





from typing import List

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


_a						=   logging.get_logger(__name__)

_a						=   {
    "snap-research/efficientformer-l1-300": (
        "https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"
    ),
}






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			lowerCAmelCase_							  =		"""efficientformer"""





			def __init__(					self ,						__lowerCAmelCase = [3, 2, 6, 4] ,						__lowerCAmelCase = [4_8, 9_6, 2_2_4, 4_4_8] ,						__lowerCAmelCase = [True, True, True, True] ,						__lowerCAmelCase = 4_4_8 ,						__lowerCAmelCase = 3_2 ,						__lowerCAmelCase = 4 ,						__lowerCAmelCase = 7 ,						__lowerCAmelCase = 5 ,						__lowerCAmelCase = 8 ,						__lowerCAmelCase = 4 ,						__lowerCAmelCase = 0.0 ,						__lowerCAmelCase = 1_6 ,						__lowerCAmelCase = 3 ,						__lowerCAmelCase = 3 ,						__lowerCAmelCase = 3 ,						__lowerCAmelCase = 2 ,						__lowerCAmelCase = 1 ,						__lowerCAmelCase = 0.0 ,						__lowerCAmelCase = 1 ,						__lowerCAmelCase = True ,						__lowerCAmelCase = True ,						__lowerCAmelCase = 1E-5 ,						__lowerCAmelCase = "gelu" ,						__lowerCAmelCase = 0.02 ,						__lowerCAmelCase = 1E-12 ,						__lowerCAmelCase = 2_2_4 ,						__lowerCAmelCase = 1E-05 ,						**__lowerCAmelCase ,						):



				'''simple docstring'''







				super().__init__(**__lowerCAmelCase							)

				lowerCamelCase__              =	hidden_act
				lowerCamelCase__              =	hidden_dropout_prob
				lowerCamelCase__              =	hidden_sizes
				lowerCamelCase__              =	num_hidden_layers
				lowerCamelCase__              =	num_attention_heads
				lowerCamelCase__              =	initializer_range
				lowerCamelCase__              =	layer_norm_eps
				lowerCamelCase__              =	patch_size
				lowerCamelCase__              =	num_channels
				lowerCamelCase__              =	depths
				lowerCamelCase__              =	mlp_expansion_ratio
				lowerCamelCase__              =	downsamples
				lowerCamelCase__              =	dim
				lowerCamelCase__              =	key_dim
				lowerCamelCase__              =	attention_ratio
				lowerCamelCase__              =	resolution
				lowerCamelCase__              =	pool_size
				lowerCamelCase__              =	downsample_patch_size
				lowerCamelCase__              =	downsample_stride
				lowerCamelCase__              =	downsample_pad
				lowerCamelCase__              =	drop_path_rate
				lowerCamelCase__              =	num_metaad_blocks
				lowerCamelCase__              =	distillation
				lowerCamelCase__              =	use_layer_scale
				lowerCamelCase__              =	layer_scale_init_value
				lowerCamelCase__              =	image_size
				lowerCamelCase__              =	batch_norm_eps










import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


_a						=   namedtuple(
    "_TestCommandArgs",
    [
        "dataset",
        "name",
        "cache_dir",
        "data_dir",
        "all_configs",
        "save_infos",
        "ignore_verifications",
        "force_redownload",
        "clear_cache",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   List[str]:







	'''simple docstring'''







	return (abs(source - target							) / target) < 0.0_1





@pytest.mark.integration
def lowerCAmelCase__(__snake_case							)       ->   Tuple:







	'''simple docstring'''







	lowerCamelCase__              =	_TestCommandArgs(dataset=__snake_case ,all_configs=__snake_case ,save_infos=__snake_case							)
	lowerCamelCase__              =	TestCommand(*__snake_case							)
	test_command.run()
	lowerCamelCase__              =	os.path.join(__snake_case ,'''README.md'''							)
	assert os.path.exists(__snake_case							)
	lowerCamelCase__              =	DatasetInfosDict.from_directory(__snake_case							)
	lowerCamelCase__              =	DatasetInfosDict(
	    {
	        '''default''': DatasetInfo(
	            features=Features(
	                {
	                    '''tokens''': Sequence(Value('''string'''							)							),
	                    '''ner_tags''': Sequence(
	                        ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']							)							),
	                    '''langs''': Sequence(Value('''string'''							)							),
	                    '''spans''': Sequence(Value('''string'''							)							),
	                }							) ,splits=[
	                {
	                    '''name''': '''train''',
	                    '''num_bytes''': 2351563,
	                    '''num_examples''': 10000,
	                },
	                {
	                    '''name''': '''validation''',
	                    '''num_bytes''': 238418,
	                    '''num_examples''': 1000,
	                },
	            ] ,download_size=3940680 ,dataset_size=2589981 ,)
	    }							)
	assert dataset_infos.keys() == expected_dataset_infos.keys()
	for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
		lowerCamelCase__       ,			lowerCamelCase__              =	getattr(dataset_infos['''default'''] ,__snake_case							), getattr(expected_dataset_infos['''default'''] ,__snake_case							)
		if key == "num_bytes":
			assert is_apercent_close(__snake_case ,__snake_case							)
		elif key == "splits":
			assert list(__snake_case							) == list(__snake_case							)
			for split in result:
				assert result[split].name == expected[split].name
				assert result[split].num_examples == expected[split].num_examples
				assert is_apercent_close(result[split].num_bytes ,expected[split].num_bytes							)
		else:
			result == expected



