

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 		__magic_name__ (				snake_case       ,	unittest.TestCase							):
     UpperCamelCase_     :Union[str, Any]									=	SpeechaTextaTokenizer
     UpperCamelCase_     :Optional[Any]									=	False






     def      UpperCAmelCase_							(							self     )->			Dict:
         super().setUp()

         UpperCamelCase_          =		"<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" "     )
         UpperCamelCase_          =		["he re</w> 123", "here a 1456"]
         UpperCamelCase_          =		dict(zip(_lowercase						,		range(len(_lowercase     )     )     )     )

         UpperCamelCase_          =		{"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

         UpperCamelCase_          =		tempfile.mkdtemp()
         UpperCamelCase_          =		os.path.join(self.tmpdirname						,		VOCAB_FILES_NAMES["vocab_file"]     )
         UpperCamelCase_          =		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(_lowercase     ) + "\n"     )

         with open(self.merges_file						,		"w"     ) as fp:
             fp.write("\n".join(_lowercase     )     )






     def      UpperCAmelCase_							(							self     )->			Any:
         UpperCamelCase_          =		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(_lowercase     )						,		14     )






     def      UpperCAmelCase_							(							self     )->			int:
         self.assertEqual(self.get_tokenizer().vocab_size						,		14     )






     def      UpperCAmelCase_							(							self     )->			List[str]:
         UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(self.tmpdirname     )

         # make sure @@ is correctly concatenated
         UpperCamelCase_          =		[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
         UpperCamelCase_          =		tokenizer.decode(_lowercase     )

         self.assertTrue(output_string == "herecouple words ofthe"     )






     def      UpperCAmelCase_							(							self     )->			Any:
         UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(self.tmpdirname     )

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

             # load tokenizer without merges file should not throw an error
             UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(_lowercase     )

         with tempfile.TemporaryDirectory() as tmp_dirname:
             # save tokenizer and load again
             tokenizer.save_pretrained(_lowercase     )
             UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(_lowercase     )

         self.assertIsNotNone(_lowercase     )






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

         UpperCamelCase_          =		inspect.signature(self.tokenizer_class.__init__     )
         UpperCamelCase_          =		self.get_tokenizer()

         for parameter_name, parameter in signature.parameters.items():
             if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
                 self.assertIn(_lowercase						,		tokenizer.init_kwargs     )








"""simple docstring"""


import sys
from dataclasses import dataclass
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


if TYPE_CHECKING:
   import sqlitea

   import sqlalchemy


_UpperCamelCase				:    Optional[Any]     =						datasets.utils.logging.get_logger(__name__)






@dataclass
class 						snake_case  (  datasets.BuilderConfig       ):
    __magic_name__         =     None
    __magic_name__         =     None
    __magic_name__         =     None
    __magic_name__         =     True
    __magic_name__         =     None
    __magic_name__         =     None
    __magic_name__         =     None
    __magic_name__         =     1_0000
    __magic_name__         =     None





    def 				lowerCamelCase__      (							self	:					Tuple			):


      '''simple docstring'''




      if self.sql is None:
        raise ValueError('sql must be specified'			)
      if self.con is None:
        raise ValueError('con must be specified'			)





    def 				lowerCamelCase__      (							self	:					int				,		A	:					dict				,		A	:					Optional[datasets.Features] = None				,		):


      '''simple docstring'''




      a     :			str				=   config_kwargs.copy()
      # We need to stringify the Selectable object to make its hash deterministic

      # The process of stringifying is explained here: http://docs.sqlalchemy.org/en/latest/faq/sqlexpressions.html
      a     :			List[str]				=   config_kwargs['sql']
      if not isinstance(A				,		A			):
        if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
          import sqlalchemy

          if isinstance(A				,		sqlalchemy.sql.Selectable			):
            a     :			Union[str, Any]				=   sqlalchemy.create_engine(config_kwargs['con'].split('://'			)[0] + '://'			)
            a     :			List[Any]				=   str(sql.compile(dialect=engine.dialect			)			)
            a     :			str				=   sql_str
          else:
            raise TypeError(
                F'''Supported types for \'sql\' are string and sqlalchemy.sql.Selectable but got {type(A			)}: {sql}'''			)
        else:
          raise TypeError(
              F'''Supported types for \'sql\' are string and sqlalchemy.sql.Selectable but got {type(A			)}: {sql}'''			)
      a     :			List[str]				=   config_kwargs['con']
      if not isinstance(A				,		A			):
        a     :			Optional[Any]				=   id(A			)
        logger.info(
            F'''SQL connection \'con\' of type {type(A			)} couldn\'t be hashed properly. To enable hashing, specify \'con\' as URI string instead.'''			)

      return super().create_config_id(A				,		custom_features=A			)





    @property
    def 				lowerCamelCase__      (							self	:					Optional[int]			):


      '''simple docstring'''




      a     :			int				=   {
          'index_col': self.index_col,
          'columns': self.columns,
          'params': self.params,
          'coerce_float': self.coerce_float,
          'parse_dates': self.parse_dates,
      }
      return pd_read_sql_kwargs






class 						snake_case  (  datasets.ArrowBasedBuilder       ):
    __magic_name__         =     SqlConfig





    def 				lowerCamelCase__      (							self	:					Any			):


      '''simple docstring'''




      return datasets.DatasetInfo(features=self.config.features			)





    def 				lowerCamelCase__      (							self	:					Dict				,		A	:					Optional[int]			):


      '''simple docstring'''




      return [datasets.SplitGenerator(name=datasets.Split.TRAIN				,		gen_kwargs={}			)]





    def 				lowerCamelCase__      (							self	:					Union[str, Any]				,		A	:					pa.Table			):


      '''simple docstring'''




      if self.config.features is not None:
        a     :			List[Any]				=   self.config.features.arrow_schema
        if all(not require_storage_cast(A			) for feature in self.config.features.values()			):
          # cheaper cast
          a     :			Dict				=   pa.Table.from_arrays([pa_table[field.name] for field in schema]				,		schema=A			)
        else:
          # more expensive cast; allows str <-> int/float or str to Audio for example
          a     :			Union[str, Any]				=   table_cast(A				,		A			)
      return pa_table





    def 				lowerCamelCase__      (							self	:					Dict			):


      '''simple docstring'''




      a     :			List[Any]				=   self.config.chunksize
      a     :			Union[str, Any]				=   pd.read_sql(
          self.config.sql				,		self.config.con				,		chunksize=A				,		**self.config.pd_read_sql_kwargs			)
      a     :			Optional[Any]				=   [sql_reader] if chunksize is None else sql_reader
      for chunk_idx, df in enumerate(A			):
        a     :			List[Any]				=   pa.Table.from_pandas(A			)
        yield chunk_idx, self._cast_table(A			)




