import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin






class 							_SCREAMING_SNAKE_CASE(   snake_case__       ,      unittest.TestCase	):
   UpperCamelCase_				:						str 			=   SpeechaTextaTokenizer
   UpperCamelCase_				:						Optional[Any] 			=   False
   def _lowercase(    self    )	->str:
        super().setUp()

        a  :    int				=						'''<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'''.split(''' '''    )
        a  :    Any				=						['''he re</w> 123''', '''here a 1456''']
        a  :    List[str]				=						dict(zip(lowerCAmelCase_							,     range(len(lowerCAmelCase_    )    )    )    )

        a  :    str				=						{'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

        a  :    Optional[int]				=						tempfile.mkdtemp()
        a  :    Union[str, Any]				=						os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES['''vocab_file''']    )
        a  :    Dict				=						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'''    ) as fp:
             fp.write('''\n'''.join(lowerCAmelCase_    )    )
   def _lowercase(    self    )	->List[Any]:
        a  :    Dict				=						list(self.get_tokenizer().get_vocab().keys()    )

        self.assertEqual(vocab_keys[0]							,     '''<s>'''    )
        self.assertEqual(vocab_keys[1]							,     '''<pad>'''    )
        self.assertEqual(vocab_keys[-1]							,     '''vocab'''    )
        self.assertEqual(len(lowerCAmelCase_    )							,     14    )
   def _lowercase(    self    )	->Tuple:
        self.assertEqual(self.get_tokenizer().vocab_size							,     14    )
   def _lowercase(    self    )	->Optional[int]:
        a  :    List[Any]				=						SpeechaTextaTokenizer.from_pretrained(self.tmpdirname    )

        # make sure @@ is correctly concatenated
        a  :    List[Any]				=						[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
        a  :    Tuple				=						tokenizer.decode(lowerCAmelCase_    )

        self.assertTrue(output_string == '''herecouple words ofthe'''    )
   def _lowercase(    self    )	->Union[str, Any]:
        a  :    Optional[Any]				=						SpeechaTextaTokenizer.from_pretrained(self.tmpdirname    )

        with tempfile.TemporaryDirectory() as tmp_dirname:
             tokenizer.save_pretrained(lowerCAmelCase_    )
             os.remove(os.path.join(lowerCAmelCase_							,     '''merges.txt'''    )    )

             # load tokenizer without merges file should not throw an error
             a  :    Dict				=						SpeechaTextaTokenizer.from_pretrained(lowerCAmelCase_    )

        with tempfile.TemporaryDirectory() as tmp_dirname:
             # save tokenizer and load again
             tokenizer.save_pretrained(lowerCAmelCase_    )
             a  :    Tuple				=						SpeechaTextaTokenizer.from_pretrained(lowerCAmelCase_    )

        self.assertIsNotNone(lowerCAmelCase_    )


   def _lowercase(    self    )	->Dict:
        if not self.test_slow_tokenizer:
             return

        a  :    int				=						inspect.signature(self.tokenizer_class.__init__    )
        a  :    Optional[Any]				=						self.get_tokenizer()

        for parameter_name, parameter in signature.parameters.items():
             if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
                  self.assertIn(lowerCAmelCase_							,     tokenizer.init_kwargs    )
# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    """--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"""
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/