase=2				,     _lowercase=False				,     _lowercase=True				,     _lowercase=None				,     **_lowercase				,     )			->    Union[str, Any]:







								'''simple docstring'''

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







								'''simple docstring'''

								if self.rope_scaling is None:
														return

								if not isinstance(self.rope_scaling				,     _lowercase ) 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}' )
								snake_case_ :			Dict            =      self.rope_scaling.get("""type"""				,     _lowercase )
								snake_case_ :			str            =      self.rope_scaling.get("""factor"""				,     _lowercase )
								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(_lowercase				,     _lowercase ) or rope_scaling_factor <= 1.0:
														raise ValueError(f'`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}' )







import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin

class 						__lowerCAmelCase      (      __magic_name__ ,			unittest.TestCase					):
							UpperCamelCase__   	=    TransfoXLTokenizer
							UpperCamelCase__   	=    False
							UpperCamelCase__   	=    False
							def  lowerCamelCase__				(		self		:Optional[Any]							):







								'''simple docstring'''







								super().setUp()

								a									=				[
								    """<unk>""",
								    """[CLS]""",
								    """[SEP]""",
								    """want""",
								    """unwanted""",
								    """wa""",
								    """un""",
								    """running""",
								    """,""",
								    """low""",
								    """l""",
								]
								a									=				os.path.join(self.tmpdirname						, VOCAB_FILES_NAMES["""vocab_file"""]							)
								with open(self.vocab_file						, """w"""						, encoding="""utf-8"""							) as vocab_writer:
									vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]							)							)
							def  lowerCamelCase__				(		self		:List[Any]						, **__magic_name__		:Optional[int]							):







								'''simple docstring'''







								a									=				True
								return TransfoXLTokenizer.from_pretrained(self.tmpdirname						, **__magic_name__							)
							def  lowerCamelCase__				(		self		:Union[str, Any]						, __magic_name__		:int							):







								'''simple docstring'''







								a									=				"""<unk> UNwanted , running"""
								a									=				"""<unk> unwanted, running"""
								return input_text, output_text
							def  lowerCamelCase__				(		self		:str							):







								'''simple docstring'''







								a									=				TransfoXLTokenizer(vocab_file=self.vocab_file						, lower_case=__magic_name__							)

								a									=				tokenizer.tokenize("""<unk> UNwanted , running"""							)
								self.assertListEqual(__magic_name__						, ["""<unk>""", """unwanted""", """,""", """running"""]							)

								self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__							)						, [0, 4, 8, 7]							)
							def  lowerCamelCase__				(		self		:int							):







								'''simple docstring'''







								a									=				TransfoXLTokenizer(lower_case=__magic_name__							)

								self.assertListEqual(
								    tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """							)						, ["""hello""", """!""", """how""", """are""", """you""", """?"""]							)
							def  lowerCamelCase__				(		self		:str							):







								'''simple docstring'''







								a									=				TransfoXLTokenizer(lower_case=__magic_name__							)

								self.assertListEqual(
								    tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """							)						, ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]							)
							def  lowerCamelCase__				(		self		:Optional[int]							):







								'''simple docstring'''







								a									=				TransfoXLTokenizer(lower_case=__magic_name__							)
								a									=				"""Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"""
								a									=				[
								    """Hello""",
								    """(""",
								    """bracket""",
								    """)""",
								    """and""",
								    """side""",
								    """@-@""",
								    """scrolled""",
								    """[""",
								    """and""",
								    """]""",
								    """Henry""",
								    """'s""",
								    """$""",
								    """5""",
								    """@,@""",
								    """000""",
								    """with""",
								    """3""",
								    """@.@""",
								    """34""",
								    """m""",
								    """.""",
								    """What""",
								    """'s""",
								    """up""",
								    """!""",
								    """?""",
								]

								self.assertListEqual(tokenizer.tokenize(__magic_name__							)						, __magic_name__							)

								self.assertEqual(tokenizer.convert_tokens_to_string(__magic_name__							)						, __magic_name__							)





							def  lowerCamelCase__				(		self		:List[Any]							):







								'''simple docstring'''







								a									=				self.get_tokenizer()
								a									=				len(__magic_name__							)

								tokenizer.add_tokens(["""new1""", """new2"""]							)
								tokenizer.move_added_token("""new1"""						, 1							)

								# Check that moved token is not copied (duplicate)
								self.assertEqual(len(__magic_name__							)						, original_len + 2							)
								# Check that token is moved to specified id
								self.assertEqual(tokenizer.encode("""new1"""							)						, [1]							)
								self.assertEqual(tokenizer.decode([1]							)						, """new1"""							)

