





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 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase					)     ->	Optional[int]:
    assert isinstance(_UpperCAmelCase		,      _UpperCAmelCase					)
    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 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	int:
    lowerCamelCase__       : Any   					=						tmp_path / 'cache'
    lowerCamelCase__       : Union[str, Any]   					=						{'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        lowerCamelCase__       : Optional[int]   					=						SqlDatasetReader(
            'dataset'		,      'sqlite:///' + sqlite_path		,      cache_dir=_UpperCAmelCase		,      keep_in_memory=_UpperCAmelCase					).read()
    _check_sql_dataset(_UpperCAmelCase		,      _UpperCAmelCase					)


@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 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	str:
    lowerCamelCase__       : Any   					=						tmp_path / 'cache'
    lowerCamelCase__       : Any   					=						{'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
    lowerCamelCase__       : Tuple   					=						features.copy() if features else default_expected_features
    lowerCamelCase__       : str   					=						(
        Features({feature: Value(_UpperCAmelCase					) for feature, dtype in features.items()}					) if features is not None else None
    )
    lowerCamelCase__       : Any   					=						SqlDatasetReader('dataset'		,      'sqlite:///' + sqlite_path		,      features=_UpperCAmelCase		,      cache_dir=_UpperCAmelCase					).read()
    _check_sql_dataset(_UpperCAmelCase		,      _UpperCAmelCase					)


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase					)     ->	Optional[int]:
    with contextlib.closing(sqlitea.connect(_UpperCAmelCase					)					) as con:
        lowerCamelCase__       : List[str]   					=						con.cursor()
        cur.execute('SELECT * FROM dataset'					)
        for row in cur:
            yield row


@require_sqlalchemy
def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	Dict:
    lowerCamelCase__       : Union[str, Any]   					=						tmp_path / 'cache'
    lowerCamelCase__       : str   					=						os.path.join(_UpperCAmelCase		,      'tmp.sql'					)
    lowerCamelCase__       : Optional[Any]   					=						SqlDatasetReader('dataset'		,      'sqlite:///' + sqlite_path		,      cache_dir=_UpperCAmelCase					).read()
    SqlDatasetWriter(_UpperCAmelCase		,      'dataset'		,      'sqlite:///' + output_sqlite_path		,      num_proc=1					).write()

    lowerCamelCase__       : List[str]   					=						iter_sql_file(_UpperCAmelCase					)
    lowerCamelCase__       : List[Any]   					=						iter_sql_file(_UpperCAmelCase					)

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


@require_sqlalchemy
def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	int:
    lowerCamelCase__       : Optional[int]   					=						tmp_path / 'cache'
    lowerCamelCase__       : Optional[Any]   					=						os.path.join(_UpperCAmelCase		,      'tmp.sql'					)
    lowerCamelCase__       : int   					=						SqlDatasetReader('dataset'		,      'sqlite:///' + sqlite_path		,      cache_dir=_UpperCAmelCase					).read()
    SqlDatasetWriter(_UpperCAmelCase		,      'dataset'		,      'sqlite:///' + output_sqlite_path		,      num_proc=2					).write()

    lowerCamelCase__       : Optional[Any]   					=						iter_sql_file(_UpperCAmelCase					)
    lowerCamelCase__       : Optional[Any]   					=						iter_sql_file(_UpperCAmelCase					)

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


@require_sqlalchemy
def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	Optional[Any]:
    lowerCamelCase__       : int   					=						tmp_path / 'cache'
    lowerCamelCase__       : Optional[int]   					=						os.path.join(_UpperCAmelCase		,      'tmp.sql'					)
    lowerCamelCase__       : int   					=						SqlDatasetReader('dataset'		,      'sqlite:///' + sqlite_path		,      cache_dir=_UpperCAmelCase					).read()
    with pytest.raises(_UpperCAmelCase					):
        SqlDatasetWriter(_UpperCAmelCase		,      'dataset'		,      'sqlite:///' + output_sqlite_path		,      num_proc=0					).write()












from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCAmelCase							:			Any        =							logging.get_logger(__name__)

_UpperCAmelCase							:			Union[str, Any]        =							{
    """snap-research/efficientformer-l1-300""": (
        """https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"""
    ),
}

class   lowerCAmelCase				(   __UpperCamelCase     ):
 UpperCAmelCase__						=						"""efficientformer"""
 def __init__( self    : Dict     ,	UpperCAmelCase    : List[int] = [3, 2, 6, 4]     ,	UpperCAmelCase    : List[int] = [48, 96, 224, 448]     ,	UpperCAmelCase    : List[bool] = [True, True, True, True]     ,	UpperCAmelCase    : int = 448     ,	UpperCAmelCase    : int = 32     ,	UpperCAmelCase    : int = 4     ,	UpperCAmelCase    : int = 7     ,	UpperCAmelCase    : int = 5     ,	UpperCAmelCase    : int = 8     ,	UpperCAmelCase    : int = 4     ,	UpperCAmelCase    : float = 0.0     ,	UpperCAmelCase    : int = 16     ,	UpperCAmelCase    : int = 3     ,	UpperCAmelCase    : int = 3     ,	UpperCAmelCase    : int = 3     ,	UpperCAmelCase    : int = 2     ,	UpperCAmelCase    : int = 1     ,	UpperCAmelCase    : float = 0.0     ,	UpperCAmelCase    : int = 1     ,	UpperCAmelCase    : bool = True     ,	UpperCAmelCase    : bool = True     ,	UpperCAmelCase    : float = 1e-5     ,	UpperCAmelCase    : str = "gelu"     ,	UpperCAmelCase    : float = 0.0_2     ,	UpperCAmelCase    : float = 1e-12     ,	UpperCAmelCase    : int = 224     ,	UpperCAmelCase    : float = 1e-05     ,	**UpperCAmelCase    : Tuple     ,	)     ->      None:
     super().__init__(**UpperCAmelCase      )

     lowerCamelCase__       : Optional[Any]   					=						hidden_act
     lowerCamelCase__       : int   					=						hidden_dropout_prob
     lowerCamelCase__       : List[Any]   					=						hidden_sizes
     lowerCamelCase__       : int   					=						num_hidden_layers
     lowerCamelCase__       : int   					=						num_attention_heads
     lowerCamelCase__       : Dict   					=						initializer_range
     lowerCamelCase__       : Optional[Any]   					=						layer_norm_eps
     lowerCamelCase__       : int   					=						patch_size
     lowerCamelCase__       : List[Any]   					=						num_channels
     lowerCamelCase__       : List[str]   					=						depths
     lowerCamelCase__       : Any   					=						mlp_expansion_ratio
     lowerCamelCase__       : Any   					=						downsamples
     lowerCamelCase__       : str   					=						dim
     lowerCamelCase__       : Tuple   					=						key_dim
     lowerCamelCase__       : int   					=						attention_ratio
     lowerCamelCase__       : int   					=						resolution
     lowerCamelCase__       : Dict   					=						pool_size
     lowerCamelCase__       : List[str]   					=						downsample_patch_size
     lowerCamelCase__       : Tuple   					=						downsample_stride
     lowerCamelCase__       : int   					=						downsample_pad
     lowerCamelCase__       : Optional[int]   					=						drop_path_rate
     lowerCamelCase__       : Optional[Any]   					=						num_metaad_blocks
     lowerCamelCase__       : Any   					=						distillation
     lowerCamelCase__       : Optional[int]   					=						use_layer_scale
     lowerCamelCase__       : Union[str, Any]   					=						layer_scale_init_value
     lowerCamelCase__       : Optional[int]   					=						image_size
     lowerCamelCase__       : Optional[Any]   					=						batch_norm_eps





