



"""simple docstring"""






import unittest

import numpy as np

from transformers import is_flax_available
from transformers.testing_utils import require_flax

from ..test_modeling_flax_common import ids_tensor


if is_flax_available():
	import jax
	import jax.numpy as jnp

	from transformers.generation import (
	    FlaxForcedBOSTokenLogitsProcessor,
	    FlaxForcedEOSTokenLogitsProcessor,
	    FlaxLogitsProcessorList,
	    FlaxMinLengthLogitsProcessor,
	    FlaxTemperatureLogitsWarper,
	    FlaxTopKLogitsWarper,
	    FlaxTopPLogitsWarper,
	)



@require_flax
class     A__     (						unittest.TestCase							):




	'''simple docstring'''





	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any] ,    _SCREAMING_SNAKE_CASE:	int ,    _SCREAMING_SNAKE_CASE:	int)       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						int				= jnp.ones((batch_size, length)) / length
				return scores

	def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> Tuple:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= None
				__lowerCAmelCase   :						Dict				= 20

				__lowerCAmelCase   :						List[Any]				= self._get_uniform_logits(batch_size=2 ,    length=_SCREAMING_SNAKE_CASE)

				# tweak scores to not be uniform anymore
				__lowerCAmelCase   :						Tuple				= scores.at[1, 5].set((1 / length) + 0.1)  # peak, 1st batch
				__lowerCAmelCase   :						Union[str, Any]				= scores.at[1, 10].set((1 / length) - 0.4)  # valley, 1st batch

				# compute softmax
				__lowerCAmelCase   :						Dict				= jax.nn.softmax(_SCREAMING_SNAKE_CASE ,    axis=-1)

				__lowerCAmelCase   :						Any				= FlaxTemperatureLogitsWarper(temperature=0.5)
				__lowerCAmelCase   :						Union[str, Any]				= FlaxTemperatureLogitsWarper(temperature=1.3)

				__lowerCAmelCase   :						List[Any]				= jax.nn.softmax(temp_dist_warper_sharper(_SCREAMING_SNAKE_CASE ,    scores.copy() ,    cur_len=_SCREAMING_SNAKE_CASE) ,    axis=-1)
				__lowerCAmelCase   :						Optional[Any]				= jax.nn.softmax(temp_dist_warper_smoother(_SCREAMING_SNAKE_CASE ,    scores.copy() ,    cur_len=_SCREAMING_SNAKE_CASE) ,    axis=-1)

				# uniform distribution stays uniform
				self.assertTrue(jnp.allclose(probs[0, :] ,    warped_prob_sharp[0, :] ,    atol=1e-3))
				self.assertTrue(jnp.allclose(probs[0, :] ,    warped_prob_smooth[0, :] ,    atol=1e-3))

				# sharp peaks get higher, valleys get lower
				self.assertLess(probs[1, :].max() ,    warped_prob_sharp[1, :].max())
				self.assertGreater(probs[1, :].min() ,    warped_prob_sharp[1, :].min())

				# smooth peaks get lower, valleys get higher
				self.assertGreater(probs[1, :].max() ,    warped_prob_smooth[1, :].max())
				self.assertLess(probs[1, :].min() ,    warped_prob_smooth[1, :].min())

	def 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= None
				__lowerCAmelCase   :						Optional[int]				= 10
				__lowerCAmelCase   :						Union[str, Any]				= 2

				# create ramp distribution
				__lowerCAmelCase   :						List[str]				= np.broadcast_to(np.arange(_SCREAMING_SNAKE_CASE)[None, :] ,    (batch_size, vocab_size)).copy()
				__lowerCAmelCase   :						Optional[Any]				= ramp_logits[1:, : vocab_size // 2] + vocab_size

				__lowerCAmelCase   :						Dict				= FlaxTopKLogitsWarper(3)

				__lowerCAmelCase   :						List[str]				= top_k_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# check that correct tokens are filtered
				self.assertListEqual(jnp.isinf(scores[0]).tolist() ,    7 * [True] + 3 * [False])
				self.assertListEqual(jnp.isinf(scores[1]).tolist() ,    2 * [True] + 3 * [False] + 5 * [True])

				# check special case
				__lowerCAmelCase   :						Union[str, Any]				= 5
				__lowerCAmelCase   :						Any				= FlaxTopKLogitsWarper(top_k=1 ,    filter_value=0.0 ,    min_tokens_to_keep=3)

				__lowerCAmelCase   :						List[Any]				= np.broadcast_to(np.arange(_SCREAMING_SNAKE_CASE)[None, :] ,    (batch_size, length)).copy()
				__lowerCAmelCase   :						List[str]				= top_k_warp_safety_check(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# min_tokens overwrites k: 3 tokens are kept => 2 tokens are nullified
				self.assertListEqual((scores == 0.0).sum(axis=-1).tolist() ,    [2, 2])

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> Any:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= None
				__lowerCAmelCase   :						Optional[int]				= 10
				__lowerCAmelCase   :						Optional[int]				= 2

				# create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
				__lowerCAmelCase   :						Optional[Any]				= np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.15, 0.3, 0.3, 0.25]]))

				__lowerCAmelCase   :						Dict				= FlaxTopPLogitsWarper(0.8)
				__lowerCAmelCase   :						Dict				= np.exp(top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE))

				# dist should be filtered to keep min num values so that sum is >= top_p
				# exp (-inf) => 0
				__lowerCAmelCase   :						Dict				= np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]])
				self.assertTrue(np.allclose(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    atol=1e-3))

				# check edge cases with negative and extreme logits
				__lowerCAmelCase   :						int				= np.broadcast_to(np.arange(_SCREAMING_SNAKE_CASE)[None, :] ,    (batch_size, vocab_size)).copy() - (
				    vocab_size // 2
				)

				# make ramp_logits more extreme
				__lowerCAmelCase   :						List[str]				= ramp_logits[1] * 100.0

				# make sure at least 2 tokens are kept
				__lowerCAmelCase   :						Optional[Any]				= FlaxTopPLogitsWarper(0.9 ,    min_tokens_to_keep=2 ,    filter_value=0.0)
				__lowerCAmelCase   :						Tuple				= top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# first batch should keep three tokens, second batch would keep only 1, but due to `min_tokens_to_keep=2` keeps 2.
				self.assertListEqual((filtered_dist != 0.0).sum(axis=-1).tolist() ,    [3, 2])

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> int:

				"""simple docstring"""

				__lowerCAmelCase   :						str				= 20
				__lowerCAmelCase   :						Dict				= 4
				__lowerCAmelCase   :						Optional[int]				= 0

				__lowerCAmelCase   :						Tuple				= FlaxMinLengthLogitsProcessor(min_length=10 ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				# check that min length is applied at length 5
				__lowerCAmelCase   :						Optional[int]				= ids_tensor((batch_size, 20) ,    vocab_size=20)
				__lowerCAmelCase   :						Any				= 5
				__lowerCAmelCase   :						Optional[Any]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= min_dist_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist() ,    4 * [-float("inf")])

				# check that min length is not applied anymore at length 15
				__lowerCAmelCase   :						Optional[int]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[str]				= 15
				__lowerCAmelCase   :						Tuple				= min_dist_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertFalse(jnp.isinf(_SCREAMING_SNAKE_CASE).any())

	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any])       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[Any]				= 20
				__lowerCAmelCase   :						List[Any]				= 4
				__lowerCAmelCase   :						List[Any]				= 0

				__lowerCAmelCase   :						Optional[Any]				= FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_SCREAMING_SNAKE_CASE)

				# check that all scores are -inf except the bos_token_id score
				__lowerCAmelCase   :						Any				= ids_tensor((batch_size, 1) ,    vocab_size=20)
				__lowerCAmelCase   :						int				= 1
				__lowerCAmelCase   :						str				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[int]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertTrue(jnp.isneginf(scores[:, bos_token_id + 1 :]).all())
				self.assertListEqual(scores[:, bos_token_id].tolist() ,    4 * [0])  # score for bos_token_id shold be zero

				# check that bos_token_id is not forced if current length is greater than 1
				__lowerCAmelCase   :						Dict				= 3
				__lowerCAmelCase   :						List[str]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[int]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertFalse(jnp.isinf(_SCREAMING_SNAKE_CASE).any())

	def 							_SCREAMING_SNAKE_CASE     (  self:	Optional[Any])       -> Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= 20
				__lowerCAmelCase   :						List[str]				= 4
				__lowerCAmelCase   :						Optional[Any]				= 0
				__lowerCAmelCase   :						List[str]				= 5

				__lowerCAmelCase   :						Any				= FlaxForcedEOSTokenLogitsProcessor(max_length=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				# check that all scores are -inf except the eos_token_id when max_length is reached
				__lowerCAmelCase   :						int				= ids_tensor((batch_size, 4) ,    vocab_size=20)
				__lowerCAmelCase   :						Tuple				= 4
				__lowerCAmelCase   :						str				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertTrue(jnp.isneginf(scores[:, eos_token_id + 1 :]).all())
				self.assertListEqual(scores[:, eos_token_id].tolist() ,    4 * [0])  # score for eos_token_id should be zero

				# check that eos_token_id is not forced if max_length is not reached
				__lowerCAmelCase   :						Dict				= 3
				__lowerCAmelCase   :						int				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertFalse(jnp.isinf(_SCREAMING_SNAKE_CASE).any())

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> str:

				"""simple docstring"""

				__lowerCAmelCase   :						Any				= 4
				__lowerCAmelCase   :						List[str]				= 10
				__lowerCAmelCase   :						Tuple				= 15
				__lowerCAmelCase   :						List[Any]				= 2
				__lowerCAmelCase   :						List[str]				= 1
				__lowerCAmelCase   :						List[str]				= 15

				# dummy input_ids and scores
				__lowerCAmelCase   :						Any				= ids_tensor((batch_size, sequence_length) ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Dict				= input_ids.copy()

				__lowerCAmelCase   :						Any				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= scores.copy()

				# instantiate all dist processors
				__lowerCAmelCase   :						List[str]				= FlaxTemperatureLogitsWarper(temperature=0.5)
				__lowerCAmelCase   :						Dict				= FlaxTopKLogitsWarper(3)
				__lowerCAmelCase   :						Any				= FlaxTopPLogitsWarper(0.8)

				# instantiate all logits processors
				__lowerCAmelCase   :						List[Any]				= FlaxMinLengthLogitsProcessor(min_length=10 ,    eos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= FlaxForcedEOSTokenLogitsProcessor(max_length=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						str				= 10

				# no processor list
				__lowerCAmelCase   :						Tuple				= temp_dist_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= top_k_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Tuple				= top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= min_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Dict				= bos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= eos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# with processor list
				__lowerCAmelCase   :						Optional[int]				= FlaxLogitsProcessorList(
				    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
				__lowerCAmelCase   :						Dict				= processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# scores should be equal
				self.assertTrue(jnp.allclose(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    atol=1e-3))

				# input_ids should never be changed
				self.assertListEqual(input_ids.tolist() ,    input_ids_comp.tolist())







	def 							_SCREAMING_SNAKE_CASE     (  self:	Tuple)       -> Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[Any]				= 4
				__lowerCAmelCase   :						Optional[Any]				= 10
				__lowerCAmelCase   :						Optional[Any]				= 15
				__lowerCAmelCase   :						Dict				= 2
				__lowerCAmelCase   :						List[str]				= 1
				__lowerCAmelCase   :						Union[str, Any]				= 15

				# dummy input_ids and scores
				__lowerCAmelCase   :						Dict				= ids_tensor((batch_size, sequence_length) ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= input_ids.copy()

				__lowerCAmelCase   :						Union[str, Any]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= scores.copy()

				# instantiate all dist processors
				__lowerCAmelCase   :						Optional[Any]				= FlaxTemperatureLogitsWarper(temperature=0.5)
				__lowerCAmelCase   :						Optional[int]				= FlaxTopKLogitsWarper(3)
				__lowerCAmelCase   :						Optional[int]				= FlaxTopPLogitsWarper(0.8)

				# instantiate all logits processors
				__lowerCAmelCase   :						List[str]				= FlaxMinLengthLogitsProcessor(min_length=10 ,    eos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Any				= FlaxForcedEOSTokenLogitsProcessor(max_length=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Dict				= 10

				# no processor list
				def run_no_processor_list(_SCREAMING_SNAKE_CASE:	Optional[Any] ,    _SCREAMING_SNAKE_CASE:	Tuple ,    _SCREAMING_SNAKE_CASE:	int):
							__lowerCAmelCase   :						Dict				= temp_dist_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Any				= top_k_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Optional[int]				= top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Tuple				= min_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Tuple				= bos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Optional[Any]				= eos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							return scores

				# with processor list
				def run_processor_list(_SCREAMING_SNAKE_CASE:	Optional[Any] ,    _SCREAMING_SNAKE_CASE:	str ,    _SCREAMING_SNAKE_CASE:	List[Any]):
							__lowerCAmelCase   :						Optional[Any]				= FlaxLogitsProcessorList(
							    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
							__lowerCAmelCase   :						Optional[int]				= processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							return scores

				__lowerCAmelCase   :						List[Any]				= jax.jit(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= jax.jit(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Optional[int]				= jitted_run_no_processor_list(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Any				= jitted_run_processor_list(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

				# scores should be equal
				self.assertTrue(jnp.allclose(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    atol=1e-3))

				# input_ids should never be changed
				self.assertListEqual(input_ids.tolist() ,    input_ids_comp.tolist())





"""simple docstring"""






import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english



@require_tokenizers
class     A__     (						__SCREAMING_SNAKE_CASE						,	unittest.TestCase							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			RoCBertTokenizer
	SCREAMING_SNAKE_CASE					   =			None
	SCREAMING_SNAKE_CASE					   =			False
	SCREAMING_SNAKE_CASE					   =			True
	SCREAMING_SNAKE_CASE					   =			filter_non_english

	def 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> Optional[Any]:

				"""simple docstring"""

				super().setUp()

				__lowerCAmelCase   :						Dict				= ["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "你", "好", "是", "谁", "a", "b", "c", "d"]
				__lowerCAmelCase   :						str				= {}
				__lowerCAmelCase   :						List[Any]				= {}
				for i, value in enumerate(_SCREAMING_SNAKE_CASE):
							__lowerCAmelCase   :						int				= i
							__lowerCAmelCase   :						List[str]				= i
				__lowerCAmelCase   :						int				= os.path.join(self.tmpdirname ,    VOCAB_FILES_NAMES["vocab_file"])
				__lowerCAmelCase   :						Union[str, Any]				= os.path.join(self.tmpdirname ,    VOCAB_FILES_NAMES["word_shape_file"])
				__lowerCAmelCase   :						Any				= os.path.join(self.tmpdirname ,    VOCAB_FILES_NAMES["word_pronunciation_file"])
				with open(self.vocab_file ,    "w" ,    encoding="utf-8") as vocab_writer:
							vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
				with open(self.word_shape_file ,    "w" ,    encoding="utf-8") as word_shape_writer:
							json.dump(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    ensure_ascii=_SCREAMING_SNAKE_CASE)
				with open(self.word_pronunciation_file ,    "w" ,    encoding="utf-8") as word_pronunciation_writer:
							json.dump(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    ensure_ascii=_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> str:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= self.tokenizer_class(self.vocab_file ,    self.word_shape_file ,    self.word_pronunciation_file)

				__lowerCAmelCase   :						List[Any]				= tokenizer.tokenize("你好[SEP]你是谁")
				self.assertListEqual(_SCREAMING_SNAKE_CASE ,    ["你", "好", "[SEP]", "你", "是", "谁"])
				self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE) ,    [5, 6, 2, 5, 7, 8])
				self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(_SCREAMING_SNAKE_CASE) ,    [5, 6, 2, 5, 7, 8])
				self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(_SCREAMING_SNAKE_CASE) ,    [5, 6, 2, 5, 7, 8])

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> int:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= RoCBertBasicTokenizer()

				self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz") ,    ["ah", "\u535A", "\u63A8", "zz"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	Optional[Any])       -> Tuple:

				"""simple docstring"""

				__lowerCAmelCase   :						int				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ") ,    ["hello", "!", "how", "are", "you", "?"])
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo") ,    ["hello"])

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

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[int]				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE ,    strip_accents=_SCREAMING_SNAKE_CASE)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ") ,    ["hällo", "!", "how", "are", "you", "?"])
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo") ,    ["h\u00E9llo"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	Tuple)       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase   :						Tuple				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE ,    strip_accents=_SCREAMING_SNAKE_CASE)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ") ,    ["hallo", "!", "how", "are", "you", "?"])
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo") ,    ["hello"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ") ,    ["hallo", "!", "how", "are", "you", "?"])
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo") ,    ["hello"])

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

				"""simple docstring"""

				__lowerCAmelCase   :						Any				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE)

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

	def 							_SCREAMING_SNAKE_CASE     (  self:	Optional[Any])       -> Tuple:

				"""simple docstring"""

				__lowerCAmelCase   :						str				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE ,    strip_accents=_SCREAMING_SNAKE_CASE)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ") ,    ["HäLLo", "!", "how", "Are", "yoU", "?"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	Any)       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase   :						str				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE ,    strip_accents=_SCREAMING_SNAKE_CASE)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ") ,    ["HaLLo", "!", "how", "Are", "yoU", "?"])

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

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[Any]				= RoCBertBasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE ,    never_split=["[UNK]"])

				self.assertListEqual(
				    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]") ,    ["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[str])       -> Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						str				= ["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

				__lowerCAmelCase   :						Union[str, Any]				= {}
				for i, token in enumerate(_SCREAMING_SNAKE_CASE):
							__lowerCAmelCase   :						Optional[int]				= i
				__lowerCAmelCase   :						Any				= RoCBertWordpieceTokenizer(vocab=_SCREAMING_SNAKE_CASE ,    unk_token="[UNK]")

				self.assertListEqual(tokenizer.tokenize("") ,    [])

				self.assertListEqual(tokenizer.tokenize("unwanted running") ,    ["un", "##want", "##ed", "runn", "##ing"])

				self.assertListEqual(tokenizer.tokenize("unwantedX running") ,    ["[UNK]", "runn", "##ing"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> int:

				"""simple docstring"""

				self.assertTrue(_is_whitespace(" "))
				self.assertTrue(_is_whitespace("\t"))
				self.assertTrue(_is_whitespace("\r"))
				self.assertTrue(_is_whitespace("\n"))
				self.assertTrue(_is_whitespace("\u00A0"))

				self.assertFalse(_is_whitespace("A"))
				self.assertFalse(_is_whitespace("-"))

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> Dict:

				"""simple docstring"""

				self.assertTrue(_is_control("\u0005"))

				self.assertFalse(_is_control("A"))
				self.assertFalse(_is_control(" "))
				self.assertFalse(_is_control("\t"))
				self.assertFalse(_is_control("\r"))

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> str:

				"""simple docstring"""

				self.assertTrue(_is_punctuation("-"))
				self.assertTrue(_is_punctuation("$"))
				self.assertTrue(_is_punctuation("`"))
				self.assertTrue(_is_punctuation("."))

				self.assertFalse(_is_punctuation("A"))
				self.assertFalse(_is_punctuation(" "))

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> Tuple:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= self.get_tokenizer()

				# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
				self.assertListEqual([tokenizer.tokenize(_SCREAMING_SNAKE_CASE) for t in ["Test", "\xad", "test"]] ,    [["[UNK]"], [], ["[UNK]"]])

				if self.test_rust_tokenizer:
							__lowerCAmelCase   :						List[str]				= self.get_rust_tokenizer()
							self.assertListEqual(
							    [rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE) for t in ["Test", "\xad", "test"]] ,    [["[UNK]"], [], ["[UNK]"]])

	def 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> List[str]:

				"""simple docstring"""

				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
										__lowerCAmelCase   :						List[Any]				= self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						Optional[Any]				= F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
										__lowerCAmelCase   :						List[Any]				= tokenizer_r.encode_plus(
										    _SCREAMING_SNAKE_CASE ,    return_attention_mask=_SCREAMING_SNAKE_CASE ,    return_token_type_ids=_SCREAMING_SNAKE_CASE ,    return_offsets_mapping=_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE ,    )

										__lowerCAmelCase   :						Optional[Any]				= tokenizer_r.do_lower_case if hasattr(_SCREAMING_SNAKE_CASE ,    "do_lower_case") else False
										__lowerCAmelCase   :						int				= (
										    [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), "A"),
										        ((1, 2), ","),
										        ((3, 5), "na"),
										        ((5, 6), "##ï"),
										        ((6, 8), "##ve"),
										        ((9, 15), tokenizer_r.mask_token),
										        ((16, 21), "Allen"),
										        ((21, 23), "##NL"),
										        ((23, 24), "##P"),
										        ((25, 33), "sentence"),
										        ((33, 34), "."),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										    if not do_lower_case
										    else [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), "a"),
										        ((1, 2), ","),
										        ((3, 8), "naive"),
										        ((9, 15), tokenizer_r.mask_token),
										        ((16, 21), "allen"),
										        ((21, 23), "##nl"),
										        ((23, 24), "##p"),
										        ((25, 33), "sentence"),
										        ((33, 34), "."),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										)

										self.assertEqual(
										    [e[1] for e in expected_results] ,    tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]))
										self.assertEqual([e[0] for e in expected_results] ,    tokens["offset_mapping"])

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[str])       -> Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= ["的", "人", "有"]
				__lowerCAmelCase   :						Tuple				= "".join(_SCREAMING_SNAKE_CASE)
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
										__lowerCAmelCase   :						Any				= True
										__lowerCAmelCase   :						Dict				= self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						int				= self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						Dict				= tokenizer_p.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						List[Any]				= tokenizer_r.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						Optional[Any]				= tokenizer_r.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						Optional[int]				= tokenizer_p.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE)

										# it is expected that each Chinese character is not preceded by "##"
										self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
										self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						int				= False
										__lowerCAmelCase   :						List[Any]				= self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						List[Any]				= self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						Any				= tokenizer_r.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						List[Any]				= tokenizer_p.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						int				= tokenizer_r.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						Dict				= tokenizer_p.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE)

										# it is expected that only the first Chinese character is not preceded by "##".
										__lowerCAmelCase   :						Union[str, Any]				= [
										    F"""##{token}""" if idx != 0 else token for idx, token in enumerate(_SCREAMING_SNAKE_CASE)
										]
										self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
										self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

	@slow
	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> str:

				"""simple docstring"""

				__lowerCAmelCase   :						Tuple				= self.tokenizer_class(self.vocab_file ,    self.word_shape_file ,    self.word_pronunciation_file)

				__lowerCAmelCase   :						List[Any]				= tokenizer.encode("你好" ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= tokenizer.encode("你是谁" ,    add_special_tokens=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						List[str]				= tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

				assert encoded_sentence == [1] + text + [2]
				assert encoded_pair == [1] + text + [2] + text_a + [2]







	def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						Union[str, Any]				= self.get_tokenizers(do_lower_case=_SCREAMING_SNAKE_CASE)
				for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""):
										__lowerCAmelCase   :						Dict				= "你好，你是谁"
										__lowerCAmelCase   :						Tuple				= tokenizer.tokenize(_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						Optional[Any]				= tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						List[str]				= tokenizer.convert_tokens_to_shape_ids(_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						str				= tokenizer.convert_tokens_to_pronunciation_ids(_SCREAMING_SNAKE_CASE)
										__lowerCAmelCase   :						int				= tokenizer.prepare_for_model(
										    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)

										__lowerCAmelCase   :						Union[str, Any]				= tokenizer.encode_plus(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)

										self.assertEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)