




'''simple docstring'''






import json
import os
from typing import List, Optional, Tuple

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


A_ 			=		logging.get_logger(__name__)

A_ 			=		{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

A_ 			=		{
    "vocab_file": {
        "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json",
    },
    "merges_file": {"microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt"},
}

A_ 			=		{
    "microsoft/biogpt": 1024,
}






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      str:
						snake_case__					:      Optional[Any]  			=						set()
						snake_case__					:      Dict  			=						word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)		)
												snake_case__					:      Tuple  			=						char
						return pairs






class 					lowercase_			(	lowerCAmelCase_       ):
					A_       							= VOCAB_FILES_NAMES
					A_       							= PRETRAINED_VOCAB_FILES_MAP
					A_       							= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A_       							= ["input_ids", "attention_mask"]





					def __init__(    self    :				Optional[int]    ,       __lowerCamelCase    :				Tuple    ,       __lowerCamelCase    :				List[str]    ,       __lowerCamelCase    :				Dict="<unk>"    ,       __lowerCamelCase    :				Dict="<s>"    ,       __lowerCamelCase    :				List[str]="</s>"    ,       __lowerCamelCase    :				str="</s>"    ,       __lowerCamelCase    :				Optional[Any]="<pad>"    ,       **__lowerCamelCase    :				int    ,       ):
											super().__init__(
											    bos_token=__lowerCamelCase    ,       eos_token=__lowerCamelCase    ,       sep_token=__lowerCamelCase    ,       unk_token=__lowerCamelCase    ,       pad_token=__lowerCamelCase    ,       **__lowerCamelCase    ,       )

											try:
																	import sacremoses
											except ImportError:
																	raise ImportError(
																	    'You need to install sacremoses to use BioGptTokenizer. '
																	    'See https://pypi.org/project/sacremoses/ for installation.' )

											snake_case__					:      Optional[Any]  			=						'en'
											snake_case__					:      Optional[Any]  			=						sacremoses
											# cache of sm.MosesTokenizer instance
											snake_case__					:      int  			=						{}
											snake_case__					:      List[str]  			=						{}
											with open(__lowerCamelCase    ,       encoding='utf-8' ) as vocab_handle:
																	snake_case__					:      Any  			=						json.load(__lowerCamelCase )
											snake_case__					:      List[str]  			=						{v: k for k, v in self.encoder.items()}
											with open(__lowerCamelCase    ,       encoding='utf-8' ) as merges_handle:
																	snake_case__					:      str  			=						merges_handle.read().split('\n' )[:-1]
											snake_case__					:      Union[str, Any]  			=						[tuple(merge.split()[:2] ) for merge in merges]
											snake_case__					:      List[Any]  			=						dict(zip(__lowerCamelCase    ,       range(len(__lowerCamelCase ) ) ) )
											snake_case__					:      List[str]  			=						{}





					@property
					def  _lowerCAmelCase			(    self    :				List[Any] ):
											return len(self.encoder )





					def  _lowerCAmelCase			(    self    :				int ):
											return dict(self.encoder    ,       **self.added_tokens_encoder )





					def  _lowerCAmelCase			(    self    :				List[Any]    ,       __lowerCamelCase    :				int    ,       __lowerCamelCase    :				int ):
											if lang not in self.cache_moses_tokenizer:
																	snake_case__					:      Union[str, Any]  			=						self.sm.MosesTokenizer(lang=__lowerCamelCase )
																	snake_case__					:      Tuple  			=						moses_tokenizer
											return self.cache_moses_tokenizer[lang].tokenize(
											    __lowerCamelCase    ,       aggressive_dash_splits=__lowerCamelCase    ,       return_str=__lowerCamelCase    ,       escape=__lowerCamelCase )





					def  _lowerCAmelCase			(    self    :				List[str]    ,       __lowerCamelCase    :				Union[str, Any]    ,       __lowerCamelCase    :				Optional[Any] ):
											if lang not in self.cache_moses_detokenizer:
																	snake_case__					:      str  			=						self.sm.MosesDetokenizer(lang=__lowerCamelCase )
																	snake_case__					:      Optional[int]  			=						moses_detokenizer
											return self.cache_moses_detokenizer[lang].detokenize(__lowerCamelCase )





					def  _lowerCAmelCase			(    self    :				List[Any]    ,       __lowerCamelCase    :				List[Any] ):
											snake_case__					:      List[Any]  			=						tuple(token[:-1] ) + (token[-1] + '</w>',)
											if token in self.cache:
																	return self.cache[token]
											snake_case__					:      Union[str, Any]  			=						get_pairs(__lowerCamelCase )

											if not pairs:
																	return token + "</w>"

											while True:
																	snake_case__					:      Union[str, Any]  			=						min(__lowerCamelCase    ,       key=lambda __lowerCamelCase : self.bpe_ranks.get(__lowerCamelCase    ,       float('inf' ) ) )
																	if bigram not in self.bpe_ranks:
																							break
																	snake_case__					:      int  			=						bigram
																	snake_case__					:      Dict  			=						[]
																	snake_case__					:      str  			=						0
																	while i < len(__lowerCamelCase ):
																							try:
																													snake_case__					:      Optional[Any]  			=						word.index(__lowerCamelCase    ,       __lowerCamelCase )
																							except ValueError:
																													new_word.extend(word[i:] )
																													break
																							else:
																													new_word.extend(word[i:j] )
																													snake_case__					:      Any  			=						j

																							if word[i] == first and i < len(__lowerCamelCase ) - 1 and word[i + 1] == second:
																													new_word.append(first + second )
																													i += 2
																							else:
																													new_word.append(word[i] )
																													i += 1
																	snake_case__					:      List[str]  			=						tuple(__lowerCamelCase )
																	snake_case__					:      Union[str, Any]  			=						new_word
																	if len(__lowerCamelCase ) == 1:
																							break
																	else:
																							snake_case__					:      Tuple  			=						get_pairs(__lowerCamelCase )
											snake_case__					:      str  			=						' '.join(__lowerCamelCase )
											if word == "\n  </w>":
																	snake_case__					:      Optional[Any]  			=						'\n</w>'
											snake_case__					:      Optional[int]  			=						word
											return word





					def  _lowerCAmelCase			(    self    :				Dict    ,       __lowerCamelCase    :				Any    ,       __lowerCamelCase    :				str=False ):
											if bypass_tokenizer:
																	snake_case__					:      List[str]  			=						text.split()
											else:
																	snake_case__					:      Optional[int]  			=						self.moses_tokenize(__lowerCamelCase    ,       self.lang )

											snake_case__					:      Optional[int]  			=						[]
											for token in text:
																	if token:
																							split_tokens.extend(list(self.bpe(__lowerCamelCase ).split(' ' ) ) )

											return split_tokens





					def  _lowerCAmelCase			(    self    :				int    ,       __lowerCamelCase    :				Optional[int] ):
											return self.encoder.get(__lowerCamelCase    ,       self.encoder.get(self.unk_token ) )





					def  _lowerCAmelCase			(    self    :				Dict    ,       __lowerCamelCase    :				List[str] ):
											return self.decoder.get(__lowerCamelCase    ,       self.unk_token )





					def  _lowerCAmelCase			(    self    :				Union[str, Any]    ,       __lowerCamelCase    :				Dict ):
											snake_case__					:      Optional[Any]  			=						[t.replace(' '    ,       '' ).replace('</w>'    ,       ' ' ) for t in tokens]
											snake_case__					:      Tuple  			=						''.join(__lowerCamelCase ).split()
											# detokenize
											snake_case__					:      List[str]  			=						self.moses_detokenize(__lowerCamelCase    ,       self.lang )
											return text





					def  _lowerCAmelCase			(    self    :				str    ,       __lowerCamelCase    :				List[int]    ,       __lowerCamelCase    :				Optional[List[int]] = None ):
											if token_ids_a is None:
																	return [self.sep_token_id] + token_ids_a
											snake_case__					:      Optional[int]  			=						[self.sep_token_id]
											return sep + token_ids_a + sep + token_ids_a





					def  _lowerCAmelCase			(    self    :				Union[str, Any]    ,       __lowerCamelCase    :				List[int]    ,       __lowerCamelCase    :				Optional[List[int]] = None    ,       __lowerCamelCase    :				bool = False ):
											if already_has_special_tokens:
																	return super().get_special_tokens_mask(
																	    token_ids_a=__lowerCamelCase    ,       token_ids_a=__lowerCamelCase    ,       already_has_special_tokens=__lowerCamelCase )
											# no bos used in fairseq
											if token_ids_a is not None:
																	return [1] + ([0] * len(__lowerCamelCase )) + [1] + ([0] * len(__lowerCamelCase ))
											return [1] + ([0] * len(__lowerCamelCase ))





					def  _lowerCAmelCase			(    self    :				Dict    ,       __lowerCamelCase    :				List[int]    ,       __lowerCamelCase    :				Optional[List[int]] = None ):
											snake_case__					:      Optional[Any]  			=						[self.sep_token_id]

											# no bos used in fairseq
											if token_ids_a is None:
																	return len(token_ids_a + sep ) * [0]
											return len(token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]





					def  _lowerCAmelCase			(    self    :				Any    ,       __lowerCamelCase    :				str    ,       __lowerCamelCase    :				Optional[str] = None ):
											if not os.path.isdir(__lowerCamelCase ):
																	logger.error(F"Vocabulary path ({save_directory}) should be a directory" )
																	return
											snake_case__					:      Optional[Any]  			=						os.path.join(
											    __lowerCamelCase    ,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )
											snake_case__					:      List[str]  			=						os.path.join(
											    __lowerCamelCase    ,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'] )

											with open(__lowerCamelCase    ,       'w'    ,       encoding='utf-8' ) as f:
																	f.write(json.dumps(self.encoder    ,       indent=2    ,       sort_keys=__lowerCamelCase    ,       ensure_ascii=__lowerCamelCase ) + '\n' )

											snake_case__					:      str  			=						0
											with open(__lowerCamelCase    ,       'w'    ,       encoding='utf-8' ) as writer:
																	for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,       key=lambda __lowerCamelCase : kv[1] ):
																							if index != token_index:
																													logger.warning(
																													    F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
																													    ' Please check that the tokenizer is not corrupted!' )
																													snake_case__					:      Tuple  			=						token_index
																							writer.write(' '.join(__lowerCamelCase ) + '\n' )
																							index += 1

											return vocab_file, merge_file





					def __getstate__(    self    :				List[Any] ):
											snake_case__					:      List[Any]  			=						self.__dict__.copy()
											snake_case__					:      List[Any]  			=						None
											return state





					def __setstate__(    self    :				Optional[Any]    ,       __lowerCamelCase    :				List[str] ):
											snake_case__					:      int  			=						d

											try:
																	import sacremoses
											except ImportError:
																	raise ImportError(
																	    'You need to install sacremoses to use XLMTokenizer. '
																	    'See https://pypi.org/project/sacremoses/ for installation.' )

											snake_case__					:      Dict  			=						sacremoses






'''simple docstring'''






import shutil
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import SpeechaTextTokenizer, is_speech_available
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, require_torchaudio
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_speech_to_text import floats_list


if is_speech_available():
      from transformers import SpeechaTextFeatureExtractor, SpeechaTextProcessor


A_ 			=		get_tests_dir("fixtures/test_sentencepiece.model")






@require_torch
@require_torchaudio
@require_sentencepiece
class 					lowercase_			(	unittest.TestCase       ):





     def  _lowerCAmelCase			(    self    :				List[str] ):
           snake_case__					:      Dict  			=						tempfile.mkdtemp()

           snake_case__					:      Union[str, Any]  			=						['<s>', '<pad>', '</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est']
           snake_case__					:      str  			=						dict(zip(__lowerCamelCase    ,       range(len(__lowerCamelCase ) ) ) )
           snake_case__					:      Union[str, Any]  			=						Path(self.tmpdirname )
           save_json(__lowerCamelCase    ,       save_dir / VOCAB_FILES_NAMES['vocab_file'] )
           if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
                 copyfile(__lowerCamelCase    ,       save_dir / VOCAB_FILES_NAMES['spm_file'] )

           snake_case__					:      Optional[Any]  			=						SpeechaTextTokenizer.from_pretrained(self.tmpdirname )
           tokenizer.save_pretrained(self.tmpdirname )

           snake_case__					:      str  			=						{
               'feature_size': 24,
               'num_mel_bins': 24,
               'padding_value': 0.0,
               'sampling_rate': 16000,
               'return_attention_mask': False,
               'do_normalize': True,
           }
           save_json(__lowerCamelCase    ,       save_dir / FEATURE_EXTRACTOR_NAME )





     def  _lowerCAmelCase			(    self    :				str    ,       **__lowerCamelCase    :				int ):
           return SpeechaTextTokenizer.from_pretrained(self.tmpdirname    ,       **__lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				int    ,       **__lowerCamelCase    :				List[Any] ):
           return SpeechaTextFeatureExtractor.from_pretrained(self.tmpdirname    ,       **__lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				List[Any] ):
           shutil.rmtree(self.tmpdirname )





     def  _lowerCAmelCase			(    self    :				Dict ):
           snake_case__					:      Dict  			=						self.get_tokenizer()
           snake_case__					:      Any  			=						self.get_feature_extractor()

           snake_case__					:      Tuple  			=						SpeechaTextProcessor(tokenizer=__lowerCamelCase    ,       feature_extractor=__lowerCamelCase )

           processor.save_pretrained(self.tmpdirname )
           snake_case__					:      Any  			=						SpeechaTextProcessor.from_pretrained(self.tmpdirname )

           self.assertEqual(processor.tokenizer.get_vocab()    ,       tokenizer.get_vocab() )
           self.assertIsInstance(processor.tokenizer    ,       __lowerCamelCase )

           self.assertEqual(processor.feature_extractor.to_json_string()    ,       feature_extractor.to_json_string() )
           self.assertIsInstance(processor.feature_extractor    ,       __lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				List[Any] ):
           snake_case__					:      Any  			=						SpeechaTextProcessor(
               tokenizer=self.get_tokenizer()    ,       feature_extractor=self.get_feature_extractor() )
           processor.save_pretrained(self.tmpdirname )

           snake_case__					:      Tuple  			=						self.get_tokenizer(bos_token='(BOS)'    ,       eos_token='(EOS)' )
           snake_case__					:      int  			=						self.get_feature_extractor(do_normalize=__lowerCamelCase    ,       padding_value=1.0 )

           snake_case__					:      Any  			=						SpeechaTextProcessor.from_pretrained(
               self.tmpdirname    ,       bos_token='(BOS)'    ,       eos_token='(EOS)'    ,       do_normalize=__lowerCamelCase    ,       padding_value=1.0 )

           self.assertEqual(processor.tokenizer.get_vocab()    ,       tokenizer_add_kwargs.get_vocab() )
           self.assertIsInstance(processor.tokenizer    ,       __lowerCamelCase )

           self.assertEqual(processor.feature_extractor.to_json_string()    ,       feature_extractor_add_kwargs.to_json_string() )
           self.assertIsInstance(processor.feature_extractor    ,       __lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				Any ):
           snake_case__					:      int  			=						self.get_feature_extractor()
           snake_case__					:      Optional[Any]  			=						self.get_tokenizer()

           snake_case__					:      List[str]  			=						SpeechaTextProcessor(tokenizer=__lowerCamelCase    ,       feature_extractor=__lowerCamelCase )

           snake_case__					:      List[str]  			=						floats_list((3, 1000) )

           snake_case__					:      Tuple  			=						feature_extractor(__lowerCamelCase    ,       return_tensors='np' )
           snake_case__					:      str  			=						processor(__lowerCamelCase    ,       return_tensors='np' )

           for key in input_feat_extract.keys():
                 self.assertAlmostEqual(input_feat_extract[key].sum()    ,       input_processor[key].sum()    ,       delta=1E-2 )





     def  _lowerCAmelCase			(    self    :				Dict ):
           snake_case__					:      Optional[int]  			=						self.get_feature_extractor()
           snake_case__					:      Optional[Any]  			=						self.get_tokenizer()

           snake_case__					:      Tuple  			=						SpeechaTextProcessor(tokenizer=__lowerCamelCase    ,       feature_extractor=__lowerCamelCase )

           snake_case__					:      Optional[int]  			=						'This is a test string'

           snake_case__					:      int  			=						processor(text=__lowerCamelCase )

           snake_case__					:      Tuple  			=						tokenizer(__lowerCamelCase )

           for key in encoded_tok.keys():
                 self.assertListEqual(encoded_tok[key]    ,       encoded_processor[key] )





     def  _lowerCAmelCase			(    self    :				int ):
           snake_case__					:      Optional[int]  			=						self.get_feature_extractor()
           snake_case__					:      int  			=						self.get_tokenizer()

           snake_case__					:      str  			=						SpeechaTextProcessor(tokenizer=__lowerCamelCase    ,       feature_extractor=__lowerCamelCase )

           snake_case__					:      str  			=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           snake_case__					:      List[str]  			=						processor.batch_decode(__lowerCamelCase )
           snake_case__					:      Optional[int]  			=						tokenizer.batch_decode(__lowerCamelCase )

           self.assertListEqual(__lowerCamelCase    ,       __lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				str ):
           snake_case__					:      List[str]  			=						self.get_feature_extractor()
           snake_case__					:      int  			=						self.get_tokenizer()

           snake_case__					:      int  			=						SpeechaTextProcessor(tokenizer=__lowerCamelCase    ,       feature_extractor=__lowerCamelCase )

           self.assertListEqual(
               processor.model_input_names    ,       feature_extractor.model_input_names    ,       msg='`processor` and `feature_extractor` model input names do not match'    ,       )
