


'''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     :  Optional[List[str]]											=    None
lowerCAmelCase     :  str											=    """<""" 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     :  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 						UpperCamelCase__       :



     """simple docstring"""






     __magic_name__           =     True
     __magic_name__           =     None
     # Automatically constructed
     __magic_name__           =     "PIL.Image.Image"
     __magic_name__           =     pa.struct({"bytes": pa.binary(), "path": pa.string()}						)
     __magic_name__           =     field(default="Image"     ,       init=SCREAMING_SNAKE_CASE_     ,       repr=SCREAMING_SNAKE_CASE_						)







     def __call__(			self ):

            '''simple docstring'''

            return self.pa_type







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

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

            if isinstance(snake_case__   ,						snake_case__ ):
                   _lowerCAmelCase     :				List[Any]       =							np.array(snake_case__ )

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

            '''simple docstring'''

            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:
                   _lowerCAmelCase     :				Union[str, Any]       =							{}

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







     def a						(			self ):

            '''simple docstring'''

            from .features import Value

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







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

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







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            @no_op_if_value_is_null
            def path_to_bytes(snake_case__ ):
                   with xopen(snake_case__   ,						'rb' ) as f:
                          _lowerCAmelCase     :				List[str]       =							f.read()
                   return bytes_

            _lowerCAmelCase     :				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()   ,						)
            _lowerCAmelCase     :				Optional[int]       =							pa.array(
                [os.path.basename(snake_case__ ) if path is not None else None for path in storage.field('path' ).to_pylist()]   ,						type=pa.string()   ,						)
            _lowerCAmelCase     :				int       =							pa.StructArray.from_arrays([bytes_array, path_array]   ,						['bytes', 'path']   ,						mask=bytes_array.is_null() )
            return array_cast(snake_case__   ,						self.pa_type )






def       lowercase					():







       """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()
              _lowerCAmelCase     :				List[str]       =							list(set(PIL.Image.OPEN.keys()       ) & set(PIL.Image.SAVE.keys()       )       )
       return _IMAGE_COMPRESSION_FORMATS






def       lowercase					(_A       ):







       """simple docstring"""







       _lowerCAmelCase     :				Union[str, Any]       =							BytesIO()
       if image.format in list_image_compression_formats():
              _lowerCAmelCase     :				Dict       =							image.format
       else:
              _lowerCAmelCase     :				Optional[Any]       =							'PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
       image.save(_A ,    format=_A       )
       return buffer.getvalue()






def       lowercase					(_A       ):







       """simple docstring"""







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






def       lowercase					(_A       ):







       """simple docstring"""







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

       _lowerCAmelCase     :				List[Any]       =							array.dtype
       _lowerCAmelCase     :				Tuple       =							dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
       _lowerCAmelCase     :				Tuple       =							dtype.kind
       _lowerCAmelCase     :				List[str]       =							dtype.itemsize

       _lowerCAmelCase     :				Any       =							None

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






def       lowercase					(_A       ):







       """simple docstring"""







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

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





'''simple docstring'''







import argparse
from collections import defaultdict

import yaml


lowerCAmelCase     :  Dict											=    """docs/source/en/_toctree.yml"""






def       lowercase					(_A       ):







       """simple docstring"""







       _lowerCAmelCase     :				Optional[int]       =							defaultdict(_A       )
       _lowerCAmelCase     :				Tuple       =							[]
       _lowerCAmelCase     :				Dict       =							[]
       for doc in doc_list:
              if "local" in doc:
                     counts[doc["local"]] += 1

              if doc["title"].lower() == "overview":
                     overview_doc.append({'local': doc['local'], 'title': doc['title']}       )
              else:
                     new_doc_list.append(_A       )

       _lowerCAmelCase     :				str       =							new_doc_list
       _lowerCAmelCase     :				List[Any]       =							[key for key, value in counts.items() if value > 1]

       _lowerCAmelCase     :				List[str]       =							[]
       for duplicate_key in duplicates:
              _lowerCAmelCase     :				Any       =							list({doc['title'] for doc in doc_list if doc['local'] == duplicate_key}       )
              if len(_A       ) > 1:
                     raise ValueError(
                         f'{duplicate_key} is present several times in the documentation table of content at '
                         '`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '
                         'others.'       )
              # Only add this once
              new_doc.append({'local': duplicate_key, 'title': titles[0]}       )

       # Add none duplicate-keys
       new_doc.extend([doc for doc in doc_list if 'local' not in counts or counts[doc['local']] == 1]       )
       _lowerCAmelCase     :				Any       =							sorted(_A ,    key=lambda _A       : s["title"].lower()       )

       # "overview" gets special treatment and is always first
       if len(_A       ) > 1:
              raise ValueError('{doc_list} has two \'overview\' docs which is not allowed.'       )

       overview_doc.extend(_A       )

       # Sort
       return overview_doc






def       lowercase					(_A=False       ):







       """simple docstring"""







       with open(_A ,    encoding='utf-8'       ) as f:
              _lowerCAmelCase     :				Union[str, Any]       =							yaml.safe_load(f.read()       )

       # Get to the API doc
       _lowerCAmelCase     :				Tuple       =							0
       while content[api_idx]["title"] != "API":
              api_idx += 1
       _lowerCAmelCase     :				str       =							content[api_idx]['sections']

       # Then to the model doc
       _lowerCAmelCase     :				Dict       =							0
       while api_doc[scheduler_idx]["title"] != "Schedulers":
              scheduler_idx += 1

       _lowerCAmelCase     :				Optional[int]       =							api_doc[scheduler_idx]['sections']
       _lowerCAmelCase     :				Any       =							clean_doc_toc(_A       )

       _lowerCAmelCase     :				int       =							False
       if new_scheduler_doc != scheduler_doc:
              _lowerCAmelCase     :				str       =							True
              if overwrite:
                     _lowerCAmelCase     :				int       =							new_scheduler_doc

       if diff:
              if overwrite:
                     _lowerCAmelCase     :				Dict       =							api_doc
                     with open(_A ,    'w' ,    encoding='utf-8'       ) as f:
                            f.write(yaml.dump(_A ,    allow_unicode=_A       )       )
              else:
                     raise ValueError(
                         'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'       )






def       lowercase					(_A=False       ):







       """simple docstring"""







       with open(_A ,    encoding='utf-8'       ) as f:
              _lowerCAmelCase     :				Optional[Any]       =							yaml.safe_load(f.read()       )

       # Get to the API doc
       _lowerCAmelCase     :				Optional[Any]       =							0
       while content[api_idx]["title"] != "API":
              api_idx += 1
       _lowerCAmelCase     :				Union[str, Any]       =							content[api_idx]['sections']

       # Then to the model doc
       _lowerCAmelCase     :				Optional[int]       =							0
       while api_doc[pipeline_idx]["title"] != "Pipelines":
              pipeline_idx += 1

       _lowerCAmelCase     :				List[Any]       =							False
       _lowerCAmelCase     :				List[Any]       =							api_doc[pipeline_idx]['sections']
       _lowerCAmelCase     :				Union[str, Any]       =							[]

       # sort sub pipeline docs
       for pipeline_doc in pipeline_docs:
              if "section" in pipeline_doc:
                     _lowerCAmelCase     :				Tuple       =							pipeline_doc['section']
                     _lowerCAmelCase     :				Optional[int]       =							clean_doc_toc(_A       )
                     if overwrite:
                            _lowerCAmelCase     :				str       =							new_sub_pipeline_doc
              new_pipeline_docs.append(_A       )

       # sort overall pipeline doc
       _lowerCAmelCase     :				str       =							clean_doc_toc(_A       )

       if new_pipeline_docs != pipeline_docs:
              _lowerCAmelCase     :				Any       =							True
              if overwrite:
                     _lowerCAmelCase     :				Optional[int]       =							new_pipeline_docs

       if diff:
              if overwrite:
                     _lowerCAmelCase     :				str       =							api_doc
                     with open(_A ,    'w' ,    encoding='utf-8'       ) as f:
                            f.write(yaml.dump(_A ,    allow_unicode=_A       )       )
              else:
                     raise ValueError(
                         'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'       )


if __name__ == "__main__":
       lowerCAmelCase     :  Tuple											=    argparse.ArgumentParser()
       parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
       lowerCAmelCase     :  List[Any]											=    parser.parse_args()

       check_scheduler_doc(args.fix_and_overwrite)
       check_pipeline_doc(args.fix_and_overwrite)

