
"""simple docstring"""

import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def 			lowercase__  (    lowerCAmelCase :    List[Any]       , lowerCAmelCase :    Optional[int]       )       ->					List[Any]:






    """simple docstring"""




    assert isinstance(lowerCAmelCase       , lowerCAmelCase       )
    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




@pytest.mark.parametrize('keep_in_memory'       , [False, True]       )
def 			lowercase__  (    lowerCAmelCase :    Any       , lowerCAmelCase :    Any       , lowerCAmelCase :    Any       )       ->					int:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        UpperCAmelCase  	=    CsvDatasetReader(lowerCAmelCase       , cache_dir=lowerCAmelCase       , keep_in_memory=lowerCAmelCase       ).read()
    _check_csv_dataset(lowerCAmelCase       , lowerCAmelCase       )




@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 			lowercase__  (    lowerCAmelCase :    Union[str, Any]       , lowerCAmelCase :    Any       , lowerCAmelCase :    List[Any]       )       ->					Any:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    UpperCAmelCase  	=    features.copy() if features else default_expected_features
    UpperCAmelCase  	=    (
        Features({feature: Value(lowerCAmelCase       ) for feature, dtype in features.items()}       ) if features is not None else None
    )
    UpperCAmelCase  	=    CsvDatasetReader(lowerCAmelCase       , features=lowerCAmelCase       , cache_dir=lowerCAmelCase       ).read()
    _check_csv_dataset(lowerCAmelCase       , lowerCAmelCase       )




@pytest.mark.parametrize('split'       , [None, NamedSplit('train'       ), 'train', 'test']       )
def 			lowercase__  (    lowerCAmelCase :    List[str]       , lowerCAmelCase :    str       , lowerCAmelCase :    List[Any]       )       ->					Optional[int]:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    UpperCAmelCase  	=    CsvDatasetReader(lowerCAmelCase       , cache_dir=lowerCAmelCase       , split=lowerCAmelCase       ).read()
    _check_csv_dataset(lowerCAmelCase       , lowerCAmelCase       )
    assert dataset.split == split if split else "train"




@pytest.mark.parametrize('path_type'       , [str, list]       )
def 			lowercase__  (    lowerCAmelCase :    Optional[int]       , lowerCAmelCase :    Any       , lowerCAmelCase :    Dict       )       ->					List[Any]:






    """simple docstring"""




    if issubclass(lowerCAmelCase       , lowerCAmelCase       ):
        UpperCAmelCase  	=    csv_path
    elif issubclass(lowerCAmelCase       , lowerCAmelCase       ):
        UpperCAmelCase  	=    [csv_path]
    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    UpperCAmelCase  	=    CsvDatasetReader(lowerCAmelCase       , cache_dir=lowerCAmelCase       ).read()
    _check_csv_dataset(lowerCAmelCase       , lowerCAmelCase       )




def 			lowercase__  (    lowerCAmelCase :    Tuple       , lowerCAmelCase :    Optional[Any]       , lowerCAmelCase :    Optional[Any]=("train",)       )       ->					Any:






    """simple docstring"""




    assert isinstance(lowerCAmelCase       , lowerCAmelCase       )
    for split in splits:
        UpperCAmelCase  	=    dataset_dict[split]
        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




@pytest.mark.parametrize('keep_in_memory'       , [False, True]       )
def 			lowercase__  (    lowerCAmelCase :    List[str]       , lowerCAmelCase :    Optional[int]       , lowerCAmelCase :    Optional[int]       )       ->					Optional[Any]:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        UpperCAmelCase  	=    CsvDatasetReader({'train': csv_path}       , cache_dir=lowerCAmelCase       , keep_in_memory=lowerCAmelCase       ).read()
    _check_csv_datasetdict(lowerCAmelCase       , lowerCAmelCase       )




@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 			lowercase__  (    lowerCAmelCase :    List[str]       , lowerCAmelCase :    Union[str, Any]       , lowerCAmelCase :    Optional[int]       )       ->					int:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    UpperCAmelCase  	=    features.copy() if features else default_expected_features
    UpperCAmelCase  	=    (
        Features({feature: Value(lowerCAmelCase       ) for feature, dtype in features.items()}       ) if features is not None else None
    )
    UpperCAmelCase  	=    CsvDatasetReader({'train': csv_path}       , features=lowerCAmelCase       , cache_dir=lowerCAmelCase       ).read()
    _check_csv_datasetdict(lowerCAmelCase       , lowerCAmelCase       )




@pytest.mark.parametrize('split'       , [None, NamedSplit('train'       ), 'train', 'test']       )
def 			lowercase__  (    lowerCAmelCase :    Tuple       , lowerCAmelCase :    Optional[Any]       , lowerCAmelCase :    List[Any]       )       ->					Dict:






    """simple docstring"""




    if split:
        UpperCAmelCase  	=    {split: csv_path}
    else:
        UpperCAmelCase  	=    {'train': csv_path, 'test': csv_path}
    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
    UpperCAmelCase  	=    CsvDatasetReader(lowerCAmelCase       , cache_dir=lowerCAmelCase       ).read()
    _check_csv_datasetdict(lowerCAmelCase       , lowerCAmelCase       , splits=list(path.keys()       )       )
    assert all(dataset[split].split == split for split in path.keys()       )




def 			lowercase__  (    lowerCAmelCase :    List[Any]       )       ->					Optional[Any]:






    """simple docstring"""




    with open(lowerCAmelCase       , encoding='utf-8'       ) as csvfile:
        yield from csv.reader(lowerCAmelCase       )




def 			lowercase__  (    lowerCAmelCase :    Union[str, Any]       , lowerCAmelCase :    int       )       ->					int:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    os.path.join(lowerCAmelCase       , 'tmp.csv'       )
    UpperCAmelCase  	=    CsvDatasetReader({'train': csv_path}       , cache_dir=lowerCAmelCase       ).read()
    CsvDatasetWriter(dataset['train']       , lowerCAmelCase       , num_proc=1       ).write()

    UpperCAmelCase  	=    iter_csv_file(lowerCAmelCase       )
    UpperCAmelCase  	=    iter_csv_file(lowerCAmelCase       )

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




def 			lowercase__  (    lowerCAmelCase :    List[Any]       , lowerCAmelCase :    Union[str, Any]       )       ->					str:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    os.path.join(lowerCAmelCase       , 'tmp.csv'       )
    UpperCAmelCase  	=    CsvDatasetReader({'train': csv_path}       , cache_dir=lowerCAmelCase       ).read()
    CsvDatasetWriter(dataset['train']       , lowerCAmelCase       , num_proc=2       ).write()

    UpperCAmelCase  	=    iter_csv_file(lowerCAmelCase       )
    UpperCAmelCase  	=    iter_csv_file(lowerCAmelCase       )

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







def 			lowercase__  (    lowerCAmelCase :    str       , lowerCAmelCase :    Optional[Any]       )       ->					str:






    """simple docstring"""




    UpperCAmelCase  	=    tmp_path / 'cache'
    UpperCAmelCase  	=    os.path.join(lowerCAmelCase       , 'tmp.csv'       )
    UpperCAmelCase  	=    CsvDatasetReader({'train': csv_path}       , cache_dir=lowerCAmelCase       ).read()
    with pytest.raises(lowerCAmelCase       ):
        CsvDatasetWriter(dataset['train']       , lowerCAmelCase       , num_proc=0       )





"""simple docstring"""

from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
   from .image_encoder import PaintByExampleImageEncoder
   from .pipeline_paint_by_example import PaintByExamplePipeline



