






"""simple docstring"""
import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase_					=      '''▁'''

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







@require_sentencepiece
class 			UpperCamelCase_       (__A				,						unittest.TestCase     ):
	__magic_name__	      =				BertGenerationTokenizer
	__magic_name__	      =				False
	__magic_name__	      =				True





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]						)						->			List[str]:
				super().setUp()

				UpperCAmelCase_     : List[Any]			     =					BertGenerationTokenizer(lowerCAmelCase_	,	keep_accents=lowerCAmelCase_						)
				tokenizer.save_pretrained(self.tmpdirname						)





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]						)						->			Optional[Any]:
				UpperCAmelCase_     : List[str]			     =					"<s>"
				UpperCAmelCase_     : Optional[Any]			     =					1

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





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]						)						->			Tuple:
				UpperCAmelCase_     : str			     =					list(self.get_tokenizer().get_vocab().keys()						)

				self.assertEqual(vocab_keys[0]	,	"<unk>"						)
				self.assertEqual(vocab_keys[1]	,	"<s>"						)
				self.assertEqual(vocab_keys[-1]	,	"<pad>"						)
				self.assertEqual(len(lowerCAmelCase_						)	,	1_002						)





	def      _SCREAMING_SNAKE_CASE      (      self					: int						)						->			int:
				self.assertEqual(self.get_tokenizer().vocab_size	,	1_000						)





	def      _SCREAMING_SNAKE_CASE      (      self					: str						)						->			List[str]:
				UpperCAmelCase_     : Union[str, Any]			     =					BertGenerationTokenizer(lowerCAmelCase_	,	keep_accents=lowerCAmelCase_						)

				UpperCAmelCase_     : Optional[int]			     =					tokenizer.tokenize("This is a test"						)
				self.assertListEqual(lowerCAmelCase_	,	["▁This", "▁is", "▁a", "▁t", "est"]						)

				self.assertListEqual(
				    tokenizer.convert_tokens_to_ids(lowerCAmelCase_						)	,	[285, 46, 10, 170, 382]	,	)

				UpperCAmelCase_     : Optional[int]			     =					tokenizer.tokenize("I was born in 92000, and this is falsé."						)
				self.assertListEqual(
				    lowerCAmelCase_	,	[
				        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_     : Any			     =					tokenizer.convert_tokens_to_ids(lowerCAmelCase_						)
				self.assertListEqual(
				    lowerCAmelCase_	,	[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]	,	)

				UpperCAmelCase_     : int			     =					tokenizer.convert_ids_to_tokens(lowerCAmelCase_						)
				self.assertListEqual(
				    lowerCAmelCase_	,	[
				        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>",
				        ".",
				    ]	,	)





	@cached_property
	def      _SCREAMING_SNAKE_CASE      (      self					: Union[str, Any]						)						->			Any:
				return BertGenerationTokenizer.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder"						)





	@slow
	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]						)						->			Optional[Any]:
				UpperCAmelCase_     : List[Any]			     =					"Hello World!"
				UpperCAmelCase_     : int			     =					[18_536, 2_260, 101]

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





	@slow
	def      _SCREAMING_SNAKE_CASE      (      self					: int						)						->			Dict:
				UpperCAmelCase_     : Optional[int]			     =					(
				    "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_     : int			     =					[
				    871,
				    419,
				    358,
				    946,
				    991,
				    2_521,
				    452,
				    358,
				    1_357,
				    387,
				    7_751,
				    3_536,
				    112,
				    985,
				    456,
				    126,
				    865,
				    938,
				    5_400,
				    5_734,
				    458,
				    1_368,
				    467,
				    786,
				    2_462,
				    5_246,
				    1_159,
				    633,
				    865,
				    4_519,
				    457,
				    582,
				    852,
				    2_557,
				    427,
				    916,
				    508,
				    405,
				    34_324,
				    497,
				    391,
				    408,
				    11_342,
				    1_244,
				    385,
				    100,
				    938,
				    985,
				    456,
				    574,
				    362,
				    12_597,
				    3_200,
				    3_129,
				    1_172,
				]

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





	@require_torch
	@slow
	def      _SCREAMING_SNAKE_CASE      (      self					: Union[str, Any]						)						->			List[Any]:
				import torch

				from transformers import BertGenerationConfig, BertGenerationEncoder

				# Build sequence
				UpperCAmelCase_     : List[Any]			     =					list(self.big_tokenizer.get_vocab().keys()						)[:10]
				UpperCAmelCase_     : str			     =					" ".join(lowerCAmelCase_						)
				UpperCAmelCase_     : List[str]			     =					self.big_tokenizer.encode_plus(lowerCAmelCase_	,	return_tensors="pt"	,	return_token_type_ids=lowerCAmelCase_						)
				UpperCAmelCase_     : List[str]			     =					self.big_tokenizer.batch_encode_plus(
				    [sequence + " " + sequence]	,	return_tensors="pt"	,	return_token_type_ids=lowerCAmelCase_						)

				UpperCAmelCase_     : Any			     =					BertGenerationConfig()
				UpperCAmelCase_     : List[Any]			     =					BertGenerationEncoder(lowerCAmelCase_						)

				assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

				with torch.no_grad():
							model(**lowerCAmelCase_						)
							model(**lowerCAmelCase_						)





	@slow
	def      _SCREAMING_SNAKE_CASE      (      self					: Any						)						->			Optional[Any]:
				# fmt: off
				UpperCAmelCase_     : Dict			     =					{"input_ids": [[39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114], [448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 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], [484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 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]], "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, 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, 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=lowerCAmelCase_	,	model_name="google/bert_for_seq_generation_L-24_bbc_encoder"	,	revision="c817d1fd1be2ffa69431227a1fe320544943d4db"	,	)











"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_					=      logging.get_logger(__name__)

lowerCamelCase_					=      {
    '''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-430m-pile''': '''https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-1b5-pile''': '''https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-3b-pile''': '''https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-7b-pile''': '''https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-14b-pile''': '''https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-raven-1b5''': '''https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json''',
    '''RWKV/rwkv-raven-3b''': '''https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-7b''': '''https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-14b''': '''https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json''',
}







class 			UpperCamelCase_       (__A     ):
	__magic_name__	      =				'''rwkv'''
	__magic_name__	      =				{'''max_position_embeddings''': '''context_length'''}





	def __init__(      self					: str	,	lowerCAmelCase_					: str=50_277	,	lowerCAmelCase_					: Optional[int]=1_024	,	lowerCAmelCase_					: Optional[int]=4_096	,	lowerCAmelCase_					: Union[str, Any]=32	,	lowerCAmelCase_					: List[Any]=None	,	lowerCAmelCase_					: int=None	,	lowerCAmelCase_					: List[Any]=1e-5	,	lowerCAmelCase_					: str=0	,	lowerCAmelCase_					: Tuple=0	,	lowerCAmelCase_					: int=6	,	lowerCAmelCase_					: Optional[Any]=False	,	lowerCAmelCase_					: Any=True	,	**lowerCAmelCase_					: List[Any]	,	)						->			List[str]:
				UpperCAmelCase_     : Tuple			     =					vocab_size
				UpperCAmelCase_     : List[str]			     =					context_length
				UpperCAmelCase_     : Dict			     =					hidden_size
				UpperCAmelCase_     : Optional[int]			     =					num_hidden_layers
				UpperCAmelCase_     : Optional[int]			     =					attention_hidden_size if attention_hidden_size is not None else hidden_size
				UpperCAmelCase_     : Dict			     =					intermediate_size if intermediate_size is not None else 4 * hidden_size
				UpperCAmelCase_     : Any			     =					layer_norm_epsilon
				UpperCAmelCase_     : List[Any]			     =					rescale_every
				UpperCAmelCase_     : List[str]			     =					use_cache

				UpperCAmelCase_     : List[str]			     =					bos_token_id
				UpperCAmelCase_     : Union[str, Any]			     =					eos_token_id

				super().__init__(
				    tie_word_embeddings=lowerCAmelCase_	,	bos_token_id=lowerCAmelCase_	,	eos_token_id=lowerCAmelCase_	,	**lowerCAmelCase_						)



