


'''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


lowercase__				     =		None
lowercase__				     =		"<" 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
lowercase__				     =		[
    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 						__SCREAMING_SNAKE_CASE					:
     UpperCAmelCase 					=				True
     UpperCAmelCase 					=				None
     # Automatically constructed
     UpperCAmelCase 					=				"PIL.Image.Image"
     UpperCAmelCase 					=				pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()} )
     UpperCAmelCase 					=				field(default='''Image''' ,			init=lowercase__ ,			repr=lowercase__ )






     def __call__(			self		)       ->    Optional[int]:
           return self.pa_type






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

           if isinstance(__lowercase     ,							__lowercase		):
                 _a						=		np.array(__lowercase		)

           if isinstance(__lowercase     ,							__lowercase		):
                 return {"path": value, "bytes": None}
           elif isinstance(__lowercase     ,							__lowercase		):
                 return {"path": None, "bytes": value}
           elif isinstance(__lowercase     ,							np.ndarray		):
                 # convert the image array to PNG/TIFF bytes
                 return encode_np_array(__lowercase		)
           elif isinstance(__lowercase     ,							PIL.Image.Image		):
                 # convert the PIL image to bytes (default format is PNG/TIFF)
                 return encode_pil_image(__lowercase		)
           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  a_					(			self     ,							__UpperCamelCase     ,							__UpperCamelCase=None		)       ->    Dict:
           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						=		{}

           _a			,			_a						=		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(__lowercase		):
                             _a						=		PIL.Image.open(__lowercase		)
                       else:
                             _a						=		path.split("::"		)[-1]
                             try:
                                   _a						=		string_to_dict(__lowercase     ,							config.HUB_DATASETS_URL		)["repo_id"]
                                   _a						=		token_per_repo_id.get(__lowercase		)
                             except ValueError:
                                   _a						=		None
                             with xopen(__lowercase     ,							"rb"     ,							use_auth_token=__lowercase		) as f:
                                   _a						=		BytesIO(f.read()		)
                             _a						=		PIL.Image.open(bytes_		)
           else:
                 _a						=		PIL.Image.open(BytesIO(bytes_		)		)
           image.load()  # to avoid "Too many open files" errors
           return image






     def  a_					(			self		)       ->    Dict:
           from .features import Value

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






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Dict:
           if pa.types.is_string(storage.type		):
                 _a						=		pa.array([None] * len(__lowercase		)     ,							type=pa.binary()		)
                 _a						=		pa.StructArray.from_arrays([bytes_array, storage]     ,							["bytes", "path"]     ,							mask=storage.is_null()		)
           elif pa.types.is_binary(storage.type		):
                 _a						=		pa.array([None] * len(__lowercase		)     ,							type=pa.string()		)
                 _a						=		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						=		storage.field("bytes"		)
                 else:
                       _a						=		pa.array([None] * len(__lowercase		)     ,							type=pa.binary()		)
                 if storage.type.get_field_index("path"		) >= 0:
                       _a						=		storage.field("path"		)
                 else:
                       _a						=		pa.array([None] * len(__lowercase		)     ,							type=pa.string()		)
                 _a						=		pa.StructArray.from_arrays([bytes_array, path_array]     ,							["bytes", "path"]     ,							mask=storage.is_null()		)
           elif pa.types.is_list(storage.type		):
                 _a						=		pa.array(
                     [encode_np_array(np.array(__lowercase		)		)["bytes"] if arr is not None else None for arr in storage.to_pylist()]     ,							type=pa.binary()     ,							)
                 _a						=		pa.array([None] * len(__lowercase		)     ,							type=pa.string()		)
                 _a						=		pa.StructArray.from_arrays(
                     [bytes_array, path_array]     ,							["bytes", "path"]     ,							mask=bytes_array.is_null()		)
           return array_cast(__lowercase     ,							self.pa_type		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Optional[int]:

           @no_op_if_value_is_null
           def path_to_bytes(__UpperCamelCase		):
                 with xopen(__lowercase     ,							"rb"		) as f:
                       _a						=		f.read()
                 return bytes_

           _a						=		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						=		pa.array(
               [os.path.basename(__lowercase		) if path is not None else None for path in storage.field("path"		).to_pylist()]     ,							type=pa.string()     ,							)
           _a						=		pa.StructArray.from_arrays([bytes_array, path_array]     ,							["bytes", "path"]     ,							mask=bytes_array.is_null()		)
           return array_cast(__lowercase     ,							self.pa_type		)







def __UpperCamelCase   (			)      ->     List[str]:







      '''simple docstring'''






      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						=		list(set(PIL.Image.OPEN.keys()				) & set(PIL.Image.SAVE.keys()				)				)
      return _IMAGE_COMPRESSION_FORMATS






def __UpperCamelCase   (			__lowerCamelCase		: Any				)      ->     List[str]:







      '''simple docstring'''






      _a						=		BytesIO()
      if image.format in list_image_compression_formats():
            _a						=		image.format
      else:
            _a						=		"PNG" if image.mode in ["1", "L", "LA", "RGB", "RGBA"] else "TIFF"
      image.save(SCREAMING_SNAKE_CASE_      ,  format=SCREAMING_SNAKE_CASE_				)
      return buffer.getvalue()






def __UpperCamelCase   (			__lowerCamelCase		: Tuple				)      ->     Union[str, Any]:







      '''simple docstring'''






      if hasattr(SCREAMING_SNAKE_CASE_      ,  "filename"				) and image.filename != "":
            return {"path": image.filename, "bytes": None}
      else:
            return {"path": None, "bytes": image_to_bytes(SCREAMING_SNAKE_CASE_				)}






def __UpperCamelCase   (			__lowerCamelCase		: Dict				)      ->     str:







      '''simple docstring'''






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

      _a						=		array.dtype
      _a						=		dtype.byteorder if dtype.byteorder != "=" else _NATIVE_BYTEORDER
      _a						=		dtype.kind
      _a						=		dtype.itemsize

      _a						=		None

      # Multi-channel array case (only np.dtype("|u1") is allowed)
      if array.shape[2:]:
            _a						=		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						=		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						=		dtype_byteorder + dtype_kind + str(SCREAMING_SNAKE_CASE_				)
                  _a						=		np.dtype(SCREAMING_SNAKE_CASE_				)
                  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						=		PIL.Image.fromarray(array.astype(SCREAMING_SNAKE_CASE_				)				)
      return {"path": None, "bytes": image_to_bytes(SCREAMING_SNAKE_CASE_				)}






def __UpperCamelCase   (			__lowerCamelCase		: str				)      ->     Any:







      '''simple docstring'''






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

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





'''simple docstring'''

class 						__SCREAMING_SNAKE_CASE					:






     def __init__(			self     ,							__UpperCamelCase		)       ->    Optional[Any]:
          # we need a list not a string, so do something to change the type
          _a						=		arr.split(","		)






     def  a_					(			self		)       ->    List[Any]:
          _a						=		[int(self.array[0]		)] * len(self.array		)
          _a						=		[int(self.array[0]		)] * len(self.array		)
          for i in range(1     ,							len(self.array		)		):
               _a						=		max(
                   int(self.array[i]		) + sum_value[i - 1]     ,							int(self.array[i]		)		)
               _a						=		max(sum_value[i]     ,							rear[i - 1]		)
          return rear[len(self.array		) - 1]


if __name__ == "__main__":
   lowercase__				     =		input("please input some numbers:")
   lowercase__				     =		SubArray(whole_array)
   lowercase__				     =		array.solve_sub_array()
   print(("the results is:", re))

