






'''simple docstring'''

import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


A:      Optional[Any]  				=				5_0_0_0_0
A:      Dict  				=				5_0_0_0

A				,		A:      List[str]  				=				os.path.split(__file__)
A:      List[str]  				=				os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))






@get_duration
def 	_UpperCAmelCase    (  a		:	datasets.Dataset						,			a		:	Optional[int]							)			->			List[str]:





						"""simple docstring"""







						for i in range(lowerCAmelCase__							):
												lowercase_      :   Optional[int]        =			dataset[i]






@get_duration
def 	_UpperCAmelCase    (  a		:	datasets.Dataset						,			a		:	Tuple						,			a		:	str							)			->			Optional[Any]:





						"""simple docstring"""







						for i in range(0						,			len(lowerCAmelCase__							)						,			lowerCAmelCase__							):
												lowercase_      :   str        =			dataset[i : i + batch_size]






@get_duration
def 	_UpperCAmelCase    (  a		:	datasets.Dataset						,			a		:	List[Any]						,			a		:	Tuple							)			->			List[Any]:





						"""simple docstring"""







						with dataset.formatted_as(type=lowerCAmelCase__							):
												for i in range(lowerCAmelCase__							):
																		lowercase_      :   Tuple        =			dataset[i]






@get_duration
def 	_UpperCAmelCase    (  a		:	datasets.Dataset						,			a		:	List[Any]						,			a		:	Dict						,			a		:	int							)			->			Optional[Any]:





						"""simple docstring"""







						with dataset.formatted_as(type=lowerCAmelCase__							):
												for i in range(0						,			lowerCAmelCase__						,			lowerCAmelCase__							):
																		lowercase_      :   Union[str, Any]        =			dataset[i : i + batch_size]






def 	_UpperCAmelCase    (  )			->			str:





						"""simple docstring"""
						lowercase_      :   str        =			{'num examples': SPEED_TEST_N_EXAMPLES}
						lowercase_      :   Any        =			[
						    (read, {'length': SMALL_TEST}),
						    (read, {'length': SPEED_TEST_N_EXAMPLES}),
						    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0}),
						    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0}),
						    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0_0}),
						    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
						    (read_formatted, {'type': 'pandas', 'length': SMALL_TEST}),
						    (read_formatted, {'type': 'torch', 'length': SMALL_TEST}),
						    (read_formatted, {'type': 'tensorflow', 'length': SMALL_TEST}),
						    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0}),
						    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0_0_0}),
						]

						lowercase_      :   str        =			[
						    (read, {'length': SMALL_TEST}),
						    (read, {'length': SPEED_TEST_N_EXAMPLES}),
						    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0}),
						    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0}),
						    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0_0}),
						    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
						    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0}),
						    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0_0_0}),
						]
						with tempfile.TemporaryDirectory() as tmp_dir:
												print('generating dataset'							)
												lowercase_      :   str        =			datasets.Features(
												    {'list': datasets.Sequence(datasets.Value('float32'							)							), 'numbers': datasets.Value('float32'							)}							)
												lowercase_      :   List[Any]        =			generate_example_dataset(
												    os.path.join(lowerCAmelCase__						,			'dataset.arrow'							)						,			lowerCAmelCase__						,			num_examples=lowerCAmelCase__						,			seq_shapes={'list': (1_0_0,)}						,			)
												print('first set of iterations'							)
												for func, kwargs in functions:
																		print(func.__name__						,			str(lowerCAmelCase__							)							)
																		lowercase_      :   Tuple        =			func(lowerCAmelCase__						,			**lowerCAmelCase__							)

												print('shuffling dataset'							)
												lowercase_      :   str        =			dataset.shuffle()
												print('Second set of iterations (after shuffling'							)
												for func, kwargs in functions_shuffled:
																		print('shuffled '						,			func.__name__						,			str(lowerCAmelCase__							)							)
																		lowercase_      :   Optional[Any]        =			func(
																		    lowerCAmelCase__						,			**lowerCAmelCase__							)

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


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








'''simple docstring'''

from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url






class 							__magic_name__     (	UpperCAmelCase_				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      Union[str, Any]        =  ''
	SCREAMING_SNAKE_CASE_					:      Union[str, Any]        =  'hf-legacy'  # "hf://"" is reserved for hffs
	def __init__(							self  ,      _lowercase = None  ,      _lowercase = None  ,      **_lowercase  ,      )						->  Optional[Any]:
							super().__init__(self  ,      **_lowercase       )
							lowercase_      :   int        =			repo_info
							lowercase_      :   List[Any]        =			token
							lowercase_      :   Union[str, Any]        =			None
	def        lowerCamelCase__		(							self       )						->  Optional[Any]:
							if self.dir_cache is None:
													lowercase_      :   Optional[Any]        =			{}
													for hf_file in self.repo_info.siblings:
																			# TODO(QL): add sizes
																			lowercase_      :   str        =			{
																			    'name': hf_file.rfilename,
																			    'size': None,
																			    'type': 'file',
																			}
																			self.dir_cache.update(
																			    {
																			        str(_lowercase       ): {'name': str(_lowercase       ), 'size': None, 'type': 'directory'}
																			        for d in list(PurePosixPath(hf_file.rfilename       ).parents       )[:-1]
																			    }       )
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = "rb"  ,      **_lowercase  ,      )						->  Dict:
							if not isinstance(self.repo_info  ,      _lowercase       ):
													raise NotImplementedError(f"Open is only implemented for dataset repositories, but got {self.repo_info}"       )
							lowercase_      :   Optional[int]        =			hf_hub_url(self.repo_info.id  ,      _lowercase  ,      revision=self.repo_info.sha       )
							return fsspec.open(
							    _lowercase  ,      mode=_lowercase  ,      headers=get_authentication_headers_for_url(_lowercase  ,      use_auth_token=self.token       )  ,      client_kwargs={'trust_env': True}  ,      ).open()
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      **_lowercase       )						->  Tuple:
							self._get_dirs()
							lowercase_      :   str        =			self._strip_protocol(_lowercase       )
							if path in self.dir_cache:
													return self.dir_cache[path]
							else:
													raise FileNotFoundError(_lowercase       )







	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase=False  ,      **_lowercase       )						->  List[str]:
							self._get_dirs()
							lowercase_      :   List[str]        =			PurePosixPath(path.strip('/'       )       )
							lowercase_      :   List[str]        =			{}
							for p, f in self.dir_cache.items():
													lowercase_      :   Tuple        =			PurePosixPath(p.strip('/'       )       )
													lowercase_      :   Optional[int]        =			p.parent
													if root == path:
																			lowercase_      :   List[str]        =			f
							lowercase_      :   List[str]        =			list(paths.values()       )
							if detail:
													return out
							else:
													return sorted(f['name'] for f in out       )
