





'''simple docstring'''






A__    :       Optional[int]              ={
    '''meter''': '''m''',
    '''kilometer''': '''km''',
    '''megametre''': '''Mm''',
    '''gigametre''': '''Gm''',
    '''terametre''': '''Tm''',
    '''petametre''': '''Pm''',
    '''exametre''': '''Em''',
    '''zettametre''': '''Zm''',
    '''yottametre''': '''Ym''',
}
# Exponent of the factor(meter)
A__    :       List[str]              ={
    '''m''': 0,
    '''km''': 3,
    '''Mm''': 6,
    '''Gm''': 9,
    '''Tm''': 12,
    '''Pm''': 15,
    '''Em''': 18,
    '''Zm''': 21,
    '''Ym''': 24,
}
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase												=							from_type.lower().strip("""s"""  )
      _lowerCAmelCase												=							to_type.lower().strip("""s"""  )

      _lowerCAmelCase												=							UNIT_SYMBOL.get(lowerCAmelCase							,     lowerCAmelCase  )
      _lowerCAmelCase												=							UNIT_SYMBOL.get(lowerCAmelCase							,     lowerCAmelCase  )

      if from_sanitized not in METRIC_CONVERSION:
            _lowerCAmelCase												=							(
                f"Invalid 'from_type' value: {from_type!r}.\n"
                f"Conversion abbreviations are: {', '.join(lowerCAmelCase  )}"
            )
            raise ValueError(lowerCAmelCase  )
      if to_sanitized not in METRIC_CONVERSION:
            _lowerCAmelCase												=							(
                f"Invalid 'to_type' value: {to_type!r}.\n"
                f"Conversion abbreviations are: {', '.join(lowerCAmelCase  )}"
            )
            raise ValueError(lowerCAmelCase  )
      _lowerCAmelCase												=							METRIC_CONVERSION[from_sanitized]
      _lowerCAmelCase												=							METRIC_CONVERSION[to_sanitized]
      _lowerCAmelCase												=							1

      if from_exponent > to_exponent:
            _lowerCAmelCase												=							from_exponent - to_exponent
      else:
            _lowerCAmelCase												=							-(to_exponent - from_exponent)

      return value * pow(10							,     lowerCAmelCase  )


if __name__ == "__main__":
      from doctest import testmod

      testmod()












'''simple docstring'''






import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


A__    :       str              =5_00_00
A__    :       Optional[int]              =50_00

A__       ,						A__    :       Optional[int]              =os.path.split(__file__)
A__    :       Tuple              =os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))
@get_duration
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      for i in range(lowerCAmelCase  ):
            _lowerCAmelCase												=							dataset[i]
@get_duration
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      for i in range(0							,     len(lowerCAmelCase  )							,     lowerCAmelCase  ):
            _lowerCAmelCase												=							dataset[i : i + batch_size]
@get_duration
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      with dataset.formatted_as(type=lowerCAmelCase  ):
            for i in range(lowerCAmelCase  ):
                  _lowerCAmelCase												=							dataset[i]
@get_duration
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      with dataset.formatted_as(type=lowerCAmelCase  ):
            for i in range(0							,     lowerCAmelCase							,     lowerCAmelCase  ):
                  _lowerCAmelCase												=							dataset[i : i + batch_size]
def        UpperCamelCase__				(		):





      """simple docstring"""


      _lowerCAmelCase												=							{"""num examples""": SPEED_TEST_N_EXAMPLES}
      _lowerCAmelCase												=							[
          (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""": 1_00}),
          (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 10_00}),
          (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""": 10_00}),
      ]

      _lowerCAmelCase												=							[
          (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""": 1_00}),
          (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 10_00}),
          (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""": 10_00}),
      ]
      with tempfile.TemporaryDirectory() as tmp_dir:
            print("""generating dataset"""  )
            _lowerCAmelCase												=							datasets.Features(
                {"""list""": datasets.Sequence(datasets.Value("""float32"""  )  ), """numbers""": datasets.Value("""float32"""  )}  )
            _lowerCAmelCase												=							generate_example_dataset(
                os.path.join(lowerCAmelCase							,     """dataset.arrow"""  )							,     lowerCAmelCase							,     num_examples=lowerCAmelCase							,     seq_shapes={"""list""": (1_00,)}							,     )
            print("""first set of iterations"""  )
            for func, kwargs in functions:
                  print(func.__name__							,     str(lowerCAmelCase  )  )
                  _lowerCAmelCase												=							func(lowerCAmelCase							,     **lowerCAmelCase  )

            print("""shuffling dataset"""  )
            _lowerCAmelCase												=							dataset.shuffle()
            print("""Second set of iterations (after shuffling"""  )
            for func, kwargs in functions_shuffled:
                  print("""shuffled """							,     func.__name__							,     str(lowerCAmelCase  )  )
                  _lowerCAmelCase												=							func(
                      lowerCAmelCase							,     **lowerCAmelCase  )

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


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






