




'''simple docstring'''







import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_lowerCamelCase				:		str				      =    500_000

_lowerCamelCase      ,_lowerCamelCase				:		List[Any]				      =    os.path.split(__file__)
_lowerCamelCase				:		Union[str, Any]				      =    os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))






@get_duration
def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			dataset.select(range(0		,				len(lowercase_    )		,				2    )    )






@get_duration
def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			dataset.sort("numbers"    )






@get_duration
def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			dataset.shuffle()






@get_duration
def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			dataset.train_test_split(0.1    )






@get_duration
def 						_lowercase						(      lowercase_		,				lowercase_=10    ):



		'''simple docstring'''







		for shard_id in range(lowercase_    ):
				_snake_case      			=			dataset.shard(lowercase_		,				lowercase_    )






def 						_lowercase						(      ):



		'''simple docstring'''







		_snake_case      			=			{"num examples": SPEED_TEST_N_EXAMPLES}
		_snake_case      			=			(select, sort, shuffle, train_test_split, shard)
		with tempfile.TemporaryDirectory() as tmp_dir:
				print("generating dataset"    )
				_snake_case      			=			datasets.Features({"text": datasets.Value("string"    ), "numbers": datasets.Value("float32"    )}    )
				_snake_case      			=			generate_example_dataset(
				    os.path.join(lowercase_		,				"dataset.arrow"    )		,				lowercase_		,				num_examples=lowercase_    )
				print("Functions"    )
				for func in functions:
						print(func.__name__    )
						_snake_case      			=			func(lowercase_    )

		with open(lowercase_		,				"wb"    ) as f:
				f.write(json.dumps(lowercase_    ).encode("utf-8"    )    )


if __name__ == "__main__":  # useful to run the profiler
						benchmark_indices_mapping()











'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase				:		List[str]				      =    logging.get_logger(__name__)

_lowerCamelCase				:		Optional[Any]				      =    {
    'MBZUAI/swiftformer-xs': 'https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json',
}





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					lowercase__       =					"""swiftformer"""






					def __init__(       self,    __UpperCamelCase=3,    __UpperCamelCase=[3, 3, 6, 4],    __UpperCamelCase=[48, 56, 112, 220],    __UpperCamelCase=4,    __UpperCamelCase=[True, True, True, True],    __UpperCamelCase="gelu",    __UpperCamelCase=3,    __UpperCamelCase=2,    __UpperCamelCase=1,    __UpperCamelCase=0.0,    __UpperCamelCase=True,    __UpperCamelCase=1E-5,    __UpperCamelCase=1E-5,    **__UpperCamelCase,    ):
							super().__init__(**__UpperCamelCase					)
							_snake_case      			=			num_channels
							_snake_case      			=			depths
							_snake_case      			=			embed_dims
							_snake_case      			=			mlp_ratio
							_snake_case      			=			downsamples
							_snake_case      			=			hidden_act
							_snake_case      			=			down_patch_size
							_snake_case      			=			down_stride
							_snake_case      			=			down_pad
							_snake_case      			=			drop_path_rate
							_snake_case      			=			use_layer_scale
							_snake_case      			=			layer_scale_init_value
							_snake_case      			=			batch_norm_eps





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					lowercase__       =					version.parse("""1.11"""				)






					@property
					def 							__SCREAMING_SNAKE_CASE      (       self					):
							return OrderedDict(
							    [
							        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
							    ]					)






					@property
					def 							__SCREAMING_SNAKE_CASE      (       self					):
							return 1E-4





