
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


UpperCAmelCase__	:  Tuple      =   (30, 487)
UpperCAmelCase__	:  Tuple      =   (36, 1024)
UpperCAmelCase__	:  List[Any]      =   (100, 100)
UpperCAmelCase__	:  Any      =   100

UpperCAmelCase__	:  Tuple      =   datasets.Features(
    {'text': ArrayaD(SHAPE_TEST_1, dtype='float32'), 'image': ArrayaD(SHAPE_TEST_2, dtype='float32')}
)

UpperCAmelCase__	:  Tuple      =   os.path.split(__file__)
UpperCAmelCase__	:  Union[str, Any]      =   os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))






@get_duration
def 						lowerCamelCase__							(      a	,	a	,	a   )   ->     Any:
   with ArrowWriter(features=a	,	path=os.path.join(a	,	'''beta.arrow'''   )   ) as writer:
      for key, record in dummy_data:
         _A:						Tuple	    = my_features.encode_example(a   )
         writer.write(a   )
      _A:						Union[str, Any]	    = writer.finalize()






@get_duration
def 						lowerCamelCase__							(      a	,	a   )   ->     Tuple:
   _A:						Optional[Any]	    = datasets.Dataset.from_file(
       filename=os.path.join(a	,	'''beta.arrow'''   )	,	info=datasets.DatasetInfo(features=a   )   )
   for _ in dataset:
      pass






@get_duration
def 						lowerCamelCase__							(      a	,	a   )   ->     Optional[int]:
   _A:						Optional[int]	    = datasets.Dataset.from_file(
       filename=os.path.join(a	,	'''beta.arrow'''   )	,	info=datasets.DatasetInfo(features=a   )   )
   dataset.set_format('''numpy'''   )
   for _ in dataset:
      pass






@get_duration
def 						lowerCamelCase__							(      a	,	a   )   ->     Any:
   _A:						Optional[Any]	    = 10
   _A:						Any	    = datasets.Dataset.from_file(
       filename=os.path.join(a	,	'''beta.arrow'''   )	,	info=datasets.DatasetInfo(features=a   )   )
   for i in range(0	,	len(a   )	,	a   ):
      _A:						Union[str, Any]	    = dataset[i : i + batch_size]






@get_duration
def 						lowerCamelCase__							(      a	,	a   )   ->     Union[str, Any]:
   _A:						Optional[Any]	    = 10
   _A:						List[Any]	    = datasets.Dataset.from_file(
       filename=os.path.join(a	,	'''beta.arrow'''   )	,	info=datasets.DatasetInfo(features=a   )   )
   dataset.set_format('''numpy'''   )
   for i in range(0	,	len(a   )	,	a   ):
      _A:						List[Any]	    = dataset[i : i + batch_size]






@get_duration
def 						lowerCamelCase__							(      a	,	a   )   ->     Optional[Any]:
   _A:						Union[str, Any]	    = datasets.Dataset.from_file(
       filename=os.path.join(a	,	'''beta.arrow'''   )	,	info=datasets.DatasetInfo(features=a   )   )
   for col in feats:
      _A:						Optional[Any]	    = dataset[col]






@get_duration
def 						lowerCamelCase__							(      a	,	a   )   ->     Optional[int]:
   _A:						List[str]	    = datasets.Dataset.from_file(
       filename=os.path.join(a	,	'''beta.arrow'''   )	,	info=datasets.DatasetInfo(features=a   )   )
   dataset.set_format('''numpy'''   )
   for col in feats:
      _A:						Dict	    = dataset[col]






def 						lowerCamelCase__							(      )   ->     Any:
   _A:						List[str]	    = {}
   _A:						Optional[int]	    = (
       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:
      _A:						Dict	    = datasets.Features({'''image''': ArrayaD(a	,	dtype='''float32'''   )}   )
      _A:						Optional[Any]	    = generate_examples(features=a	,	num_examples=a   )
      _A:						Optional[int]	    = write(a	,	a	,	a   )
      for read_func in read_functions:
         _A:						List[str]	    = read_func(a	,	a   )

   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])}
      # )
      _A:						Optional[Any]	    = datasets.Features({'''image''': datasets.Sequence(datasets.Sequence(datasets.Value('''float32'''   )   )   )}   )
      _A:						Optional[Any]	    = generate_examples(
          features=a	,	num_examples=a	,	seq_shapes={'''image''': SPEED_TEST_SHAPE}   )
      _A:						Union[str, Any]	    = write(a	,	a	,	a   )
      for read_func in read_functions:
         _A:						Optional[Any]	    = read_func(a	,	a   )

   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])}
      # )
      _A:						List[Any]	    = datasets.Features({'''image''': datasets.Sequence(datasets.Value('''float32'''   )   )}   )
      _A:						Optional[Any]	    = generate_examples(
          features=a	,	num_examples=a	,	seq_shapes={'''image''': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}	,	)
      _A:						int	    = write(a	,	a	,	a   )
      for read_func in read_functions:
         _A:						Optional[Any]	    = read_func(a	,	a   )

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


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





from __future__ import annotations






def 						lowerCamelCase__							(      a	,	a   )   ->     Union[str, Any]:
   _A:						Any	    = 0
   _A:						str	    = len(a   ) - 1
   while left <= right:
      _A:						Any	    = (left + right) // 2
      if left == right:
         if sorted_list[middle] < item:
            _A:						Union[str, Any]	    = middle + 1
         break
      elif sorted_list[middle] < item:
         _A:						Optional[Any]	    = middle + 1
      else:
         _A:						str	    = middle - 1
   sorted_list.insert(a	,	a   )
   return sorted_list






def 						lowerCamelCase__							(      a	,	a   )   ->     int:
   _A:						List[Any]	    = []
   while left and right:
      if left[0][0] < right[0][0]:
         result.append(left.pop(0   )   )
      else:
         result.append(right.pop(0   )   )
   return result + left + right






def 						lowerCamelCase__							(      a   )   ->     List[Any]:
   _A:						Dict	    = len(a   )
   if length <= 1:
      return list_ad
   _A:						str	    = length // 2
   return merge(sortlist_ad(list_ad[:middle]   )	,	sortlist_ad(list_ad[middle:]   )   )






def 						lowerCamelCase__							(      a   )   ->     list[int]:

   if len(a   ) <= 1:
      return collection
   _A:						str	    = []
   _A:						Tuple	    = False
   for i in range(0	,	len(a   )	,	2   ):
      if i == len(a   ) - 1:
         _A:						Dict	    = True
      else:
         if collection[i] < collection[i + 1]:
            two_paired_list.append([collection[i], collection[i + 1]]   )
         else:
            two_paired_list.append([collection[i + 1], collection[i]]   )
   _A:						List[Any]	    = sortlist_ad(a   )
   _A:						Union[str, Any]	    = [i[0] for i in sorted_list_ad]
   result.append(sorted_list_ad[-1][1]   )
   if has_last_odd_item:
      _A:						List[Any]	    = collection[-1]
      _A:						Optional[Any]	    = binary_search_insertion(a	,	a   )
   _A:						Optional[int]	    = False
   for i in range(len(a   ) - 1   ):
      if result[i] == collection[-1] and has_last_odd_item:
         _A:						Tuple	    = True
      _A:						Optional[Any]	    = sorted_list_ad[i][1]
      # If last_odd_item is inserted before the item's index,
      # you should forward index one more.
      if is_last_odd_item_inserted_before_this_index:
         _A:						int	    = result[: i + 2] + binary_search_insertion(result[i + 2 :]	,	a   )
      else:
         _A:						Union[str, Any]	    = result[: i + 1] + binary_search_insertion(result[i + 1 :]	,	a   )

   return result


if __name__ == "__main__":
   UpperCAmelCase__	:  List[str]      =   input('Enter numbers separated by a comma:\n').strip()
   UpperCAmelCase__	:  List[Any]      =   [int(item) for item in user_input.split(',')]
   print(merge_insertion_sort(unsorted))



