





'''simple docstring'''







import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
					from PIL import Image


class        __a   (unittest.TestCase							,		lowerCamelCase  ):

							def      UpperCAmelCase__						(				self				:  int )       ->							Dict:







													"""simple docstring"""
													UpperCAmelCase_      :   Optional[Any]      =	load_tool('''image-question-answering''' )
													self.tool.setup()
													UpperCAmelCase_      :   Optional[int]      =	load_tool('''image-question-answering'''							,  remote=__magic_name__ )

							def      UpperCAmelCase__						(				self				:  int )       ->							int:







													"""simple docstring"""
													UpperCAmelCase_      :   Dict      =	Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO''' ) ) / '''000000039769.png''' )
													UpperCAmelCase_      :   Tuple      =	self.tool(__magic_name__							,  '''How many cats are sleeping on the couch?''' )
													self.assertEqual(__magic_name__							,  '''2''' )

							def      UpperCAmelCase__						(				self				:  int )       ->							int:







													"""simple docstring"""
													UpperCAmelCase_      :   List[Any]      =	Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO''' ) ) / '''000000039769.png''' )
													UpperCAmelCase_      :   Union[str, Any]      =	self.remote_tool(__magic_name__							,  '''How many cats are sleeping on the couch?''' )
													self.assertEqual(__magic_name__							,  '''2''' )

							def      UpperCAmelCase__						(				self				:  Union[str, Any] )       ->							str:







													"""simple docstring"""
													UpperCAmelCase_      :   List[str]      =	Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO''' ) ) / '''000000039769.png''' )
													UpperCAmelCase_      :   Any      =	self.tool(image=__magic_name__							,  question='''How many cats are sleeping on the couch?''' )
													self.assertEqual(__magic_name__							,  '''2''' )



							def      UpperCAmelCase__						(				self				:  List[Any] )       ->							Optional[Any]:







													"""simple docstring"""
													UpperCAmelCase_      :   int      =	Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO''' ) ) / '''000000039769.png''' )
													UpperCAmelCase_      :   Dict      =	self.remote_tool(image=__magic_name__							,  question='''How many cats are sleeping on the couch?''' )
													self.assertEqual(__magic_name__							,  '''2''' )







import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


_UpperCAmelCase   :					str    =			100_000_000_000
_UpperCAmelCase   :					Optional[int]    =			10_000

_UpperCAmelCase  ,_UpperCAmelCase   :					Optional[int]    =			os.path.split(__file__)
_UpperCAmelCase   :					Optional[int]    =			os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))


def  A			(   lowercase       ,			lowercase					)  ->    datasets.Dataset:
		'''simple docstring'''

		UpperCamelCase            =	pa.Table.from_pydict({'col': [0] * chunk_size}					)
		UpperCamelCase            =	pa.concat_tables([table] * (num_examples // chunk_size)					)
		return datasets.Dataset(lowercase       ,			fingerprint='table_100B'					)


@dataclass
class 							lowercase   :
		__lowercase			:			int
		__lowercase			:			int
		__lowercase			:			int
		__lowercase			:			int



		def __UpperCamelCase					(					self			)    ->   Optional[int]:
				"""simple docstring"""
				UpperCamelCase            =	np.random.default_rng(self.seed			)
				UpperCamelCase            =	rng.integers(low=self.low							, high=self.high							, size=self.size			).tolist()



		def __iter__(					self			)    ->   List[str]:
				"""simple docstring"""
				return iter(self._sampled_values			)



		def __len__(					self			)    ->   int:
				"""simple docstring"""
				return self.size






@get_duration
def  A			(   lowercase					)  ->    List[Any]:
		'''simple docstring'''

		UpperCamelCase            =	dataset[0]


@get_duration
def  A			(   lowercase					)  ->    Any:
		'''simple docstring'''

		UpperCamelCase            =	dataset[-1]


@get_duration
def  A			(   lowercase					)  ->    List[Any]:
		'''simple docstring'''

		UpperCamelCase            =	dataset[range(len(lowercase					) // 2       ,			len(lowercase					) // 2 + 1_024					)]


@get_duration
def  A			(   lowercase					)  ->    Any:
		'''simple docstring'''

		UpperCamelCase            =	dataset[RandIter(0       ,			len(lowercase					)       ,			1_024       ,			seed=42					)]


def  A			(   )  ->    List[Any]:
		'''simple docstring'''

		UpperCamelCase            =	{'num examples': SPEED_TEST_N_EXAMPLES}
		UpperCamelCase            =	(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
		print('generating dataset'					)
		UpperCamelCase            =	generate_100B_dataset(num_examples=lowercase       ,			chunk_size=lowercase					)
		print('Functions'					)
		for func in functions:
				print(func.__name__					)
				UpperCamelCase            =	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_table_100B()
