





'''simple docstring'''





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


UpperCAmelCase_  							=				5_0000
UpperCAmelCase_  							=				5000

UpperCAmelCase_							,     UpperCAmelCase_  							=				os.path.split(__file__)
UpperCAmelCase_  							=				os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))




@get_duration
def 	lowerCAmelCase_					(						__UpperCAmelCase:    datasets.Dataset	,     __UpperCAmelCase:    str   )   ->			Optional[Any]:
    for i in range(__UpperCAmelCase   ):
        UpperCamelCase__							:       Tuple      =   dataset[i]




@get_duration
def 	lowerCAmelCase_					(						__UpperCAmelCase:    datasets.Dataset	,     __UpperCAmelCase:    Any	,     __UpperCAmelCase:    Tuple   )   ->			Any:
    for i in range(0	,     len(__UpperCAmelCase   )	,     __UpperCAmelCase   ):
        UpperCamelCase__							:       List[Any]      =   dataset[i : i + batch_size]




@get_duration
def 	lowerCAmelCase_					(						__UpperCAmelCase:    datasets.Dataset	,     __UpperCAmelCase:    Optional[Any]	,     __UpperCAmelCase:    List[Any]   )   ->			List[str]:
    with dataset.formatted_as(type=__UpperCAmelCase   ):
        for i in range(__UpperCAmelCase   ):
            UpperCamelCase__							:       List[Any]      =   dataset[i]




@get_duration
def 	lowerCAmelCase_					(						__UpperCAmelCase:    datasets.Dataset	,     __UpperCAmelCase:    Optional[Any]	,     __UpperCAmelCase:    Dict	,     __UpperCAmelCase:    Optional[Any]   )   ->			Any:
    with dataset.formatted_as(type=__UpperCAmelCase   ):
        for i in range(0	,     __UpperCAmelCase	,     __UpperCAmelCase   ):
            UpperCamelCase__							:       Union[str, Any]      =   dataset[i : i + batch_size]




def 	lowerCAmelCase_					(						)   ->			List[str]:
    UpperCamelCase__							:       Dict      =   {'''num examples''': SPEED_TEST_N_EXAMPLES}
    UpperCamelCase__							:       str      =   [
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1000}),
        (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''': 10}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1000}),
    ]

    UpperCamelCase__							:       Union[str, Any]      =   [
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1000}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 10}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1000}),
    ]
    with tempfile.TemporaryDirectory() as tmp_dir:
        print('''generating dataset'''   )
        UpperCamelCase__							:       Union[str, Any]      =   datasets.Features(
            {'''list''': datasets.Sequence(datasets.Value('''float32'''   )   ), '''numbers''': datasets.Value('''float32'''   )}   )
        UpperCamelCase__							:       str      =   generate_example_dataset(
            os.path.join(__UpperCAmelCase	,     '''dataset.arrow'''   )	,     __UpperCAmelCase	,     num_examples=__UpperCAmelCase	,     seq_shapes={'''list''': (100,)}	,     )
        print('''first set of iterations'''   )
        for func, kwargs in functions:
            print(func.__name__	,     str(__UpperCAmelCase   )   )
            UpperCamelCase__							:       Optional[int]      =   func(__UpperCAmelCase	,     **__UpperCAmelCase   )

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








from __future__ import annotations




def 	lowerCAmelCase_					(						__UpperCAmelCase:    str	,     __UpperCAmelCase:    str   )   ->			bool:
    UpperCamelCase__							:       List[str]      =   get_failure_array(__UpperCAmelCase   )

    # 2) Step through text searching for pattern
    UpperCamelCase__     ,UpperCamelCase__							:       Dict      =   0, 0  # index into text, pattern
    while i < len(__UpperCAmelCase   ):
        if pattern[j] == text[i]:
            if j == (len(__UpperCAmelCase   ) - 1):
                return True
            j += 1

        # if this is a prefix in our pattern
        # just go back far enough to continue
        elif j > 0:
            UpperCamelCase__							:       Optional[int]      =   failure[j - 1]
            continue
        i += 1
    return False




def 	lowerCAmelCase_					(						__UpperCAmelCase:    str   )   ->			list[int]:
    UpperCamelCase__							:       Union[str, Any]      =   [0]
    UpperCamelCase__							:       Tuple      =   0
    UpperCamelCase__							:       Tuple      =   1
    while j < len(__UpperCAmelCase   ):
        if pattern[i] == pattern[j]:
            i += 1
        elif i > 0:
            UpperCamelCase__							:       str      =   failure[i - 1]
            continue
        j += 1
        failure.append(__UpperCAmelCase   )
    return failure


if __name__ == "__main__":
  # Test 1)
  UpperCAmelCase_  							=				'abc1abc12'
  UpperCAmelCase_  							=				'alskfjaldsabc1abc1abc12k23adsfabcabc'
  UpperCAmelCase_  							=				'alskfjaldsk23adsfabcabc'
  assert kmp(pattern, texta) and not kmp(pattern, texta)

  # Test 2)
  UpperCAmelCase_  							=				'ABABX'
  UpperCAmelCase_  							=				'ABABZABABYABABX'
  assert kmp(pattern, text)

  # Test 3)
  UpperCAmelCase_  							=				'AAAB'
  UpperCAmelCase_  							=				'ABAAAAAB'
  assert kmp(pattern, text)

  # Test 4)
  UpperCAmelCase_  							=				'abcdabcy'
  UpperCAmelCase_  							=				'abcxabcdabxabcdabcdabcy'
  assert kmp(pattern, text)

  # Test 5)
  UpperCAmelCase_  							=				'aabaabaaa'
  assert get_failure_array(pattern) == [0, 1, 0, 1, 2, 3, 4, 5, 2]

