'''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		:				Optional[List[str]]	       =		None
_lowercase		:				Tuple	       =		"<" 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		:				List[Any]	       =		[
    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__		:
   UpperCamelCase__       = True
   UpperCamelCase__       = None
   # Automatically constructed
   UpperCamelCase__       = '''PIL.Image.Image'''
   UpperCamelCase__       = pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()})
   UpperCamelCase__       = field(default='''Image''',  init=_UpperCAmelCase,  repr=_UpperCAmelCase)







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







   def 			SCREAMING_SNAKE_CASE_  (			self       :						int       ,    lowercase_       :						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(lowercase_       ,    lowercase_					):
                 lowercase_      :    str       		= 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 			SCREAMING_SNAKE_CASE_  (			self       :						Any       ,    lowercase_       :						dict       ,    lowercase_       :						Any=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:
                 lowercase_      :    Any       		= {}

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







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]					):
          from .features import Value

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







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Any       ,    lowercase_       :						Union[pa.StringArray, pa.StructArray, pa.ListArray]					):
          if pa.types.is_string(storage.type					):
                 lowercase_      :    Any       		= pa.array([None] * len(lowercase_					)       ,    type=pa.binary()					)
                 lowercase_      :    Tuple       		= pa.StructArray.from_arrays([bytes_array, storage]       ,    ["""bytes""", """path"""]       ,    mask=storage.is_null()					)
          elif pa.types.is_binary(storage.type					):
                 lowercase_      :    Union[str, Any]       		= pa.array([None] * len(lowercase_					)       ,    type=pa.string()					)
                 lowercase_      :    List[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:
                        lowercase_      :    List[str]       		= storage.field("""bytes"""					)
                 else:
                        lowercase_      :    str       		= pa.array([None] * len(lowercase_					)       ,    type=pa.binary()					)
                 if storage.type.get_field_index("""path"""					) >= 0:
                        lowercase_      :    List[str]       		= storage.field("""path"""					)
                 else:
                        lowercase_      :    Tuple       		= pa.array([None] * len(lowercase_					)       ,    type=pa.string()					)
                 lowercase_      :    int       		= pa.StructArray.from_arrays([bytes_array, path_array]       ,    ["""bytes""", """path"""]       ,    mask=storage.is_null()					)
          elif pa.types.is_list(storage.type					):
                 lowercase_      :    List[Any]       		= 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()       ,    )
                 lowercase_      :    Dict       		= pa.array([None] * len(lowercase_					)       ,    type=pa.string()					)
                 lowercase_      :    Optional[Any]       		= pa.StructArray.from_arrays(
                     [bytes_array, path_array]       ,    ["""bytes""", """path"""]       ,    mask=bytes_array.is_null()					)
          return array_cast(lowercase_       ,    self.pa_type					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]       ,    lowercase_       :						pa.StructArray					):

          @no_op_if_value_is_null
          def path_to_bytes(lowercase_       :						Any					):
                 with xopen(lowercase_       ,    """rb"""					) as f:
                        lowercase_      :    Any       		= f.read()
                 return bytes_

          lowercase_      :    Dict       		= 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()       ,    )
          lowercase_      :    int       		= pa.array(
              [os.path.basename(lowercase_					) if path is not None else None for path in storage.field("""path"""					).to_pylist()]       ,    type=pa.string()       ,    )
          lowercase_      :    List[str]       		= pa.StructArray.from_arrays([bytes_array, path_array]       ,    ["""bytes""", """path"""]       ,    mask=bytes_array.is_null()					)
          return array_cast(lowercase_       ,    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()
              lowercase_      :    Union[str, Any]       		= list(set(PIL.Image.OPEN.keys()				) & set(PIL.Image.SAVE.keys()				)				)
       return _IMAGE_COMPRESSION_FORMATS




def 							lowerCamelCase			(   UpperCAmelCase__ :      "PIL.Image.Image"				)    ->   bytes:
       lowercase_      :    List[str]       		= BytesIO()
       if image.format in list_image_compression_formats():
              lowercase_      :    int       		= image.format
       else:
              lowercase_      :    str       		= """PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
       image.save(UpperCAmelCase__   ,   format=UpperCAmelCase__				)
       return buffer.getvalue()




def 							lowerCamelCase			(   UpperCAmelCase__ :      "PIL.Image.Image"				)    ->   dict:
       if hasattr(UpperCAmelCase__   ,   """filename"""				) and image.filename != "":
              return {"path": image.filename, "bytes": None}
       else:
              return {"path": None, "bytes": image_to_bytes(UpperCAmelCase__				)}




def 							lowerCamelCase			(   UpperCAmelCase__ :      np.ndarray				)    ->   dict:
       if config.PIL_AVAILABLE:
              import PIL.Image
       else:
              raise ImportError("""To support encoding images, please install 'Pillow'."""				)

       lowercase_      :    Dict       		= array.dtype
       lowercase_      :    Dict       		= dtype.byteorder if dtype.byteorder != """=""" else _NATIVE_BYTEORDER
       lowercase_      :    Any       		= dtype.kind
       lowercase_      :    Tuple       		= dtype.itemsize

       lowercase_      :    Any       		= None

       # Multi-channel array case (only np.dtype("|u1") is allowed)
       if array.shape[2:]:
              lowercase_      :    Dict       		= 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:
              lowercase_      :    List[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:
                     lowercase_      :    int       		= dtype_byteorder + dtype_kind + str(UpperCAmelCase__				)
                     lowercase_      :    Union[str, Any]       		= np.dtype(UpperCAmelCase__				)
                     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}'''				)
       lowercase_      :    Optional[Any]       		= PIL.Image.fromarray(array.astype(UpperCAmelCase__				)				)
       return {"path": None, "bytes": image_to_bytes(UpperCAmelCase__				)}




def 							lowerCamelCase			(   UpperCAmelCase__ :      Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]				)    ->   List[dict]:
       if config.PIL_AVAILABLE:
              import PIL.Image
       else:
              raise ImportError("""To support encoding images, please install 'Pillow'."""				)

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






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_lowercase		:				Optional[Any]	       =		{
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase		:				Any	       =		[
						    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SwiftFormerForImageClassification",
						    "SwiftFormerModel",
						    "SwiftFormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_swiftformer import (
						    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SwiftFormerConfig,
						    SwiftFormerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_swiftformer import (
												    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SwiftFormerForImageClassification,
												    SwiftFormerModel,
												    SwiftFormerPreTrainedModel,
												)

else:
						import sys

						_lowercase		:				Optional[int]	       =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





