


'''simple docstring'''



import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy


def 				lowerCamelCase__				(	A       :      int				,       A       :      Union[str, Any]					):




						'''simple docstring'''






						assert isinstance(a__				,       a__					)
						assert dataset.num_rows == 4
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_1", "col_2", "col_3"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype


@require_sqlalchemy
@pytest.mark.parametrize('''keep_in_memory'''				,       [False, True]					)
def 				lowerCamelCase__				(	A       :      Any				,       A       :      Optional[int]				,       A       :      Optional[Any]				,       A       :      Tuple					):




						'''simple docstring'''






						UpperCAmelCase					    =     tmp_path / '''cache'''
						UpperCAmelCase					    =     {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												UpperCAmelCase					    =     SqlDatasetReader(
												    '''dataset'''				,       '''sqlite:///''' + sqlite_path				,       cache_dir=a__				,       keep_in_memory=a__					).read()
						_check_sql_dataset(a__				,       a__					)


@require_sqlalchemy
@pytest.mark.parametrize(
    '''features'''				,       [
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ]				,       )
def 				lowerCamelCase__				(	A       :      Any				,       A       :      Tuple				,       A       :      Optional[int]				,       A       :      Optional[int]					):




						'''simple docstring'''






						UpperCAmelCase					    =     tmp_path / '''cache'''
						UpperCAmelCase					    =     {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						UpperCAmelCase					    =     features.copy() if features else default_expected_features
						UpperCAmelCase					    =     (
						    Features({feature: Value(a__					) for feature, dtype in features.items()}					) if features is not None else None
						)
						UpperCAmelCase					    =     SqlDatasetReader('''dataset'''				,       '''sqlite:///''' + sqlite_path				,       features=a__				,       cache_dir=a__					).read()
						_check_sql_dataset(a__				,       a__					)


def 				lowerCamelCase__				(	A       :      Optional[int]					):




						'''simple docstring'''






						with contextlib.closing(sqlitea.connect(a__					)					) as con:
												UpperCAmelCase					    =     con.cursor()
												cur.execute('''SELECT * FROM dataset'''					)
												for row in cur:
																		yield row


@require_sqlalchemy
def 				lowerCamelCase__				(	A       :      Any				,       A       :      List[Any]				,       A       :      Dict					):




						'''simple docstring'''






						UpperCAmelCase					    =     tmp_path / '''cache'''
						UpperCAmelCase					    =     os.path.join(a__				,       '''tmp.sql'''					)
						UpperCAmelCase					    =     SqlDatasetReader('''dataset'''				,       '''sqlite:///''' + sqlite_path				,       cache_dir=a__					).read()
						SqlDatasetWriter(a__				,       '''dataset'''				,       '''sqlite:///''' + output_sqlite_path				,       num_proc=1					).write()

						UpperCAmelCase					    =     iter_sql_file(a__					)
						UpperCAmelCase					    =     iter_sql_file(a__					)

						for rowa, rowa in zip(a__				,       a__					):
												assert rowa == rowa


@require_sqlalchemy
def 				lowerCamelCase__				(	A       :      Any				,       A       :      Tuple				,       A       :      Optional[Any]					):




						'''simple docstring'''






						UpperCAmelCase					    =     tmp_path / '''cache'''
						UpperCAmelCase					    =     os.path.join(a__				,       '''tmp.sql'''					)
						UpperCAmelCase					    =     SqlDatasetReader('''dataset'''				,       '''sqlite:///''' + sqlite_path				,       cache_dir=a__					).read()
						SqlDatasetWriter(a__				,       '''dataset'''				,       '''sqlite:///''' + output_sqlite_path				,       num_proc=2					).write()

						UpperCAmelCase					    =     iter_sql_file(a__					)
						UpperCAmelCase					    =     iter_sql_file(a__					)

						for rowa, rowa in zip(a__				,       a__					):
												assert rowa == rowa




@require_sqlalchemy
def 				lowerCamelCase__				(	A       :      str				,       A       :      Optional[Any]				,       A       :      int					):




						'''simple docstring'''






						UpperCAmelCase					    =     tmp_path / '''cache'''
						UpperCAmelCase					    =     os.path.join(a__				,       '''tmp.sql'''					)
						UpperCAmelCase					    =     SqlDatasetReader('''dataset'''				,       '''sqlite:///''' + sqlite_path				,       cache_dir=a__					).read()
						with pytest.raises(a__					):
												SqlDatasetWriter(a__				,       '''dataset'''				,       '''sqlite:///''' + output_sqlite_path				,       num_proc=0					).write()









'''simple docstring'''



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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation


_lowercase      :      Optional[Any]            =					logging.get_logger(__name__)

_lowercase      :      List[str]            =					{"""tokenizer_file""": """tokenizer.json"""}

_lowercase      :      Optional[Any]            =					{
    """tokenizer_file""": {
        """bigscience/tokenizer""": """https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json""",
        """bigscience/bloom-560m""": """https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json""",
        """bigscience/bloom-1b1""": """https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json""",
        """bigscience/bloom-1b7""": """https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json""",
        """bigscience/bloom-3b""": """https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json""",
        """bigscience/bloom-7b1""": """https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json""",
        """bigscience/bloom""": """https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json""",
    },
}






class 	UpperCamelCase__(       lowerCAmelCase	):
				__magic_name__    :				List[str]  		=	VOCAB_FILES_NAMES
				__magic_name__    :				Optional[int]  		=	PRETRAINED_VOCAB_FILES_MAP
				__magic_name__    :				Any  		=	["input_ids", "attention_mask"]
				__magic_name__    :				Optional[int]  		=	None




				def __init__(		self      :			List[Any]				,   lowerCAmelCase      :			str=None				,   lowerCAmelCase      :			Tuple=None				,   lowerCAmelCase      :			str=None				,   lowerCAmelCase      :			Optional[int]="<unk>"				,   lowerCAmelCase      :			int="<s>"				,   lowerCAmelCase      :			Dict="</s>"				,   lowerCAmelCase      :			Union[str, Any]="<pad>"				,   lowerCAmelCase      :			int=False				,   lowerCAmelCase      :			Optional[int]=False				,   **lowerCAmelCase      :			Optional[int]				,   )->					Union[str, Any]:

										"""simple docstring"""




										super().__init__(
										    lowerCAmelCase				,   lowerCAmelCase				,   tokenizer_file=lowerCAmelCase				,   unk_token=lowerCAmelCase				,   bos_token=lowerCAmelCase				,   eos_token=lowerCAmelCase				,   pad_token=lowerCAmelCase				,   add_prefix_space=lowerCAmelCase				,   clean_up_tokenization_spaces=lowerCAmelCase				,   **lowerCAmelCase				,   )
										UpperCAmelCase					    =     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()				)
										if pre_tok_state.get('''add_prefix_space'''				,   lowerCAmelCase				) != add_prefix_space:
																UpperCAmelCase					    =     getattr(lowerCAmelCase				,   pre_tok_state.pop('''type'''				)				)
																UpperCAmelCase					    =     add_prefix_space
																UpperCAmelCase					    =     pre_tok_class(**lowerCAmelCase				)

										UpperCAmelCase					    =     add_prefix_space




				def 					a__(		self      :			str				,   *lowerCAmelCase      :			Dict				,   **lowerCAmelCase      :			List[str]				)->					BatchEncoding:

										"""simple docstring"""




										UpperCAmelCase					    =     kwargs.get('''is_split_into_words'''				,   lowerCAmelCase				)
										if not (self.add_prefix_space or not is_split_into_words):
																raise Exception(
																    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
																    ''' pretokenized inputs.'''				)

										return super()._batch_encode_plus(*lowerCAmelCase				,   **lowerCAmelCase				)




				def 					a__(		self      :			Union[str, Any]				,   *lowerCAmelCase      :			List[str]				,   **lowerCAmelCase      :			Union[str, Any]				)->					BatchEncoding:

										"""simple docstring"""




										UpperCAmelCase					    =     kwargs.get('''is_split_into_words'''				,   lowerCAmelCase				)

										if not (self.add_prefix_space or not is_split_into_words):
																raise Exception(
																    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
																    ''' pretokenized inputs.'''				)

										return super()._encode_plus(*lowerCAmelCase				,   **lowerCAmelCase				)




				def 					a__(		self      :			Union[str, Any]				,   lowerCAmelCase      :			str				,   lowerCAmelCase      :			Optional[str] = None				)->					Tuple[str]:

										"""simple docstring"""




										UpperCAmelCase					    =     self._tokenizer.model.save(lowerCAmelCase				,   name=lowerCAmelCase				)
										return tuple(lowerCAmelCase				)





				def 					a__(		self      :			List[Any]				,   lowerCAmelCase      :			"Conversation"				)->					List[int]:

										"""simple docstring"""




										UpperCAmelCase					    =     []
										for is_user, text in conversation.iter_texts():
																input_ids.extend(self.encode(lowerCAmelCase				,   add_special_tokens=lowerCAmelCase				) + [self.eos_token_id]				)

										if len(lowerCAmelCase				) > self.model_max_length:
																UpperCAmelCase					    =     input_ids[-self.model_max_length :]
										return input_ids





