'''simple docstring'''





import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD




def       lowerCAmelCase_     (		lowercase:							Dict		)    ->				Dict:







 '''simple docstring'''
 def wrapper(*lowercase:							int  ,					**lowercase:							List[Any]		):
  _UpperCamelCase:     Any							= timeit.default_timer()
  _UpperCamelCase:     Union[str, Any]							= func(*lowercase  ,					**lowercase		)
  _UpperCamelCase:     Optional[Any]							= timeit.default_timer() - starttime
  return delta

 _UpperCamelCase:     str							= func.__name__

 return wrapper




def       lowerCAmelCase_     (		lowercase:							dict  ,					lowercase:							Dict=100  ,					lowercase:							Optional[Any]=None		)    ->				Optional[Any]:







 '''simple docstring'''
 _UpperCamelCase:     str							= []
 _UpperCamelCase:     str							= seq_shapes or {}
 for i in range(lowercase		):
  _UpperCamelCase:     int							= {}
  for col_id, (k, v) in enumerate(features.items()		):
   if isinstance(lowercase  ,					_ArrayXD		):
    _UpperCamelCase:     Optional[int]							= np.random.rand(*v.shape		).astype(v.dtype		)
   elif isinstance(lowercase  ,					datasets.Value		):
    if v.dtype == "string":
     _UpperCamelCase:     str							= '''The small grey turtle was surprisingly fast when challenged.'''
    else:
     _UpperCamelCase:     str							= np.random.randint(10  ,					size=1		).astype(v.dtype		).item()
   elif isinstance(lowercase  ,					datasets.Sequence		):
    while isinstance(lowercase  ,					datasets.Sequence		):
     _UpperCamelCase:     str							= v.feature
    _UpperCamelCase:     Union[str, Any]							= seq_shapes[k]
    _UpperCamelCase:     Tuple							= np.random.rand(*lowercase		).astype(v.dtype		)
   _UpperCamelCase:     Optional[Any]							= data

  dummy_data.append((i, example)		)

 return dummy_data





def       lowerCAmelCase_     (		lowercase:							Tuple  ,					lowercase:							Any  ,					lowercase:							int=100  ,					lowercase:							Any=None		)    ->				Optional[int]:







 '''simple docstring'''
 _UpperCamelCase:     Any							= generate_examples(lowercase  ,					num_examples=lowercase  ,					seq_shapes=lowercase		)

 with ArrowWriter(features=lowercase  ,					path=lowercase		) as writer:
  for key, record in dummy_data:
   _UpperCamelCase:     int							= features.encode_example(lowercase		)
   writer.write(lowercase		)

  _UpperCamelCase:     str							= writer.finalize()

 if not num_final_examples == num_examples:
  raise ValueError(
      F"""Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."""		)

 _UpperCamelCase:     Optional[Any]							= datasets.Dataset.from_file(filename=lowercase  ,					info=datasets.DatasetInfo(features=lowercase		)		)

 return dataset
import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict




@pytest.mark.parametrize(
    '''split_dict'''  ,					[
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train'''  ,					num_bytes=1_337  ,					num_examples=42  ,					dataset_name='''my_dataset'''		)}		),
        SplitDict({'''train''': SplitInfo(name='''train'''  ,					num_bytes=1_337  ,					num_examples=42		)}		),
        SplitDict({'''train''': SplitInfo()}		),
    ]  ,					)
def       lowerCAmelCase_     (		lowercase:							SplitDict		)    ->				List[str]:







 '''simple docstring'''
 _UpperCamelCase:     List[str]							= split_dict._to_yaml_list()
 assert len(lowercase		) == len(lowercase		)
 _UpperCamelCase:     Tuple							= SplitDict._from_yaml_list(lowercase		)
 for split_name, split_info in split_dict.items():
  # dataset_name field is deprecated, and is therefore not part of the YAML dump
  _UpperCamelCase:     Optional[Any]							= None
  # the split name of split_dict takes over the name of the split info object
  _UpperCamelCase:     Any							= split_name
 assert split_dict == reloaded





@pytest.mark.parametrize(
    '''split_info'''  ,					[SplitInfo(), SplitInfo(dataset_name=lowercase		), SplitInfo(dataset_name='''my_dataset'''		)]		)
def       lowerCAmelCase_     (		lowercase:							str		)    ->				Tuple:







 '''simple docstring'''
 # For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
 # field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
 _UpperCamelCase:     Optional[Any]							= asdict(SplitDict({'''train''': split_info}		)		)
 assert "dataset_name" in split_dict_asdict["train"]
 assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name