




'''simple docstring'''




import json
import os
import tempfile

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import ArrayaD
from utils import generate_examples, get_duration


a_   :	List[Any]							   = (30, 4_87)
a_   :	Dict							   = (36, 10_24)
a_   :	List[str]							   = (1_00, 1_00)
a_   :	str							   = 1_00

a_   :	str							   = datasets.Features(
    {"""text""": ArrayaD(SHAPE_TEST_1, dtype="""float32"""), """image""": ArrayaD(SHAPE_TEST_2, dtype="""float32""")}
)

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





@get_duration
def   a_							(   __snake_case							:    Dict     , __snake_case							:    str     , __snake_case							:    int     )							->		List[str]:



       """simple docstring"""







       with ArrowWriter(features=_UpperCamelCase     , path=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     ) as writer:
              for key, record in dummy_data:
                     lowerCamelCase_							=my_features.encode_example(_UpperCamelCase     )
                     writer.write(_UpperCamelCase     )
              lowerCamelCase_,   lowerCamelCase_							=writer.finalize()





@get_duration
def   a_							(   __snake_case							:    int     , __snake_case							:    Any     )							->		Dict:



       """simple docstring"""
       lowerCamelCase_							=datasets.Dataset.from_file(
           filename=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     , info=datasets.DatasetInfo(features=_UpperCamelCase     )     )
       for _ in dataset:
              pass





@get_duration
def   a_							(   __snake_case							:    List[Any]     , __snake_case							:    Optional[Any]     )							->		Optional[int]:



       """simple docstring"""
       lowerCamelCase_							=datasets.Dataset.from_file(
           filename=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     , info=datasets.DatasetInfo(features=_UpperCamelCase     )     )
       dataset.set_format('''numpy'''     )
       for _ in dataset:
              pass





@get_duration
def   a_							(   __snake_case							:    Optional[int]     , __snake_case							:    Optional[int]     )							->		List[Any]:



       """simple docstring"""
       lowerCamelCase_							=10
       lowerCamelCase_							=datasets.Dataset.from_file(
           filename=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     , info=datasets.DatasetInfo(features=_UpperCamelCase     )     )
       for i in range(0     , len(_UpperCamelCase     )     , _UpperCamelCase     ):
              lowerCamelCase_							=dataset[i : i + batch_size]





@get_duration
def   a_							(   __snake_case							:    int     , __snake_case							:    List[Any]     )							->		Any:



       """simple docstring"""
       lowerCamelCase_							=10
       lowerCamelCase_							=datasets.Dataset.from_file(
           filename=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     , info=datasets.DatasetInfo(features=_UpperCamelCase     )     )
       dataset.set_format('''numpy'''     )
       for i in range(0     , len(_UpperCamelCase     )     , _UpperCamelCase     ):
              lowerCamelCase_							=dataset[i : i + batch_size]





@get_duration
def   a_							(   __snake_case							:    str     , __snake_case							:    List[str]     )							->		List[Any]:



       """simple docstring"""
       lowerCamelCase_							=datasets.Dataset.from_file(
           filename=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     , info=datasets.DatasetInfo(features=_UpperCamelCase     )     )
       for col in feats:
              lowerCamelCase_							=dataset[col]





@get_duration
def   a_							(   __snake_case							:    List[Any]     , __snake_case							:    Union[str, Any]     )							->		Tuple:



       """simple docstring"""
       lowerCamelCase_							=datasets.Dataset.from_file(
           filename=os.path.join(_UpperCamelCase     , '''beta.arrow'''     )     , info=datasets.DatasetInfo(features=_UpperCamelCase     )     )
       dataset.set_format('''numpy'''     )
       for col in feats:
              lowerCamelCase_							=dataset[col]





def   a_							(   )							->		Tuple:



       """simple docstring"""
       lowerCamelCase_							={}
       lowerCamelCase_							=(
           read_unformated,
           read_formatted_as_numpy,
           read_batch_unformated,
           read_batch_formatted_as_numpy,
           read_col_unformated,
           read_col_formatted_as_numpy,
       )
       with tempfile.TemporaryDirectory() as tmp_dir:
              lowerCamelCase_							=datasets.Features({'''image''': ArrayaD(_UpperCamelCase     , dtype='''float32'''     )}     )
              lowerCamelCase_							=generate_examples(features=_UpperCamelCase     , num_examples=_UpperCamelCase     )
              lowerCamelCase_							=write(_UpperCamelCase     , _UpperCamelCase     , _UpperCamelCase     )
              for read_func in read_functions:
                     lowerCamelCase_							=read_func(_UpperCamelCase     , _UpperCamelCase     )

       with tempfile.TemporaryDirectory() as tmp_dir:
              # don't use fixed length for fair comparison
              # feats = datasets.Features(
              #     {"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), SPEED_TEST_SHAPE[1]), SPEED_TEST_SHAPE[0])}
              # )
              lowerCamelCase_							=datasets.Features({'''image''': datasets.Sequence(datasets.Sequence(datasets.Value('''float32'''     )     )     )}     )
              lowerCamelCase_							=generate_examples(
                  features=_UpperCamelCase     , num_examples=_UpperCamelCase     , seq_shapes={'''image''': SPEED_TEST_SHAPE}     )
              lowerCamelCase_							=write(_UpperCamelCase     , _UpperCamelCase     , _UpperCamelCase     )
              for read_func in read_functions:
                     lowerCamelCase_							=read_func(_UpperCamelCase     , _UpperCamelCase     )

       with tempfile.TemporaryDirectory() as tmp_dir:
              # don't use fixed length for fair comparison
              # feats = datasets.Features(
              #     {"image": datasets.Sequence(datasets.Value("float32"), SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1])}
              # )
              lowerCamelCase_							=datasets.Features({'''image''': datasets.Sequence(datasets.Value('''float32'''     )     )}     )
              lowerCamelCase_							=generate_examples(
                  features=_UpperCamelCase     , num_examples=_UpperCamelCase     , seq_shapes={'''image''': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}     , )
              lowerCamelCase_							=write(_UpperCamelCase     , _UpperCamelCase     , _UpperCamelCase     )
              for read_func in read_functions:
                     lowerCamelCase_							=read_func(_UpperCamelCase     , _UpperCamelCase     )

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


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










'''simple docstring'''




import warnings

from .generation import FlaxGenerationMixin


class 						__UpperCamelCase (				lowerCamelCase__       ):
       # warning at import time
       warnings.warn(
           'Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will '
           'be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead.'    ,      lowerCamelCase__    ,      )




