
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A							='''▁'''

__A							={'''vocab_file''': '''spiece.model'''}

__A							={
    '''vocab_file''': {'''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'''}
}

__A							={
    '''google/pegasus-xsum''': 5_1_2,
}


__A							=logging.get_logger(__name__)




class        _SCREAMING_SNAKE_CASE	( snake_case_		):
	lowerCAmelCase__   =					VOCAB_FILES_NAMES

	lowerCAmelCase__   =					VOCAB_FILES_NAMES
	lowerCAmelCase__   =					PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase__   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase__   =					['input_ids', 'attention_mask']



	def __init__(       self		,    lowercase		,    lowercase="<pad>"		,    lowercase="</s>"		,    lowercase="<unk>"		,    lowercase="<mask_2>"		,    lowercase="<mask_1>"		,    lowercase=None		,    lowercase=103		,    lowercase = None		,    **lowercase		,    )							->			None:
					lowerCamelCase_         =     offset
					if additional_special_tokens is not None:
									if not isinstance(lowercase		,    lowercase					):
													raise TypeError(
													    f'additional_special_tokens should be of type {type(lowercase					)}, but is'
													    f' {type(lowercase					)}'					)

									lowerCamelCase_         =     (
									    ([mask_token_sent] + additional_special_tokens)
									    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
									    else additional_special_tokens
									)
									# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
									additional_special_tokens_extended += [
									    f'<unk_{i}>' for i in range(len(lowercase					)		,    self.offset - 1					)
									]

									if len(set(lowercase					)					) != len(lowercase					):
													raise ValueError(
													    "Please make sure that the provided additional_special_tokens do not contain an incorrectly"
													    f' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'					)
									lowerCamelCase_         =     additional_special_tokens_extended
					else:
									lowerCamelCase_         =     [mask_token_sent] if mask_token_sent is not None else []
									additional_special_tokens += [f'<unk_{i}>' for i in range(2		,    self.offset					)]

					lowerCamelCase_         =     {} if sp_model_kwargs is None else sp_model_kwargs

					super().__init__(
					    eos_token=lowercase		,    unk_token=lowercase		,    mask_token=lowercase		,    pad_token=lowercase		,    mask_token_sent=lowercase		,    offset=lowercase		,    additional_special_tokens=lowercase		,    sp_model_kwargs=self.sp_model_kwargs		,    **lowercase		,    )
					lowerCamelCase_         =     mask_token_sent
					lowerCamelCase_         =     vocab_file
					lowerCamelCase_         =     spm.SentencePieceProcessor(**self.sp_model_kwargs					)
					self.sp_model.Load(lowercase					)

					# add special tokens to encoder dict
					lowerCamelCase_         =     {
					    0: self.pad_token,
					    1: self.eos_token,
					}

					if self.mask_token_sent is not None:
									self.encoder.update(
									    {
									        2: self.mask_token_sent,
									        3: self.mask_token,
									    }					)

					if self.offset > 0:
									# entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
									# mask_token_sent is already added to list -> so start at 1
									self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1		,    self.offset - 1					)}					)

					lowerCamelCase_         =     {v: k for k, v in self.encoder.items()}



	@property
	def        SCREAMING_SNAKE_CASE_(       self					)							->			int:
					return len(self.sp_model					) + self.offset



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Dict[str, int]:
					lowerCamelCase_         =     {self.convert_ids_to_tokens(lowercase					): i for i in range(self.vocab_size					)}
					vocab.update(self.added_tokens_encoder					)
					return vocab



	def __getstate__(       self					)							->			Optional[int]:
					lowerCamelCase_         =     self.__dict__.copy()
					lowerCamelCase_         =     None
					return state



	def __setstate__(       self		,    lowercase					)							->			str:
					lowerCamelCase_         =     d

					# for backward compatibility
					if not hasattr(self		,    "sp_model_kwargs"					):
									lowerCamelCase_         =     {}

					lowerCamelCase_         =     spm.SentencePieceProcessor(**self.sp_model_kwargs					)
					self.sp_model.Load(self.vocab_file					)



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			List[str]:
					return self.sp_model.encode(lowercase		,    out_type=lowercase					)



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			int:
					if token in self.decoder:
									return self.decoder[token]
					elif token in self.added_tokens_decoder:
									return self.added_tokens_decoder[token]
					lowerCamelCase_         =     self.sp_model.piece_to_id(lowercase					)
					return sp_id + self.offset



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			str:
					if index in self.encoder:
									return self.encoder[index]
					elif index in self.added_tokens_encoder:
									return self.added_tokens_encoder[index]
					else:
									lowerCamelCase_         =     self.sp_model.IdToPiece(index - self.offset					)
					return token



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			Union[str, Any]:
					lowerCamelCase_         =     []
					lowerCamelCase_         =     ""
					for token in tokens:
									# make sure that special tokens are not decoded using sentencepiece model
									if token in self.all_special_tokens:
													out_string += self.sp_model.decode(lowercase					) + token
													lowerCamelCase_         =     []
									else:
													current_sub_tokens.append(lowercase					)
					out_string += self.sp_model.decode(lowercase					)
					return out_string.strip()



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase=False					)							->			str:
					return 1



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			Union[str, Any]:
					lowerCamelCase_         =     set(self.all_special_ids					)  # call it once instead of inside list comp
					all_special_ids.remove(self.unk_token_id					)  # <unk> is only sometimes special

					return [1 if x in all_special_ids else 0 for x in seq]



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase		,    lowercase = None		,    lowercase = False					)							->			List[int]:
					if already_has_special_tokens:
									return self._special_token_mask(lowercase					)
					elif token_ids_a is None:
									return self._special_token_mask(lowercase					) + [1]
					else:
									return self._special_token_mask(token_ids_a + token_ids_a					) + [1]



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase		,    lowercase=None					)							->			List[int]:
					if token_ids_a is None:
									return token_ids_a + [self.eos_token_id]
					# We don't expect to process pairs, but leave the pair logic for API consistency
					return token_ids_a + token_ids_a + [self.eos_token_id]



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase		,    lowercase = None					)							->			Tuple[str]:
					if not os.path.isdir(lowercase					):
									logger.error(f'Vocabulary path ({save_directory}) should be a directory'					)
									return
					lowerCamelCase_         =     os.path.join(
					    lowercase		,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)

					if os.path.abspath(self.vocab_file					) != os.path.abspath(lowercase					) and os.path.isfile(self.vocab_file					):
									copyfile(self.vocab_file		,    lowercase					)
					elif not os.path.isfile(self.vocab_file					):
									with open(lowercase		,    "wb"					) as fi:
													lowerCamelCase_         =     self.sp_model.serialized_model_proto()
													fi.write(lowercase					)

					return (out_vocab_file,)




import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__A							=get_tests_dir('''fixtures/spiece.model''')




@require_sentencepiece
@require_tokenizers
class        _SCREAMING_SNAKE_CASE	( snake_case_     ,			unittest.TestCase		):
	lowerCAmelCase__   =					AlbertTokenizer
	lowerCAmelCase__   =					AlbertTokenizerFast
	lowerCAmelCase__   =					True
	lowerCAmelCase__   =					True
	lowerCAmelCase__   =					True



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Any:
					super().setUp()

					# We have a SentencePiece fixture for testing
					lowerCamelCase_         =     AlbertTokenizer(lowercase					)
					tokenizer.save_pretrained(self.tmpdirname					)



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			str:
					lowerCamelCase_         =     "this is a test"
					lowerCamelCase_         =     "this is a test"
					return input_text, output_text



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Dict:
					lowerCamelCase_         =     "<pad>"
					lowerCamelCase_         =     0

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



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Any:
					lowerCamelCase_         =     list(self.get_tokenizer().get_vocab().keys()					)

					self.assertEqual(vocab_keys[0]		,    "<pad>"					)
					self.assertEqual(vocab_keys[1]		,    "<unk>"					)
					self.assertEqual(vocab_keys[-1]		,    "▁eloquent"					)
					self.assertEqual(len(lowercase					)		,    30000					)



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Union[str, Any]:
					self.assertEqual(self.get_tokenizer().vocab_size		,    30000					)



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Union[str, Any]:
					if not self.test_rust_tokenizer:
									return

					lowerCamelCase_         =     self.get_tokenizer()
					lowerCamelCase_         =     self.get_rust_tokenizer()

					lowerCamelCase_         =     "I was born in 92000, and this is falsé."

					lowerCamelCase_         =     tokenizer.tokenize(lowercase					)
					lowerCamelCase_         =     rust_tokenizer.tokenize(lowercase					)
					self.assertListEqual(lowercase		,    lowercase					)

					lowerCamelCase_         =     tokenizer.encode(lowercase		,    add_special_tokens=lowercase					)
					lowerCamelCase_         =     rust_tokenizer.encode(lowercase		,    add_special_tokens=lowercase					)
					self.assertListEqual(lowercase		,    lowercase					)

					lowerCamelCase_         =     self.get_rust_tokenizer()
					lowerCamelCase_         =     tokenizer.encode(lowercase					)
					lowerCamelCase_         =     rust_tokenizer.encode(lowercase					)
					self.assertListEqual(lowercase		,    lowercase					)



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Optional[Any]:
					lowerCamelCase_         =     AlbertTokenizer(lowercase		,    keep_accents=lowercase					)

					lowerCamelCase_         =     tokenizer.tokenize("This is a test"					)
					self.assertListEqual(lowercase		,    ["▁this", "▁is", "▁a", "▁test"]					)

					self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase					)		,    [48, 25, 21, 1289]					)

					lowerCamelCase_         =     tokenizer.tokenize("I was born in 92000, and this is falsé."					)
					self.assertListEqual(
					    lowercase		,    ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]					)
					lowerCamelCase_         =     tokenizer.convert_tokens_to_ids(lowercase					)
					self.assertListEqual(lowercase		,    [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]					)

					lowerCamelCase_         =     tokenizer.convert_ids_to_tokens(lowercase					)
					self.assertListEqual(
					    lowercase		,    ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]		,    )



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Any:
					lowerCamelCase_         =     AlbertTokenizer(lowercase					)

					lowerCamelCase_         =     tokenizer.encode("sequence builders"					)
					lowerCamelCase_         =     tokenizer.encode("multi-sequence build"					)

					lowerCamelCase_         =     tokenizer.build_inputs_with_special_tokens(lowercase					)
					lowerCamelCase_         =     tokenizer.build_inputs_with_special_tokens(lowercase		,    lowercase					)

					assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
					assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
					    tokenizer.sep_token_id
					]



	@slow
	def        SCREAMING_SNAKE_CASE_(       self					)							->			Optional[Any]:
					# fmt: off
					lowerCamelCase_         =     {"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, 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], [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, 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]], "input_ids": [[2, 21970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 12051, 18, 17, 7103, 2153, 673, 8, 3515, 18684, 8, 4461, 6, 1927, 297, 8, 12060, 2607, 18, 13, 5, 4461, 15, 10538, 38, 8, 135, 15, 822, 58, 15, 993, 10363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 10641, 6, 29, 84, 2512, 2430, 782, 18684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 11712, 15, 7103, 2153, 673, 17, 24883, 9990, 9, 3], [2, 11502, 25, 1006, 20, 782, 8, 11809, 855, 1732, 19393, 18667, 37, 367, 21018, 69, 1854, 34, 11860, 19124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 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], [2, 14, 2231, 886, 2385, 17659, 84, 14, 16792, 1952, 9, 3, 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, 0, 0, 0, 0, 0]], "token_type_ids": [[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, 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, 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, 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=lowercase		,    model_name="albert-base-v2"		,    revision="6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"		,    )


