




import posixpath
from pathlib import Path
from unittest.mock import patch

import pytest
from fsspec.implementations.local import AbstractFileSystem, LocalFileSystem, stringify_path
from fsspec.registry import _registry as _fsspec_registry






class       A      (		_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:						Union[str, Any]  ="mock"




     def __init__(     self	: List[str]						,	*A__	: Tuple						,	A__	: Any						,	**A__	: str      )					->							Any:
           super().__init__()
           lowerCamelCase__   	=					LocalFileSystem(*A__						,	**A__      )
           lowerCamelCase__   	=					Path(A__      ).resolve().as_posix() + '/'




     def 			__snake_case (     self	: str						,	A__	: Dict						,	*A__	: Tuple						,	**A__	: str      )					->							int:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.mkdir(A__						,	*A__						,	**A__      )




     def 			__snake_case (     self	: Union[str, Any]						,	A__	: Dict						,	*A__	: Optional[Any]						,	**A__	: Optional[int]      )					->							Union[str, Any]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.makedirs(A__						,	*A__						,	**A__      )




     def 			__snake_case (     self	: Any						,	A__	: str      )					->							Dict:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.rmdir(A__      )




     def 			__snake_case (     self	: Tuple						,	A__	: List[Any]						,	A__	: Union[str, Any]=True						,	*A__	: Optional[int]						,	**A__	: Optional[int]      )					->							Union[str, Any]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           lowerCamelCase__   	=					self._fs.ls(A__						,	detail=A__						,	*A__						,	**A__      )
           if detail:
                 return [{**info, "name": info["name"][len(self.local_root_dir      ) :]} for info in out]
           else:
                 return [name[len(self.local_root_dir      ) :] for name in out]




     def 			__snake_case (     self	: List[str]						,	A__	: Union[str, Any]						,	*A__	: Optional[int]						,	**A__	: Any      )					->							Union[str, Any]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           lowerCamelCase__   	=					dict(self._fs.info(A__						,	*A__						,	**A__      )      )
           lowerCamelCase__   	=					out['name'][len(self.local_root_dir      ) :]
           return out




     def 			__snake_case (     self	: int						,	A__	: List[str]						,	A__	: List[Any]						,	*A__	: Any						,	**A__	: str      )					->							List[str]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.cp_file(A__						,	A__						,	*A__						,	**A__      )




     def 			__snake_case (     self	: int						,	A__	: Union[str, Any]						,	*A__	: List[str]						,	**A__	: Optional[int]      )					->							List[Any]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.rm_file(A__						,	*A__						,	**A__      )




     def 			__snake_case (     self	: str						,	A__	: Tuple						,	*A__	: Tuple						,	**A__	: str      )					->							Optional[Any]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.rm(A__						,	*A__						,	**A__      )




     def 			__snake_case (     self	: Tuple						,	A__	: List[str]						,	*A__	: Union[str, Any]						,	**A__	: Optional[int]      )					->							List[Any]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs._open(A__						,	*A__						,	**A__      )




     def 			__snake_case (     self	: List[str]						,	A__	: Optional[Any]      )					->							Optional[int]:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.created(A__      )




     def 			__snake_case (     self	: List[Any]						,	A__	: List[str]      )					->							Dict:
           lowerCamelCase__   	=					posixpath.join(self.local_root_dir						,	self._strip_protocol(A__      )      )
           return self._fs.modified(A__      )




     @classmethod
     def 			__snake_case (     cls	: Optional[Any]						,	A__	: str      )					->							Optional[int]:
           lowerCamelCase__   	=					stringify_path(A__      )
           if path.startswith('mock://'      ):
                 lowerCamelCase__   	=					path[7:]
           return path






class       A      (		_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:						Optional[int]  ="tmp"
     _snake_case:						Any  =None




     def __init__(     self	: Any						,	*A__	: str						,	**A__	: Union[str, Any]      )					->							Optional[int]:
           assert self.tmp_dir is not None, "TmpDirFileSystem.tmp_dir is not set"
           super().__init__(*A__						,	**A__						,	local_root_dir=self.tmp_dir						,	auto_mkdir=A__      )




     @classmethod
     def 			__snake_case (     cls	: Optional[Any]						,	A__	: List[Any]      )					->							Any:
           lowerCamelCase__   	=					stringify_path(A__      )
           if path.startswith('tmp://'      ):
                 lowerCamelCase__   	=					path[6:]
           return path

@pytest.fixture
def       lowerCAmelCase_      (	)       ->      Any:


      '''simple docstring'''




      lowerCamelCase__   	=					MockFileSystem
      lowerCamelCase__   	=					TmpDirFileSystem
      yield
      del _fsspec_registry["mock"]
      del _fsspec_registry["tmp"]

@pytest.fixture
def       lowerCAmelCase_      (	lowerCamelCase:							Union[str, Any]  ,					lowerCamelCase:							str    )       ->      List[Any]:


      '''simple docstring'''




      lowerCamelCase__   	=					tmp_path_factory.mktemp('mockfs'    )
      return MockFileSystem(local_root_dir=lowerCamelCase  ,					auto_mkdir=lowerCamelCase    )


@pytest.fixture
def       lowerCAmelCase_      (	lowerCamelCase:							List[str]  ,					lowerCamelCase:							Optional[int]    )       ->      Optional[Any]:


      '''simple docstring'''




      lowerCamelCase__   	=					tmp_path_factory.mktemp('tmpfs'    )
      with patch.object(lowerCamelCase  ,					'tmp_dir'  ,					lowerCamelCase    ):
            yield TmpDirFileSystem()





from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    convert_to_rgb,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


__SCREAMING_SNAKE_CASE     : Dict      =logging.get_logger(__name__)


if is_vision_available():
      import PIL






class       A      (		_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:						Any  =["pixel_values"]




     def __init__(     self	: Union[str, Any]						,	A__	: bool = True						,	A__	: Dict[str, int] = None						,	A__	: PILImageResampling = PILImageResampling.BICUBIC						,	A__	: bool = True						,	A__	: Dict[str, int] = None						,	A__	: bool = True						,	A__	: Union[int, float] = 1 / 2_5_5						,	A__	: bool = True						,	A__	: Optional[Union[float, List[float]]] = None						,	A__	: Optional[Union[float, List[float]]] = None						,	A__	: bool = True						,	**A__	: Optional[int]						,	)					->							None:
           super().__init__(**A__      )
           lowerCamelCase__   	=					size if size is not None else {'shortest_edge': 2_2_4}
           lowerCamelCase__   	=					get_size_dict(A__						,	default_to_square=A__      )
           lowerCamelCase__   	=					crop_size if crop_size is not None else {'height': 2_2_4, 'width': 2_2_4}
           lowerCamelCase__   	=					get_size_dict(A__      )

           lowerCamelCase__   	=					do_resize
           lowerCamelCase__   	=					size
           lowerCamelCase__   	=					resample
           lowerCamelCase__   	=					do_center_crop
           lowerCamelCase__   	=					crop_size
           lowerCamelCase__   	=					do_rescale
           lowerCamelCase__   	=					rescale_factor
           lowerCamelCase__   	=					do_normalize
           lowerCamelCase__   	=					image_mean if image_mean is not None else OPENAI_CLIP_MEAN
           lowerCamelCase__   	=					image_std if image_std is not None else OPENAI_CLIP_STD
           lowerCamelCase__   	=					do_convert_rgb




     def 			__snake_case (     self	: Union[str, Any]						,	A__	: np.ndarray						,	A__	: Dict[str, int]						,	A__	: PILImageResampling = PILImageResampling.BICUBIC						,	A__	: Optional[Union[str, ChannelDimension]] = None						,	**A__	: Optional[int]						,	)					->							np.ndarray:
           lowerCamelCase__   	=					get_size_dict(A__						,	default_to_square=A__      )
           lowerCamelCase__   	=					get_resize_output_image_size(
               A__						,	size=(size['height'], size['width'])						,	default_to_square=A__      )
           return resize(A__						,	size=A__						,	resample=A__						,	data_format=A__						,	**A__      )




     def 			__snake_case (     self	: int						,	A__	: np.ndarray						,	A__	: Dict[str, int]						,	A__	: Optional[Union[str, ChannelDimension]] = None						,	**A__	: List[Any]						,	)					->							np.ndarray:
           lowerCamelCase__   	=					get_size_dict(A__      )
           return center_crop(A__						,	size=(size['height'], size['width'])						,	data_format=A__						,	**A__      )




     def 			__snake_case (     self	: Dict						,	A__	: np.ndarray						,	A__	: Union[int, float]						,	A__	: Optional[Union[str, ChannelDimension]] = None						,	**A__	: List[Any]						,	)					->							Tuple:
           return rescale(A__						,	scale=A__						,	data_format=A__						,	**A__      )




     def 			__snake_case (     self	: int						,	A__	: np.ndarray						,	A__	: Union[float, List[float]]						,	A__	: Union[float, List[float]]						,	A__	: Optional[Union[str, ChannelDimension]] = None						,	**A__	: Tuple						,	)					->							np.ndarray:
           return normalize(A__						,	mean=A__						,	std=A__						,	data_format=A__						,	**A__      )




     def 			__snake_case (     self	: Tuple						,	A__	: ImageInput						,	A__	: bool = None						,	A__	: Dict[str, int] = None						,	A__	: PILImageResampling = None						,	A__	: bool = None						,	A__	: int = None						,	A__	: bool = None						,	A__	: float = None						,	A__	: bool = None						,	A__	: Optional[Union[float, List[float]]] = None						,	A__	: Optional[Union[float, List[float]]] = None						,	A__	: bool = None						,	A__	: Optional[Union[str, TensorType]] = None						,	A__	: Optional[ChannelDimension] = ChannelDimension.FIRST						,	**A__	: List[str]						,	)					->							PIL.Image.Image:
           lowerCamelCase__   	=					do_resize if do_resize is not None else self.do_resize
           lowerCamelCase__   	=					size if size is not None else self.size
           lowerCamelCase__   	=					get_size_dict(A__						,	default_to_square=A__      )
           lowerCamelCase__   	=					resample if resample is not None else self.resample
           lowerCamelCase__   	=					do_center_crop if do_center_crop is not None else self.do_center_crop
           lowerCamelCase__   	=					crop_size if crop_size is not None else self.crop_size
           lowerCamelCase__   	=					get_size_dict(A__      )
           lowerCamelCase__   	=					do_rescale if do_rescale is not None else self.do_rescale
           lowerCamelCase__   	=					rescale_factor if rescale_factor is not None else self.rescale_factor
           lowerCamelCase__   	=					do_normalize if do_normalize is not None else self.do_normalize
           lowerCamelCase__   	=					image_mean if image_mean is not None else self.image_mean
           lowerCamelCase__   	=					image_std if image_std is not None else self.image_std
           lowerCamelCase__   	=					do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

           lowerCamelCase__   	=					make_list_of_images(A__      )

           if not valid_images(A__      ):
                 raise ValueError(
                     'Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '
                     'torch.Tensor, tf.Tensor or jax.ndarray.'      )

           if do_resize and size is None:
                 raise ValueError('Size must be specified if do_resize is True.'      )

           if do_center_crop and crop_size is None:
                 raise ValueError('Crop size must be specified if do_center_crop is True.'      )

           if do_rescale and rescale_factor is None:
                 raise ValueError('Rescale factor must be specified if do_rescale is True.'      )

           if do_normalize and (image_mean is None or image_std is None):
                 raise ValueError('Image mean and std must be specified if do_normalize is True.'      )

           # PIL RGBA images are converted to RGB
           if do_convert_rgb:
                 lowerCamelCase__   	=					[convert_to_rgb(A__      ) for image in images]

           # All transformations expect numpy arrays.
           lowerCamelCase__   	=					[to_numpy_array(A__      ) for image in images]

           if do_resize:
                 lowerCamelCase__   	=					[self.resize(image=A__						,	size=A__						,	resample=A__      ) for image in images]

           if do_center_crop:
                 lowerCamelCase__   	=					[self.center_crop(image=A__						,	size=A__      ) for image in images]

           if do_rescale:
                 lowerCamelCase__   	=					[self.rescale(image=A__						,	scale=A__      ) for image in images]

           if do_normalize:
                 lowerCamelCase__   	=					[self.normalize(image=A__						,	mean=A__						,	std=A__      ) for image in images]

           lowerCamelCase__   	=					[to_channel_dimension_format(A__						,	A__      ) for image in images]

           lowerCamelCase__   	=					{'pixel_values': images}
           return BatchFeature(data=A__						,	tensor_type=A__      )