


"""simple docstring"""







import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


lowerCamelCase_  :  Dict     		=    5_0_0_0_0_0

lowerCamelCase_		,    lowerCamelCase_  :  Dict     		=    os.path.split(__file__)
lowerCamelCase_  :  Dict     		=    os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))
@get_duration
def _A		(		lowercase						):







    """simple docstring"""
    a											=dataset.select(range(0			,       len(lowercase						)			,       2						)						)
@get_duration
def _A		(		lowercase						):







    """simple docstring"""
    a											=dataset.sort('''numbers'''						)
@get_duration
def _A		(		lowercase						):







    """simple docstring"""
    a											=dataset.shuffle()
@get_duration
def _A		(		lowercase						):







    """simple docstring"""
    a											=dataset.train_test_split(0.1						)
@get_duration
def _A		(		lowercase			,       lowercase=10						):







    """simple docstring"""
    for shard_id in range(lowercase						):
        a											=dataset.shard(lowercase			,       lowercase						)
def _A		(		):







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







import unittest

from datasets import load_dataset

from transformers import load_tool

from .test_tools_common import ToolTesterMixin






class  __A							(			unittest.TestCase,       _SCREAMING_SNAKE_CASE     ):






 """simple docstring"""




 def  SCREAMING_SNAKE_CASE				(						self		)   ->	str:
     a											=load_tool('''document-question-answering'''		)
     self.tool.setup()
     a											=load_tool('''document-question-answering'''					,       remote=__A		)


 def  SCREAMING_SNAKE_CASE				(						self		)   ->	Optional[Any]:
     a											=load_dataset('''hf-internal-testing/example-documents'''					,       split='''test'''		)
     a											=dataset[0]['''image''']

     a											=self.tool(__A					,       '''When is the coffee break?'''		)
     self.assertEqual(__A					,       '''11-14 to 11:39 a.m.'''		)


 def  SCREAMING_SNAKE_CASE				(						self		)   ->	Optional[int]:
     a											=load_dataset('''hf-internal-testing/example-documents'''					,       split='''test'''		)
     a											=dataset[0]['''image''']

     a											=self.remote_tool(__A					,       '''When is the coffee break?'''		)
     self.assertEqual(__A					,       '''11-14 to 11:39 a.m.'''		)


 def  SCREAMING_SNAKE_CASE				(						self		)   ->	Union[str, Any]:
     a											=load_dataset('''hf-internal-testing/example-documents'''					,       split='''test'''		)
     a											=dataset[0]['''image''']

     self.tool(document=__A					,       question='''When is the coffee break?'''		)





 def  SCREAMING_SNAKE_CASE				(						self		)   ->	Optional[int]:
     a											=load_dataset('''hf-internal-testing/example-documents'''					,       split='''test'''		)
     a											=dataset[0]['''image''']

     a											=self.remote_tool(document=__A					,       question='''When is the coffee break?'''		)
     self.assertEqual(__A					,       '''11-14 to 11:39 a.m.'''		)