




"""simple docstring"""




from typing import List

import PIL
import torch
from PIL import Image

from ...configuration_utils import ConfigMixin
from ...models.modeling_utils import ModelMixin
from ...utils import PIL_INTERPOLATION
class 							lowerCamelCase		( _UpperCAmelCase	,  _UpperCAmelCase				):







   def __init__(							self ):
       super().__init__()

       self.register_buffer("""watermark_image"""    ,      torch.zeros((62, 62, 4) ) )
       UpperCamelCase				:   str          =							None







   def       a_							(							self    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_=None ):
       # copied from https://github.com/deep-floyd/IF/blob/b77482e36ca2031cb94dbca1001fc1e6400bf4ab/deepfloyd_if/modules/base.py#L287

       UpperCamelCase				:   List[str]          =							images[0].height
       UpperCamelCase				:   Optional[Any]          =							images[0].width

       UpperCamelCase				:   Union[str, Any]          =							sample_size or h

       UpperCamelCase				:   Tuple          =							min(h / sample_size    ,      w / sample_size )
       UpperCamelCase       ,							UpperCamelCase				:   Union[str, Any]          =							(int(h / coef ), int(w / coef )) if coef < 1 else (h, w)

       UpperCamelCase       ,							UpperCamelCase				:   List[Any]          =							1024**2, img_w * img_h
       UpperCamelCase				:   List[Any]          =							(Sa / Sa) ** 0.5
       UpperCamelCase       ,							UpperCamelCase       ,							UpperCamelCase				:   Tuple          =							int(K * 62 ), img_w - int(14 * K ), img_h - int(14 * K )

       if self.watermark_image_as_pil is None:
           UpperCamelCase				:   Tuple          =							self.watermark_image.to(torch.uinta ).cpu().numpy()
           UpperCamelCase				:   Optional[Any]          =							Image.fromarray(SCREAMING_SNAKE_CASE_    ,      mode="""RGBA""" )
           UpperCamelCase				:   int          =							watermark_image

       UpperCamelCase				:   Any          =							self.watermark_image_as_pil.resize(
           (wm_size, wm_size)    ,      PIL_INTERPOLATION["""bicubic"""]    ,      reducing_gap=SCREAMING_SNAKE_CASE_ )

       for pil_img in images:
           pil_img.paste(SCREAMING_SNAKE_CASE_    ,      box=(wm_x - wm_size, wm_y - wm_size, wm_x, wm_y)    ,      mask=wm_img.split()[-1] )

       return images










"""simple docstring"""




class 							lowerCamelCase		:







   def __init__(							self    ,      SCREAMING_SNAKE_CASE_=None ):
       UpperCamelCase				:   Optional[Any]          =							data
       UpperCamelCase				:   str          =							None







   def __repr__(							self ):
       UpperCamelCase				:   str          =							""""""
       UpperCamelCase				:   Any          =							self
       while temp:
           string_rep += f'<{temp.data}> ---> '
           UpperCamelCase				:   Optional[int]          =							temp.next
       string_rep += "<END>"
       return string_rep







def 					A_			(		snake_case_     :       Tuple    ):







    '''simple docstring'''

    # if elements_list is empty
    if not elements_list:
        raise Exception("""The Elements List is empty"""    )

    # Set first element as Head
    UpperCamelCase				:   List[Any]          =							Node(elements_list[0]    )
    UpperCamelCase				:   str          =							head
    # Loop through elements from position 1
    for data in elements_list[1:]:
        UpperCamelCase				:   Optional[int]          =							Node(snake_case_    )
        UpperCamelCase				:   Optional[Any]          =							current.next
    return head


__A :		List[Any]      							=    [1, 3, 5, 32, 44, 12, 43]
print(F'''List: {list_data}''')
print('''Creating Linked List from List.''')
__A :		int      							=    make_linked_list(list_data)
print('''Linked List:''')


print(linked_list)




