





"""simple docstring"""
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


__UpperCamelCase     :						int						       =  logging.get_logger(__name__)


if is_vision_available():
       import PIL







class       a							(   a__  ):
 snake_case__             =       ['''pixel_values''']



 def __init__(     self				,       _snake_case = True				,       _snake_case = None				,       _snake_case = PILImageResampling.BICUBIC				,       _snake_case = True				,       _snake_case = None				,       _snake_case = True				,       _snake_case = 1 / 2_55				,       _snake_case = True				,       _snake_case = None				,       _snake_case = None				,       _snake_case = True				,       **_snake_case				,       ):







  """simple docstring"""






  super().__init__(**_snake_case     )
  lowerCAmelCase    				= size if size is not None else {'shortest_edge': 2_24}
  lowerCAmelCase    				= get_size_dict(_snake_case				,       default_to_square=_snake_case     )
  lowerCAmelCase    				= crop_size if crop_size is not None else {'height': 2_24, 'width': 2_24}
  lowerCAmelCase    				= get_size_dict(_snake_case				,       default_to_square=_snake_case				,       param_name='crop_size'     )

  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    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case				,       _snake_case = PILImageResampling.BICUBIC				,       _snake_case = None				,       **_snake_case				,       ):







  """simple docstring"""






  lowerCAmelCase    				= get_size_dict(_snake_case				,       default_to_square=_snake_case     )
  if "shortest_edge" not in size:
   raise ValueError(F'The `size` parameter must contain the key `shortest_edge`. Got {size.keys()}'     )
  lowerCAmelCase    				= get_resize_output_image_size(_snake_case				,       size=size['shortest_edge']				,       default_to_square=_snake_case     )
  return resize(_snake_case				,       size=_snake_case				,       resample=_snake_case				,       data_format=_snake_case				,       **_snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case				,       _snake_case = None				,       **_snake_case				,       ):







  """simple docstring"""






  lowerCAmelCase    				= get_size_dict(_snake_case     )
  if "height" not in size or "width" not in size:
   raise ValueError(F'The `size` parameter must contain the keys (height, width). Got {size.keys()}'     )
  return center_crop(_snake_case				,       size=(size['height'], size['width'])				,       data_format=_snake_case				,       **_snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case				,       _snake_case = None				,       **_snake_case				,       ):







  """simple docstring"""






  return rescale(_snake_case				,       scale=_snake_case				,       data_format=_snake_case				,       **_snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case				,       _snake_case				,       _snake_case = None				,       **_snake_case				,       ):







  """simple docstring"""






  return normalize(_snake_case				,       mean=_snake_case				,       std=_snake_case				,       data_format=_snake_case				,       **_snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = None				,       _snake_case = ChannelDimension.FIRST				,       **_snake_case				,       ):







  """simple docstring"""






  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(_snake_case				,       param_name='size'				,       default_to_square=_snake_case     )
  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(_snake_case				,       param_name='crop_size'				,       default_to_square=_snake_case     )
  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(_snake_case     )

  if not valid_images(_snake_case     ):
   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(_snake_case     ) for image in images]

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

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

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

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

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

  lowerCAmelCase    				= [to_channel_dimension_format(_snake_case				,       _snake_case     ) for image in images]

  lowerCAmelCase    				= {'pixel_values': images}
  return BatchFeature(data=_snake_case				,       tensor_type=_snake_case     )












"""simple docstring"""
from __future__ import annotations

import requests

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str			):
 lowerCAmelCase    				= F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
 return requests.get(_UpperCAmelCase			).json()

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    int = 10			):
 lowerCAmelCase    				= 'https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty'
 lowerCAmelCase    				= requests.get(_UpperCAmelCase			).json()[:max_stories]
 return [get_hackernews_story(_UpperCAmelCase			) for story_id in story_ids]

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    int = 10			):
 lowerCAmelCase    				= hackernews_top_stories(_UpperCAmelCase			)
 return "\n".join('* [{title}]({url})'.format(**_UpperCAmelCase			) for story in stories			)


if __name__ == "__main__":
       print(hackernews_top_stories_as_markdown())





