
import timeit

import numpy as np

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



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					def wrapper(*lowerCAmelCase__				,    **lowerCAmelCase__	):
										lowercase     :   Any					=		timeit.default_timer()
										lowercase     :   List[str]					=		func(*lowerCAmelCase__				,    **lowerCAmelCase__	)
										lowercase     :   Tuple					=		timeit.default_timer() - starttime
										return delta

					lowercase     :   Optional[int]					=		func.__name__

					return wrapper



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=100				,    lowerCAmelCase__=None	):
					'''simple docstring'''
					lowercase     :   Tuple					=		[]
					lowercase     :   Optional[Any]					=		seq_shapes or {}
					for i in range(lowerCAmelCase__	):
										lowercase     :   List[Any]					=		{}
										for col_id, (k, v) in enumerate(features.items()	):
															if isinstance(lowerCAmelCase__				,    _ArrayXD	):
																				lowercase     :   Union[str, Any]					=		np.random.rand(*v.shape	).astype(v.dtype	)
															elif isinstance(lowerCAmelCase__				,    datasets.Value	):
																				if v.dtype == "string":
																									lowercase     :   str					=		'''The small grey turtle was surprisingly fast when challenged.'''
																				else:
																									lowercase     :   int					=		np.random.randint(10				,    size=1	).astype(v.dtype	).item()
															elif isinstance(lowerCAmelCase__				,    datasets.Sequence	):
																				while isinstance(lowerCAmelCase__				,    datasets.Sequence	):
																									lowercase     :   List[Any]					=		v.feature
																				lowercase     :   List[Any]					=		seq_shapes[k]
																				lowercase     :   Any					=		np.random.rand(*lowerCAmelCase__	).astype(v.dtype	)
															lowercase     :   Any					=		data

										dummy_data.append((i, example)	)

					return dummy_data



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__=100				,    lowerCAmelCase__=None	):
					'''simple docstring'''
					lowercase     :   List[str]					=		generate_examples(lowerCAmelCase__				,    num_examples=lowerCAmelCase__				,    seq_shapes=lowerCAmelCase__	)

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

										lowercase			,		lowercase     :   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}.'	)

					lowercase     :   Dict					=		datasets.Dataset.from_file(filename=lowerCAmelCase__				,    info=datasets.DatasetInfo(features=lowerCAmelCase__	)	)

					return dataset






import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    "The `inpainting.py` script is outdated. Please use directly `from diffusers import"
    " StableDiffusionInpaintPipeline` instead."
)




