"""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 					UpperCAmelCase    (		UpperCAmelCase						,					UpperCAmelCase					)				->      str:
     for i in range(UpperCAmelCase					):
          snake_case_					       =					dataset[i]







@get_duration
def 					UpperCAmelCase    (		UpperCAmelCase						,					UpperCAmelCase						,					UpperCAmelCase					)				->      Tuple:
     for i in range(0						,					len(UpperCAmelCase					)						,					UpperCAmelCase					):
          snake_case_					       =					dataset[i : i + batch_size]







@get_duration
def 					UpperCAmelCase    (		UpperCAmelCase						,					UpperCAmelCase						,					UpperCAmelCase					)				->      Optional[Any]:
     with dataset.formatted_as(type=UpperCAmelCase					):
          for i in range(UpperCAmelCase					):
               snake_case_					       =					dataset[i]







@get_duration
def 					UpperCAmelCase    (		UpperCAmelCase						,					UpperCAmelCase						,					UpperCAmelCase						,					UpperCAmelCase					)				->      int:
     with dataset.formatted_as(type=UpperCAmelCase					):
          for i in range(0						,					UpperCAmelCase						,					UpperCAmelCase					):
               snake_case_					       =					dataset[i : i + batch_size]







def 					UpperCAmelCase    (		)				->      Optional[Any]:
     snake_case_					       =					{'num examples': SPEED_TEST_N_EXAMPLES}
     snake_case_					       =					[
         (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}),
     ]

     snake_case_					       =					[
         (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'					)
          snake_case_					       =					datasets.Features(
              {'list': datasets.Sequence(datasets.Value('float32'					)					), 'numbers': datasets.Value('float32'					)}					)
          snake_case_					       =					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					)					)
               snake_case_					       =					func(UpperCAmelCase						,					**UpperCAmelCase					)

          print('shuffling dataset'					)
          snake_case_					       =					dataset.shuffle()
          print('Second set of iterations (after shuffling'					)
          for func, kwargs in functions_shuffled:
               print('shuffled '						,					func.__name__						,					str(UpperCAmelCase					)					)
               snake_case_					       =					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 typing import TYPE_CHECKING

from ..utils import _LazyModule


UpperCAmelCase__   	=							{
    '''config''': [
        '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
        '''OnnxConfig''',
        '''OnnxConfigWithPast''',
        '''OnnxSeq2SeqConfigWithPast''',
        '''PatchingSpec''',
    ],
    '''convert''': ['''export''', '''validate_model_outputs'''],
    '''features''': ['''FeaturesManager'''],
    '''utils''': ['''ParameterFormat''', '''compute_serialized_parameters_size'''],
}


if TYPE_CHECKING:
  from .config import (
      EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
      OnnxConfig,
      OnnxConfigWithPast,
      OnnxSeqaSeqConfigWithPast,
      PatchingSpec,
  )
  from .convert import export, validate_model_outputs
  from .features import FeaturesManager
  from .utils import ParameterFormat, compute_serialized_parameters_size

else:
  import sys

  UpperCAmelCase__   	=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

