


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


__snake_case             =   logging.get_logger(__name__)

__snake_case             =   """▁"""

__snake_case             =   {"""vocab_file""": """sentencepiece.bpe.model"""}

__snake_case             =   {
    """vocab_file""": {
        """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model""",
    }
}

__snake_case             =   {
    """facebook/xglm-564M""": 2048,
}







class _lowerCAmelCase    (				A_     ):
   __UpperCAmelCase			:	Any							  =  VOCAB_FILES_NAMES
   __UpperCAmelCase			:	Tuple							  =  PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase			:	Optional[int]							  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase			:	Optional[Any]							  =  ["input_ids", "attention_mask"]







   def __init__(     self						,     UpperCamelCase__						,     UpperCamelCase__="<s>"						,     UpperCamelCase__="</s>"						,     UpperCamelCase__="</s>"						,     UpperCamelCase__="<s>"						,     UpperCamelCase__="<unk>"						,     UpperCamelCase__="<pad>"						,     UpperCamelCase__ = None						,     **UpperCamelCase__						,     )     ->		None:

       '''simple docstring'''




       snake_case   :				List[Any]				 =   {} if sp_model_kwargs is None else sp_model_kwargs

       # Compatibility with the original tokenizer
       snake_case   :				Optional[int]				 =   7
       snake_case   :				List[str]				 =   [F'<madeupword{i}>' for i in range(self.num_madeup_words						)]

       snake_case   :				Union[str, Any]				 =   kwargs.get("additional_special_tokens"						,     []						)
       kwargs["additional_special_tokens"] += [
           word for word in madeup_words if word not in kwargs["additional_special_tokens"]
       ]

       super().__init__(
           bos_token=snake_case__						,     eos_token=snake_case__						,     unk_token=snake_case__						,     sep_token=snake_case__						,     cls_token=snake_case__						,     pad_token=snake_case__						,     sp_model_kwargs=self.sp_model_kwargs						,     **snake_case__						,     )

       snake_case   :				Any				 =   spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(str(snake_case__						)						)
       snake_case   :				str				 =   vocab_file

       # Original fairseq vocab and spm vocab must be "aligned":
       # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
       # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
       # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
       # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

       # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
       snake_case   :				int				 =   1

       # Mimic fairseq token-to-id alignment for the first 4 token
       snake_case   :				Any				 =   {"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

       snake_case   :				Tuple				 =   len(self.sp_model						)
       snake_case   :				Any				 =   {F'<madeupword{i}>': sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words						)}
       self.fairseq_tokens_to_ids.update(snake_case__						)

       snake_case   :				List[str]				 =   {v: k for k, v in self.fairseq_tokens_to_ids.items()}







   def __getstate__(     self						)     ->		Optional[int]:

       '''simple docstring'''




       snake_case   :				Union[str, Any]				 =   self.__dict__.copy()
       snake_case   :				str				 =   None
       snake_case   :				Union[str, Any]				 =   self.sp_model.serialized_model_proto()
       return state







   def __setstate__(     self						,     UpperCamelCase__						)     ->		List[str]:

       '''simple docstring'''




       snake_case   :				int				 =   d

       # for backward compatibility
       if not hasattr(self						,     "sp_model_kwargs"						):
           snake_case   :				List[str]				 =   {}

       snake_case   :				str				 =   spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						,     UpperCamelCase__ = None						)     ->		List[int]:

       '''simple docstring'''




       if token_ids_a is None:
           return [self.sep_token_id] + token_ids_a
       snake_case   :				Tuple				 =   [self.sep_token_id]
       return sep + token_ids_a + sep + sep + token_ids_a







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						,     UpperCamelCase__ = None						,     UpperCamelCase__ = False						)     ->		List[int]:

       '''simple docstring'''




       if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=snake_case__						,     token_ids_a=snake_case__						,     already_has_special_tokens=snake_case__						)

       if token_ids_a is None:
           return [1] + ([0] * len(snake_case__						))
       return [1] + ([0] * len(snake_case__						)) + [1, 1] + ([0] * len(snake_case__						))







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						,     UpperCamelCase__ = None						)     ->		List[int]:

       '''simple docstring'''




       snake_case   :				List[str]				 =   [self.sep_token_id]

       if token_ids_a is None:
           return len(sep + token_ids_a						) * [0]
       return len(sep + token_ids_a + sep + sep + token_ids_a						) * [0]







   @property
   def 			lowerCamelCase		(     self						)     ->		List[Any]:

       '''simple docstring'''




       return len(self.sp_model						) + self.fairseq_offset + self.num_madeup_words







   def 			lowerCamelCase		(     self						)     ->		Tuple:

       '''simple docstring'''




       snake_case   :				List[str]				 =   {self.convert_ids_to_tokens(snake_case__						): i for i in range(self.vocab_size						)}
       vocab.update(self.added_tokens_encoder						)
       return vocab







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		List[str]:

       '''simple docstring'''




       return self.sp_model.encode(snake_case__						,     out_type=snake_case__						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		Optional[int]:

       '''simple docstring'''




       if token in self.fairseq_tokens_to_ids:
           return self.fairseq_tokens_to_ids[token]
       snake_case   :				List[Any]				 =   self.sp_model.PieceToId(snake_case__						)

       # Need to return unknown token if the SP model returned 0
       return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		int:

       '''simple docstring'''




       if index in self.fairseq_ids_to_tokens:
           return self.fairseq_ids_to_tokens[index]
       return self.sp_model.IdToPiece(index - self.fairseq_offset						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		int:

       '''simple docstring'''




       snake_case   :				List[Any]				 =   "".join(snake_case__						).replace(snake_case__						,     " "						).strip()
       return out_string







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						,     UpperCamelCase__ = None						)     ->		Tuple[str]:

       '''simple docstring'''




       if not os.path.isdir(snake_case__						):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
           return
       snake_case   :				Optional[Any]				 =   os.path.join(
           snake_case__						,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

       if os.path.abspath(self.vocab_file						) != os.path.abspath(snake_case__						) and os.path.isfile(self.vocab_file						):
           copyfile(self.vocab_file						,     snake_case__						)
       elif not os.path.isfile(self.vocab_file						):
           with open(snake_case__						,     "wb"						) as fi:
               snake_case   :				Optional[Any]				 =   self.sp_model.serialized_model_proto()
               fi.write(snake_case__						)

       return (out_vocab_file,)









"""simple docstring"""



import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class _lowerCAmelCase    (				snake_case_   ,							unittest.TestCase     ):
   __UpperCAmelCase			:	List[Any]							  =  MgpstrTokenizer
   __UpperCAmelCase			:	Optional[int]							  =  False
   __UpperCAmelCase			:	Optional[int]							  =  {}
   __UpperCAmelCase			:	List[str]							  =  False







   def 			lowerCamelCase		(     self						)     ->		int:

       '''simple docstring'''




       super().setUp()

       # fmt: off
       snake_case   :				List[str]				 =   ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
       # fmt: on
       snake_case   :				Union[str, Any]				 =   dict(zip(UpperCamelCase__						,     range(len(UpperCamelCase__						)						)						)						)

       snake_case   :				int				 =   os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES["vocab_file"]						)
       with open(self.vocab_file						,     "w"						,     encoding="utf-8"						) as fp:
           fp.write(json.dumps(UpperCamelCase__						) + "\n"						)







   def 			lowerCamelCase		(     self						,     **UpperCamelCase__						)     ->		List[str]:

       '''simple docstring'''




       return MgpstrTokenizer.from_pretrained(self.tmpdirname						,     **UpperCamelCase__						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		List[Any]:

       '''simple docstring'''




       snake_case   :				int				 =   "tester"
       snake_case   :				List[str]				 =   "tester"
       return input_text, output_text







   @unittest.skip("MGP-STR always lower cases letters."						)
   def 			lowerCamelCase		(     self						)     ->		str:

       '''simple docstring'''




       pass







   def 			lowerCamelCase		(     self						)     ->		Tuple:

       '''simple docstring'''




       snake_case   :				int				 =   self.get_tokenizers(do_lower_case=UpperCamelCase__						)
       for tokenizer in tokenizers:
           with self.subTest(F'{tokenizer.__class__.__name__}'						):
               snake_case   :				List[Any]				 =   "[SPECIAL_TOKEN]"

               tokenizer.add_special_tokens({"cls_token": special_token}						)
               snake_case   :				str				 =   tokenizer.encode([special_token]						,     add_special_tokens=UpperCamelCase__						)
               self.assertEqual(len(UpperCamelCase__						)						,     1						)

               snake_case   :				List[Any]				 =   tokenizer.decode(UpperCamelCase__						,     skip_special_tokens=UpperCamelCase__						)
               self.assertTrue(special_token not in decoded						)







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

       '''simple docstring'''




       snake_case   :				List[str]				 =   self.get_tokenizers()
       for tokenizer in tokenizers:
           with self.subTest(F'{tokenizer.__class__.__name__}'						):
               snake_case ,snake_case   :				Union[str, Any]				 =   self.get_input_output_texts(UpperCamelCase__						)

               snake_case   :				Dict				 =   tokenizer.tokenize(UpperCamelCase__						)
               snake_case   :				Tuple				 =   tokenizer.convert_tokens_to_ids(UpperCamelCase__						)
               snake_case   :				List[Any]				 =   tokenizer.encode(UpperCamelCase__						,     add_special_tokens=UpperCamelCase__						)
               self.assertListEqual(UpperCamelCase__						,     UpperCamelCase__						)

               snake_case   :				Dict				 =   tokenizer.convert_ids_to_tokens(UpperCamelCase__						)
               self.assertNotEqual(len(UpperCamelCase__						)						,     0						)
               snake_case   :				Tuple				 =   tokenizer.decode(UpperCamelCase__						)
               self.assertIsInstance(UpperCamelCase__						,     UpperCamelCase__						)

               self.assertEqual(text_a.replace(" "						,     ""						)						,     UpperCamelCase__						)







   @unittest.skip("MGP-STR tokenizer only handles one sequence."						)
   def 			lowerCamelCase		(     self						)     ->		List[Any]:

       '''simple docstring'''




       pass







   @unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"						)
   def 			lowerCamelCase		(     self						)     ->		Tuple:

       '''simple docstring'''




       pass





