



'''simple docstring'''

from maths.prime_check import is_prime



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      int:
		if not isinstance(lowerCAmelCase_						,			lowerCAmelCase_  ):
				_a     :      List[str]        =							f"""Input value of [number={number}] must be an integer"""
				raise TypeError(lowerCAmelCase_  )
		if is_prime(lowerCAmelCase_  ) and is_prime(number + 2  ):
				return number + 2
		else:
				return -1


if __name__ == "__main__":
							import doctest

							doctest.testmod()









'''simple docstring'''

import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
							import PIL.Image

							from .features import FeatureType


__lowerCAmelCase									=   None
__lowerCAmelCase									=   '''<''' if sys.byteorder == '''little''' else '''>'''
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
__lowerCAmelCase									=   [
    np.dtype('''|b1'''),
    np.dtype('''|u1'''),
    np.dtype('''<u2'''),
    np.dtype('''>u2'''),
    np.dtype('''<i2'''),
    np.dtype('''>i2'''),
    np.dtype('''<u4'''),
    np.dtype('''>u4'''),
    np.dtype('''<i4'''),
    np.dtype('''>i4'''),
    np.dtype('''<f4'''),
    np.dtype('''>f4'''),
    np.dtype('''<f8'''),
    np.dtype('''>f8'''),
]

@dataclass
class 	__magic_name__						:
							lowerCAmelCase       :    bool   				=					True
							lowerCAmelCase       :    Optional[str]   				=					None
							# Automatically constructed
							lowerCAmelCase       :    ClassVar[str]   				=					"PIL.Image.Image"
							lowerCAmelCase       :    ClassVar[Any]   				=					pa.struct({'bytes': pa.binary(), 'path': pa.string()}   )
							lowerCAmelCase       :    str   				=					field(default='Image'			,						init=_UpperCamelCase			,						repr=_UpperCamelCase   )







							def __call__(							self					:       Union[str, Any]		):
									return self.pa_type







							def 							__lowercase			(							self					:       Any	,_UpperCAmelCase					:       Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]		):
									if config.PIL_AVAILABLE:
											import PIL.Image
									else:
											raise ImportError('To support encoding images, please install \'Pillow\'.'		)

									if isinstance(_UpperCAmelCase	,_UpperCAmelCase		):
											_a     :      Optional[Any]        =							np.array(_UpperCAmelCase		)

									if isinstance(_UpperCAmelCase	,_UpperCAmelCase		):
											return {"path": value, "bytes": None}
									elif isinstance(_UpperCAmelCase	,_UpperCAmelCase		):
											return {"path": None, "bytes": value}
									elif isinstance(_UpperCAmelCase	,np.ndarray		):
											# convert the image array to PNG/TIFF bytes
											return encode_np_array(_UpperCAmelCase		)
									elif isinstance(_UpperCAmelCase	,PIL.Image.Image		):
											# convert the PIL image to bytes (default format is PNG/TIFF)
											return encode_pil_image(_UpperCAmelCase		)
									elif value.get('path'		) is not None and os.path.isfile(value['path']		):
											# we set "bytes": None to not duplicate the data if they're already available locally
											return {"bytes": None, "path": value.get('path'		)}
									elif value.get('bytes'		) is not None or value.get('path'		) is not None:
											# store the image bytes, and path is used to infer the image format using the file extension
											return {"bytes": value.get('bytes'		), "path": value.get('path'		)}
									else:
											raise ValueError(
											    F"""An image sample should have one of 'path' or 'bytes' but they are missing or None in {value}."""		)







							def 							__lowercase			(							self					:       Optional[Any]	,_UpperCAmelCase					:       dict	,_UpperCAmelCase					:       Optional[int]=None		):
									if not self.decode:
											raise RuntimeError('Decoding is disabled for this feature. Please use Image(decode=True) instead.'		)

									if config.PIL_AVAILABLE:
											import PIL.Image
									else:
											raise ImportError('To support decoding images, please install \'Pillow\'.'		)

									if token_per_repo_id is None:
											_a     :      Dict        =							{}

									_a       ,					_a     :      str        =							value['path'], value['bytes']
									if bytes_ is None:
											if path is None:
													raise ValueError(F"""An image should have one of 'path' or 'bytes' but both are None in {value}."""		)
											else:
													if is_local_path(_UpperCAmelCase		):
															_a     :      Any        =							PIL.Image.open(_UpperCAmelCase		)
													else:
															_a     :      List[Any]        =							path.split('::'		)[-1]
															try:
																	_a     :      str        =							string_to_dict(_UpperCAmelCase	,config.HUB_DATASETS_URL		)['repo_id']
																	_a     :      Optional[Any]        =							token_per_repo_id.get(_UpperCAmelCase		)
															except ValueError:
																	_a     :      int        =							None
															with xopen(_UpperCAmelCase	,'rb'	,use_auth_token=_UpperCAmelCase		) as f:
																	_a     :      Tuple        =							BytesIO(f.read()		)
															_a     :      Union[str, Any]        =							PIL.Image.open(bytes_		)
									else:
											_a     :      Optional[int]        =							PIL.Image.open(BytesIO(bytes_		)		)
									image.load()  # to avoid "Too many open files" errors
									return image







							def 							__lowercase			(							self					:       int		):
									from .features import Value

									return (
									    self
									    if self.decode
									    else {
									        "bytes": Value('binary'		),
									        "path": Value('string'		),
									    }
									)







							def 							__lowercase			(							self					:       str	,_UpperCAmelCase					:       Union[pa.StringArray, pa.StructArray, pa.ListArray]		):
									if pa.types.is_string(storage.type		):
											_a     :      Union[str, Any]        =							pa.array([None] * len(_UpperCAmelCase		)	,type=pa.binary()		)
											_a     :      Union[str, Any]        =							pa.StructArray.from_arrays([bytes_array, storage]	,['bytes', 'path']	,mask=storage.is_null()		)
									elif pa.types.is_binary(storage.type		):
											_a     :      List[str]        =							pa.array([None] * len(_UpperCAmelCase		)	,type=pa.string()		)
											_a     :      Any        =							pa.StructArray.from_arrays([storage, path_array]	,['bytes', 'path']	,mask=storage.is_null()		)
									elif pa.types.is_struct(storage.type		):
											if storage.type.get_field_index('bytes'		) >= 0:
													_a     :      Union[str, Any]        =							storage.field('bytes'		)
											else:
													_a     :      Tuple        =							pa.array([None] * len(_UpperCAmelCase		)	,type=pa.binary()		)
											if storage.type.get_field_index('path'		) >= 0:
													_a     :      Union[str, Any]        =							storage.field('path'		)
											else:
													_a     :      Dict        =							pa.array([None] * len(_UpperCAmelCase		)	,type=pa.string()		)
											_a     :      Optional[Any]        =							pa.StructArray.from_arrays([bytes_array, path_array]	,['bytes', 'path']	,mask=storage.is_null()		)
									elif pa.types.is_list(storage.type		):
											_a     :      List[str]        =							pa.array(
											    [encode_np_array(np.array(_UpperCAmelCase		)		)['bytes'] if arr is not None else None for arr in storage.to_pylist()]	,type=pa.binary()	,)
											_a     :      int        =							pa.array([None] * len(_UpperCAmelCase		)	,type=pa.string()		)
											_a     :      Optional[Any]        =							pa.StructArray.from_arrays(
											    [bytes_array, path_array]	,['bytes', 'path']	,mask=bytes_array.is_null()		)
									return array_cast(_UpperCAmelCase	,self.pa_type		)







							def 							__lowercase			(							self					:       Dict	,_UpperCAmelCase					:       pa.StructArray		):

									@no_op_if_value_is_null
									def path_to_bytes(_UpperCAmelCase					:       Tuple		):
											with xopen(_UpperCAmelCase	,'rb'		) as f:
													_a     :      int        =							f.read()
											return bytes_

									_a     :      Any        =							pa.array(
									    [
									        (path_to_bytes(x['path']		) if x['bytes'] is None else x['bytes']) if x is not None else None
									        for x in storage.to_pylist()
									    ]	,type=pa.binary()	,)
									_a     :      Optional[Any]        =							pa.array(
									    [os.path.basename(_UpperCAmelCase		) if path is not None else None for path in storage.field('path'		).to_pylist()]	,type=pa.string()	,)
									_a     :      Dict        =							pa.StructArray.from_arrays([bytes_array, path_array]	,['bytes', 'path']	,mask=bytes_array.is_null()		)
									return array_cast(_UpperCAmelCase	,self.pa_type		)



def      __lowerCamelCase     (      )			->      List[str]:
		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError('To support encoding images, please install \'Pillow\'.'  )

		global _IMAGE_COMPRESSION_FORMATS
		if _IMAGE_COMPRESSION_FORMATS is None:
				PIL.Image.init()
				_a     :      Dict        =							list(set(PIL.Image.OPEN.keys()  ) & set(PIL.Image.SAVE.keys()  )  )
		return _IMAGE_COMPRESSION_FORMATS



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      bytes:
		_a     :      Optional[int]        =							BytesIO()
		if image.format in list_image_compression_formats():
				_a     :      Optional[Any]        =							image.format
		else:
				_a     :      str        =							'PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
		image.save(lowerCAmelCase_						,			format=lowerCAmelCase_  )
		return buffer.getvalue()



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      dict:
		if hasattr(lowerCAmelCase_						,			'filename'  ) and image.filename != "":
				return {"path": image.filename, "bytes": None}
		else:
				return {"path": None, "bytes": image_to_bytes(lowerCAmelCase_  )}



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      dict:
		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError('To support encoding images, please install \'Pillow\'.'  )

		_a     :      List[Any]        =							array.dtype
		_a     :      Optional[int]        =							dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
		_a     :      Union[str, Any]        =							dtype.kind
		_a     :      Union[str, Any]        =							dtype.itemsize

		_a     :      List[Any]        =							None

		# Multi-channel array case (only np.dtype("|u1") is allowed)
		if array.shape[2:]:
				_a     :      Optional[int]        =							np.dtype('|u1'  )
				if dtype_kind not in ["u", "i"]:
						raise TypeError(
						    f"""Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays."""  )
				if dtype is not dest_dtype:
						warnings.warn(f"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"""  )
    # Exact match
		elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
				_a     :      Union[str, Any]        =							dtype
		else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
				while dtype_itemsize >= 1:
						_a     :      str        =							dtype_byteorder + dtype_kind + str(lowerCAmelCase_  )
						_a     :      List[Any]        =							np.dtype(lowerCAmelCase_  )
						if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
								warnings.warn(f"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"""  )
								break
						else:
								dtype_itemsize //= 2

		if dest_dtype is None:
				raise TypeError(
				    f"""Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}"""  )
		_a     :      Union[str, Any]        =							PIL.Image.fromarray(array.astype(lowerCAmelCase_  )  )
		return {"path": None, "bytes": image_to_bytes(lowerCAmelCase_  )}



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      List[dict]:
		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError('To support encoding images, please install \'Pillow\'.'  )

		if objs:
				_a       ,					_a     :      Optional[Any]        =							first_non_null_value(lowerCAmelCase_  )
				if isinstance(lowerCAmelCase_						,			lowerCAmelCase_  ):
						return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
				if isinstance(lowerCAmelCase_						,			np.ndarray  ):
						_a     :      List[str]        =							no_op_if_value_is_null(lowerCAmelCase_  )
						return [obj_to_image_dict_func(lowerCAmelCase_  ) for obj in objs]
				elif isinstance(lowerCAmelCase_						,			PIL.Image.Image  ):
						_a     :      List[str]        =							no_op_if_value_is_null(lowerCAmelCase_  )
						return [obj_to_image_dict_func(lowerCAmelCase_  ) for obj in objs]
				else:
						return objs
		else:
				return objs




