
'''simple docstring'''







import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 			lowerCAmelCase__       (  lowerCamelCase_   ,						unittest.TestCase					):
					lowerCAmelCase_					       =					None
					lowerCAmelCase_					       =					BloomTokenizerFast
					lowerCAmelCase_					       =					BloomTokenizerFast
					lowerCAmelCase_					       =					True
					lowerCAmelCase_					       =					False
					lowerCAmelCase_					       =					'''tokenizer_file'''
					lowerCAmelCase_					       =					{'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}






					def      _snake_case   (       self		):


											"""simple docstring"""





											super().setUp()
											lowercase_     :					List[Any]													=	BloomTokenizerFast.from_pretrained('''bigscience/tokenizer'''		)
											tokenizer.save_pretrained(self.tmpdirname		)






					def      _snake_case   (       self    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											kwargs.update(self.special_tokens_map		)
											return BloomTokenizerFast.from_pretrained(self.tmpdirname    ,							**__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Tuple													=	self.get_rust_tokenizer()

											lowercase_     :					Optional[Any]													=	['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
											lowercase_     :					Union[str, Any]													=	[[21_75, 2_37_14, 7_31_73, 14_42_52, 2], [77, 13_26_19, 34_78, 3_68, 10_95_86, 3_54_33, 2]]

											lowercase_     :					Dict													=	tokenizer.batch_encode_plus(__SCREAMING_SNAKE_CASE		)['''input_ids''']
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Tuple													=	tokenizer.batch_decode(__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE=6		):


											"""simple docstring"""





											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
																							lowercase_     :					int													=	self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																							# tokenizer_r.pad_token = None # Hotfixing padding = None
																							# Simple input
																							lowercase_     :					Optional[int]													=	'''This is a simple input'''
																							lowercase_     :					List[str]													=	['''This is a simple input 1''', '''This is a simple input 2''']
																							lowercase_     :					List[str]													=	('''This is a simple input''', '''This is a pair''')
																							lowercase_     :					Union[str, Any]													=	[
																							    ('''This is a simple input 1''', '''This is a simple input 2'''),
																							    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
																							]

																							# Simple input tests
																							try:
																													tokenizer_r.encode(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																													tokenizer_r.encode_plus(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)

																													tokenizer_r.batch_encode_plus(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																													tokenizer_r.encode(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																													tokenizer_r.batch_encode_plus(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																							except ValueError:
																													self.fail('''Bloom Tokenizer should be able to deal with padding'''		)

																							lowercase_     :					Optional[Any]													=	None  # Hotfixing padding = None
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Simple input
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Simple input
																							self.assertRaises(
																							    __SCREAMING_SNAKE_CASE    ,							tokenizer_r.batch_encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''    ,							)

																							# Pair input
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Pair input
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Pair input
																							self.assertRaises(
																							    __SCREAMING_SNAKE_CASE    ,							tokenizer_r.batch_encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''    ,							)






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					List[str]													=	self.get_rust_tokenizer()
											lowercase_     :					Tuple													=	load_dataset('''xnli'''    ,							'''all_languages'''    ,							split='''test'''    ,							streaming=__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Optional[int]													=	next(iter(__SCREAMING_SNAKE_CASE		)		)['''premise''']  # pick up one data
											lowercase_     :					List[Any]													=	list(sample_data.values()		)

											lowercase_     :					Tuple													=	list(map(tokenizer.encode    ,							__SCREAMING_SNAKE_CASE		)		)
											lowercase_     :					Any													=	[tokenizer.decode(__SCREAMING_SNAKE_CASE    ,							clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE		) for x in output_tokens]
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map		)    ,							1		)
											self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()		)[0]		)    ,							1		)





'''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}'''		)



