


import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class     a		(_lowerCAmelCase					,    unittest.TestCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Optional[Any]					  =  RobertaTokenizer
							__UpperCAmelCase   :							Dict					  =  RobertaTokenizerFast
							__UpperCAmelCase   :							List[str]					  =  True
							__UpperCAmelCase   :							List[str]					  =  {'cls_token': '<s>'}

							def    __snake_case (							self	:  Tuple    )     ->   List[Any]:
														super().setUp()

														# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
														__snake_case		:      Any										=       [
														    "l",
														    "o",
														    "w",
														    "e",
														    "r",
														    "s",
														    "t",
														    "i",
														    "d",
														    "n",
														    "\u0120",
														    "\u0120l",
														    "\u0120n",
														    "\u0120lo",
														    "\u0120low",
														    "er",
														    "\u0120lowest",
														    "\u0120newer",
														    "\u0120wider",
														    "<unk>",
														]
														__snake_case		:      List[Any]										=       dict(zip(__lowerCAmelCase   ,     range(len(__lowerCAmelCase    )    )    )    )
														__snake_case		:      List[Any]										=       ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
														__snake_case		:      Dict										=       {"unk_token": "<unk>"}

														__snake_case		:      str										=       os.path.join(self.tmpdirname   ,     VOCAB_FILES_NAMES["vocab_file"]    )
														__snake_case		:      Union[str, Any]										=       os.path.join(self.tmpdirname   ,     VOCAB_FILES_NAMES["merges_file"]    )
														with open(self.vocab_file   ,     "w"   ,     encoding="utf-8"    ) as fp:
																					fp.write(json.dumps(__lowerCAmelCase    ) + "\n"    )
														with open(self.merges_file   ,     "w"   ,     encoding="utf-8"    ) as fp:
																					fp.write("\n".join(__lowerCAmelCase    )    )

							def    __snake_case (							self	:  Union[str, Any]   ,     **lowerCamelCase	:  Any    )     ->   List[Any]:
														kwargs.update(self.special_tokens_map    )
														return self.tokenizer_class.from_pretrained(self.tmpdirname   ,     **__lowerCAmelCase    )

							def    __snake_case (							self	:  List[str]   ,     **lowerCamelCase	:  List[str]    )     ->   Optional[int]:
														kwargs.update(self.special_tokens_map    )
														return RobertaTokenizerFast.from_pretrained(self.tmpdirname   ,     **__lowerCAmelCase    )

							def    __snake_case (							self	:  List[Any]   ,     lowerCamelCase	:  Tuple    )     ->   Optional[Any]:
														__snake_case		:      Optional[int]										=       "lower newer"
														__snake_case		:      Dict										=       "lower newer"
														return input_text, output_text

							def    __snake_case (							self	:  Dict    )     ->   Optional[Any]:
														__snake_case		:      int										=       self.tokenizer_class(self.vocab_file   ,     self.merges_file   ,     **self.special_tokens_map    )
														__snake_case		:      List[Any]										=       "lower newer"
														__snake_case		:      Optional[int]										=       ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
														__snake_case		:      Dict										=       tokenizer.tokenize(__lowerCAmelCase    )  # , add_prefix_space=True)
														self.assertListEqual(__lowerCAmelCase   ,     __lowerCAmelCase    )

														__snake_case		:      int										=       tokens + [tokenizer.unk_token]
														__snake_case		:      Any										=       [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
														self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase    )   ,     __lowerCAmelCase    )

							def    __snake_case (							self	:  Union[str, Any]    )     ->   Union[str, Any]:
														__snake_case		:      str										=       self.get_tokenizer()

														self.assertListEqual(tokenizer.encode("Hello world!"   ,     add_special_tokens=__lowerCAmelCase    )   ,     [0, 31414, 232, 328, 2]    )
														self.assertListEqual(
														    tokenizer.encode("Hello world! cécé herlolip 418"   ,     add_special_tokens=__lowerCAmelCase    )   ,     [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]   ,     )

							@slow
							def    __snake_case (							self	:  Union[str, Any]    )     ->   Tuple:
														__snake_case		:      Dict										=       self.tokenizer_class.from_pretrained("roberta-base"    )

														__snake_case		:      Union[str, Any]										=       tokenizer.encode("sequence builders"   ,     add_special_tokens=__lowerCAmelCase    )
														__snake_case		:      str										=       tokenizer.encode("multi-sequence build"   ,     add_special_tokens=__lowerCAmelCase    )

														__snake_case		:      Optional[int]										=       tokenizer.encode(
														    "sequence builders"   ,     add_special_tokens=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase    )
														__snake_case		:      Union[str, Any]										=       tokenizer.encode(
														    "sequence builders"   ,     "multi-sequence build"   ,     add_special_tokens=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase    )

														__snake_case		:      str										=       tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase    )
														__snake_case		:      str										=       tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase   ,     __lowerCAmelCase    )

														assert encoded_sentence == encoded_text_from_decode
														assert encoded_pair == encoded_pair_from_decode

							def    __snake_case (							self	:  List[str]    )     ->   int:
														__snake_case		:      Any										=       self.get_tokenizer()

														__snake_case		:      List[str]										=       "Encode this sequence."
														__snake_case		:      List[Any]										=       tokenizer.byte_encoder[" ".encode("utf-8"    )[0]]

														# Testing encoder arguments
														__snake_case		:      Dict										=       tokenizer.encode(__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase    )
														__snake_case		:      List[str]										=       tokenizer.convert_ids_to_tokens(encoded[0]    )[0]
														self.assertNotEqual(__lowerCAmelCase   ,     __lowerCAmelCase    )

														__snake_case		:      Optional[Any]										=       tokenizer.encode(__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase    )
														__snake_case		:      Any										=       tokenizer.convert_ids_to_tokens(encoded[0]    )[0]
														self.assertEqual(__lowerCAmelCase   ,     __lowerCAmelCase    )

														tokenizer.add_special_tokens({"bos_token": "<s>"}    )
														__snake_case		:      Dict										=       tokenizer.encode(__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
														__snake_case		:      Dict										=       tokenizer.convert_ids_to_tokens(encoded[1]    )[0]
														self.assertNotEqual(__lowerCAmelCase   ,     __lowerCAmelCase    )

														# Testing spaces after special tokens
														__snake_case		:      Dict										=       "<mask>"
														tokenizer.add_special_tokens(
														    {"mask_token": AddedToken(__lowerCAmelCase   ,     lstrip=__lowerCAmelCase   ,     rstrip=__lowerCAmelCase    )}    )  # mask token has a left space
														__snake_case		:      str										=       tokenizer.convert_tokens_to_ids(__lowerCAmelCase    )

														__snake_case		:      int										=       "Encode <mask> sequence"
														__snake_case		:      Optional[int]										=       "Encode <mask>sequence"

														__snake_case		:      Optional[int]										=       tokenizer.encode(__lowerCAmelCase    )
														__snake_case		:      Optional[int]										=       encoded.index(__lowerCAmelCase    )
														__snake_case		:      Optional[Any]										=       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]    )[0]
														self.assertEqual(__lowerCAmelCase   ,     __lowerCAmelCase    )

														__snake_case		:      List[Any]										=       tokenizer.encode(__lowerCAmelCase    )
														__snake_case		:      Dict										=       encoded.index(__lowerCAmelCase    )
														__snake_case		:      Tuple										=       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]    )[0]
														self.assertNotEqual(__lowerCAmelCase   ,     __lowerCAmelCase    )

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

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



														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'    ):
																												__snake_case		:      int										=       self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase   ,     **__lowerCAmelCase    )
																												__snake_case		:      List[str]										=       self.tokenizer_class.from_pretrained(__lowerCAmelCase   ,     **__lowerCAmelCase    )
																												__snake_case		:      Dict										=       "A, <mask> AllenNLP sentence."
																												__snake_case		:      List[str]										=       tokenizer_r.encode_plus(__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase   ,     return_token_type_ids=__lowerCAmelCase    )
																												__snake_case		:      int										=       tokenizer_p.encode_plus(__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase   ,     return_token_type_ids=__lowerCAmelCase    )

																												# token_type_ids should put 0 everywhere
																												self.assertEqual(sum(tokens_r["token_type_ids"]    )   ,     sum(tokens_p["token_type_ids"]    )    )

																												# attention_mask should put 1 everywhere, so sum over length should be 1
																												self.assertEqual(
																												    sum(tokens_r["attention_mask"]    ) / len(tokens_r["attention_mask"]    )   ,     sum(tokens_p["attention_mask"]    ) / len(tokens_p["attention_mask"]    )   ,     )

																												__snake_case		:      Optional[int]										=       tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]    )
																												__snake_case		:      List[Any]										=       tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]    )

																												# Rust correctly handles the space before the mask while python doesnt
																												self.assertSequenceEqual(tokens_p["input_ids"]   ,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]    )
																												self.assertSequenceEqual(tokens_r["input_ids"]   ,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]    )

																												self.assertSequenceEqual(
																												    __lowerCAmelCase   ,     ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]    )
																												self.assertSequenceEqual(
																												    __lowerCAmelCase   ,     ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]    )

							def    __snake_case (							self	:  int    )     ->   Any:



														for trim_offsets, add_prefix_space in itertools.product([True, False]   ,     repeat=2    ):
																					__snake_case		:      List[Any]										=       self.rust_tokenizer_class.from_pretrained(
																					    self.tmpdirname   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )

																					__snake_case		:      Union[str, Any]										=       json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()    )
																					__snake_case		:      Optional[Any]										=       json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()    )

																					self.assertEqual(pre_tokenizer_state["add_prefix_space"]   ,     __lowerCAmelCase    )

																					self.assertEqual(post_processor_state["add_prefix_space"]   ,     __lowerCAmelCase    )
																					self.assertEqual(post_processor_state["trim_offsets"]   ,     __lowerCAmelCase    )






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



														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'    ):
																												__snake_case		:      Optional[int]										=       "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																												__snake_case		:      Optional[Any]										=       F'{text_of_1_token} {text_of_1_token}'

																												__snake_case		:      List[Any]										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      Tuple										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (len(__lowerCAmelCase    ) + 1, len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )

																												__snake_case		:      int										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      List[str]										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (len(__lowerCAmelCase    ) + 1, len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )

																												__snake_case		:      Union[str, Any]										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      str										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (len(__lowerCAmelCase    ), len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )

																												__snake_case		:      Dict										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      Optional[int]										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (len(__lowerCAmelCase    ), len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )

																												__snake_case		:      List[Any]										=       F' {text}'

																												# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																												#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																												# )
																												# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																												# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																												# self.assertEqual(
																												#     encoding.offset_mapping[1],
																												#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																												# )

																												__snake_case		:      Tuple										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      Union[str, Any]										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (1, 1 + len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (1 + len(__lowerCAmelCase    ) + 1, 1 + len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )

																												__snake_case		:      Optional[Any]										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      Dict										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (0, 1 + len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (1 + len(__lowerCAmelCase    ), 1 + len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )

																												__snake_case		:      Optional[Any]										=       self.rust_tokenizer_class.from_pretrained(
																												    __lowerCAmelCase   ,     use_fast=__lowerCAmelCase   ,     add_prefix_space=__lowerCAmelCase   ,     trim_offsets=__lowerCAmelCase    )
																												__snake_case		:      Optional[Any]										=       tokenizer_r(__lowerCAmelCase   ,     return_offsets_mapping=__lowerCAmelCase   ,     add_special_tokens=__lowerCAmelCase    )
																												self.assertEqual(encoding.offset_mapping[0]   ,     (0, 1 + len(__lowerCAmelCase    ))    )
																												self.assertEqual(
																												    encoding.offset_mapping[1]   ,     (1 + len(__lowerCAmelCase    ), 1 + len(__lowerCAmelCase    ) + 1 + len(__lowerCAmelCase    ))   ,     )





import logging

from transformers.configuration_utils import PretrainedConfig


_snake_case					:		Optional[Any]      =    logging.getLogger(__name__)

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Tuple					  =  "masked_bert"

							def __init__(							self	:  Optional[int]   ,     lowerCamelCase	:  Any=30522   ,     lowerCamelCase	:  Tuple=768   ,     lowerCamelCase	:  str=12   ,     lowerCamelCase	:  Dict=12   ,     lowerCamelCase	:  List[str]=3072   ,     lowerCamelCase	:  List[str]="gelu"   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  List[Any]=512   ,     lowerCamelCase	:  int=2   ,     lowerCamelCase	:  str=0.02   ,     lowerCamelCase	:  List[str]=1E-12   ,     lowerCamelCase	:  Any=0   ,     lowerCamelCase	:  Dict="topK"   ,     lowerCamelCase	:  List[Any]="constant"   ,     lowerCamelCase	:  Dict=0.0   ,     **lowerCamelCase	:  List[Any]   ,     )     ->   Dict:
														super().__init__(pad_token_id=lowerCamelCase   ,     **lowerCamelCase    )

														__snake_case		:      Optional[Any]										=       vocab_size
														__snake_case		:      Optional[int]										=       hidden_size
														__snake_case		:      Tuple										=       num_hidden_layers
														__snake_case		:      Union[str, Any]										=       num_attention_heads
														__snake_case		:      Optional[Any]										=       hidden_act
														__snake_case		:      str										=       intermediate_size
														__snake_case		:      Tuple										=       hidden_dropout_prob
														__snake_case		:      Dict										=       attention_probs_dropout_prob
														__snake_case		:      List[str]										=       max_position_embeddings
														__snake_case		:      Union[str, Any]										=       type_vocab_size
														__snake_case		:      Any										=       initializer_range
														__snake_case		:      str										=       layer_norm_eps
														__snake_case		:      str										=       pruning_method
														__snake_case		:      int										=       mask_init
														__snake_case		:      Any										=       mask_scale

