




'''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							:      Optional[int] 	=       (30, 487)
A							:      str 	=       (36, 1_024)
A							:      int 	=       (100, 100)
A							:      List[Any] 	=       100

A							:      Optional[int] 	=       datasets.Features(
    {"""text""": ArrayaD(SHAPE_TEST_1, dtype="""float32"""), """image""": ArrayaD(SHAPE_TEST_2, dtype="""float32""")}
)

A	, A							:      Optional[Any] 	=       os.path.split(__file__)
A							:      Tuple 	=       os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))
@get_duration
def 				snake_case_  (   a__		:	Optional[Any]    ,a__		:	int    ,a__		:	Tuple			):



    """simple docstring"""




    with ArrowWriter(features=__UpperCAmelCase    ,path=os.path.join(__UpperCAmelCase    ,"""beta.arrow"""			)			) as writer:
        for key, record in dummy_data:
            __lowercase							=						my_features.encode_example(__UpperCAmelCase			)
            writer.write(__UpperCAmelCase			)
        __lowercase				,__lowercase							=						writer.finalize()
@get_duration
def 				snake_case_  (   a__		:	List[Any]    ,a__		:	Union[str, Any]			):



    """simple docstring"""




    __lowercase							=						datasets.Dataset.from_file(
        filename=os.path.join(__UpperCAmelCase    ,"""beta.arrow"""			)    ,info=datasets.DatasetInfo(features=__UpperCAmelCase			)			)
    for _ in dataset:
        pass
@get_duration
def 				snake_case_  (   a__		:	Optional[int]    ,a__		:	List[Any]			):



    """simple docstring"""




    __lowercase							=						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 				snake_case_  (   a__		:	Dict    ,a__		:	Any			):



    """simple docstring"""




    __lowercase							=						10
    __lowercase							=						datasets.Dataset.from_file(
        filename=os.path.join(__UpperCAmelCase    ,"""beta.arrow"""			)    ,info=datasets.DatasetInfo(features=__UpperCAmelCase			)			)
    for i in range(0    ,len(__UpperCAmelCase			)    ,__UpperCAmelCase			):
        __lowercase							=						dataset[i : i + batch_size]
@get_duration
def 				snake_case_  (   a__		:	Tuple    ,a__		:	List[str]			):



    """simple docstring"""




    __lowercase							=						10
    __lowercase							=						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			):
        __lowercase							=						dataset[i : i + batch_size]
@get_duration
def 				snake_case_  (   a__		:	Tuple    ,a__		:	List[str]			):



    """simple docstring"""




    __lowercase							=						datasets.Dataset.from_file(
        filename=os.path.join(__UpperCAmelCase    ,"""beta.arrow"""			)    ,info=datasets.DatasetInfo(features=__UpperCAmelCase			)			)
    for col in feats:
        __lowercase							=						dataset[col]
@get_duration
def 				snake_case_  (   a__		:	str    ,a__		:	Any			):



    """simple docstring"""




    __lowercase							=						datasets.Dataset.from_file(
        filename=os.path.join(__UpperCAmelCase    ,"""beta.arrow"""			)    ,info=datasets.DatasetInfo(features=__UpperCAmelCase			)			)
    dataset.set_format("""numpy"""			)
    for col in feats:
        __lowercase							=						dataset[col]
def 				snake_case_  (   ):



    """simple docstring"""




    __lowercase							=						{}
    __lowercase							=						(
        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:
        __lowercase							=						datasets.Features({"""image""": ArrayaD(__UpperCAmelCase    ,dtype="""float32"""			)}			)
        __lowercase							=						generate_examples(features=__UpperCAmelCase    ,num_examples=__UpperCAmelCase			)
        __lowercase							=						write(__UpperCAmelCase    ,__UpperCAmelCase    ,__UpperCAmelCase			)
        for read_func in read_functions:
            __lowercase							=						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])}
        # )
        __lowercase							=						datasets.Features({"""image""": datasets.Sequence(datasets.Sequence(datasets.Value("""float32"""			)			)			)}			)
        __lowercase							=						generate_examples(
            features=__UpperCAmelCase    ,num_examples=__UpperCAmelCase    ,seq_shapes={"""image""": SPEED_TEST_SHAPE}			)
        __lowercase							=						write(__UpperCAmelCase    ,__UpperCAmelCase    ,__UpperCAmelCase			)
        for read_func in read_functions:
            __lowercase							=						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])}
        # )
        __lowercase							=						datasets.Features({"""image""": datasets.Sequence(datasets.Value("""float32"""			)			)}			)
        __lowercase							=						generate_examples(
            features=__UpperCAmelCase    ,num_examples=__UpperCAmelCase    ,seq_shapes={"""image""": [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}    ,)
        __lowercase							=						write(__UpperCAmelCase    ,__UpperCAmelCase    ,__UpperCAmelCase			)
        for read_func in read_functions:
            __lowercase							=						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()









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase_	       =   {"configuration_vit_hybrid": ["VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTHybridConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_	       =   [
							    "VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "ViTHybridForImageClassification",
							    "ViTHybridModel",
							    "ViTHybridPreTrainedModel",
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_	       =   ["ViTHybridImageProcessor"]


if TYPE_CHECKING:
							from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_vit_hybrid import (
														    VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ViTHybridForImageClassification,
														    ViTHybridModel,
														    ViTHybridPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
							import sys

							UpperCamelCase_	       =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





