

import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor


class    SCREAMING_SNAKE_CASE__      (unittest.TestCase  ):





    @property
    def    snake_case_       (   self):
         lowercase__					:     int   = 1
         lowercase__					:     Dict   = 3
         lowercase__					:     int   = 8
         lowercase__					:     int   = 8

         lowercase__					:     List[str]   = torch.rand((batch_size, num_channels, height, width))

         return sample





    def    snake_case_       (   self		,     a):







         if isinstance(image[0]		,     PIL.Image.Image):
              return np.stack([np.array(a) for i in image]		,     axis=0)
         elif isinstance(a		,     torch.Tensor):
              return image.cpu().numpy().transpose(0		,     2		,     3		,     1)
         return image





    def    snake_case_       (   self):
         lowercase__					:     Optional[int]   = VaeImageProcessor(do_resize=a		,     do_normalize=a)

         lowercase__					:     Any   = self.dummy_sample
         lowercase__					:     Optional[Any]   = self.to_np(a)

         for output_type in ["pt", "np", "pil"]:
              lowercase__					:     Optional[Any]   = image_processor.postprocess(
                  image_processor.preprocess(a)		,     output_type=a		,     )
              lowercase__					:     Optional[Any]   = self.to_np(a)
              lowercase__					:     Any   = (input_np * 255).round() if output_type == "pil" else input_np
              assert (
                  np.abs(in_np - out_np).max() < 1e-6
              ), f"""decoded output does not match input for output_type {output_type}"""





    def    snake_case_       (   self):
         lowercase__					:     Dict   = VaeImageProcessor(do_resize=a		,     do_normalize=a)
         lowercase__					:     Tuple   = self.dummy_sample.cpu().numpy().transpose(0		,     2		,     3		,     1)

         for output_type in ["pt", "np", "pil"]:
              lowercase__					:     Dict   = image_processor.postprocess(image_processor.preprocess(a)		,     output_type=a)

              lowercase__					:     Union[str, Any]   = self.to_np(a)
              lowercase__					:     Tuple   = (input_np * 255).round() if output_type == "pil" else input_np
              assert (
                  np.abs(in_np - out_np).max() < 1e-6
              ), f"""decoded output does not match input for output_type {output_type}"""





    def    snake_case_       (   self):
         lowercase__					:     Optional[Any]   = VaeImageProcessor(do_resize=a		,     do_normalize=a)

         lowercase__					:     str   = self.dummy_sample.cpu().numpy().transpose(0		,     2		,     3		,     1)
         lowercase__					:     int   = image_processor.numpy_to_pil(a)

         for output_type in ["pt", "np", "pil"]:
              lowercase__					:     Dict   = image_processor.postprocess(image_processor.preprocess(a)		,     output_type=a)
              for i, o in zip(a		,     a):
                   lowercase__					:     Dict   = np.array(a)
                   lowercase__					:     Tuple   = self.to_np(a) if output_type == "pil" else (self.to_np(a) * 255).round()
                   assert (
                       np.abs(in_np - out_np).max() < 1e-6
                   ), f"""decoded output does not match input for output_type {output_type}"""





    def    snake_case_       (   self):
         lowercase__					:     Tuple   = VaeImageProcessor(do_resize=a		,     do_normalize=a)

         lowercase__					:     List[str]   = self.dummy_sample
         lowercase__					:     Optional[int]   = input_pt_ad.squeeze(0)

         lowercase__					:     Any   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )
         lowercase__					:     Union[str, Any]   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )

         lowercase__					:     Union[str, Any]   = self.to_np(self.dummy_sample)
         lowercase__					:     Tuple   = input_np_ad.squeeze(0)

         lowercase__					:     str   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )
         lowercase__					:     Union[str, Any]   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )

         assert np.abs(out_pt_ad - out_pt_ad).max() < 1e-6
         assert np.abs(out_np_ad - out_np_ad).max() < 1e-6





    def    snake_case_       (   self):
         lowercase__					:     Optional[Any]   = VaeImageProcessor(do_resize=a		,     do_normalize=a)

         lowercase__					:     Union[str, Any]   = self.dummy_sample
         lowercase__					:     List[str]   = list(a)

         lowercase__					:     str   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )

         lowercase__					:     Any   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )

         lowercase__					:     Dict   = self.to_np(self.dummy_sample)
         list(a)

         lowercase__					:     str   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )

         lowercase__					:     Union[str, Any]   = image_processor.postprocess(
             image_processor.preprocess(a)		,     output_type='np'		,     )

         assert np.abs(out_pt_ad - out_pt_list).max() < 1e-6
         assert np.abs(out_np_ad - out_np_list).max() < 1e-6




from __future__ import annotations


class    SCREAMING_SNAKE_CASE__      :





    def __init__(   self		,     a = 0):
         lowercase__					:     int   = value
         lowercase__					:     Node | None   = None
         lowercase__					:     Node | None   = None



def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Node | None			,  SCREAMING_SNAKE_CASE_	:					Node | None    ):



     '''simple docstring'''





     if treea is None:
          return treea
     if treea is None:
          return treea

     lowercase__					:     Optional[Any]   = treea.value + treea.value
     lowercase__					:     Union[str, Any]   = merge_two_binary_trees(treea.left			,  treea.left    )
     lowercase__					:     Optional[Any]   = merge_two_binary_trees(treea.right			,  treea.right    )
     return treea

def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Node | None    ):



     '''simple docstring'''





     if root:
          print(root.value    )
          print_preorder(root.left    )
          print_preorder(root.right    )


if __name__ == "__main__":
       snake_case_    						=				Node(1)
       snake_case_    						=				Node(2)
       snake_case_    						=				Node(3)
       snake_case_    						=				Node(4)

       snake_case_    						=				Node(2)
       snake_case_    						=				Node(4)
       snake_case_    						=				Node(6)
       snake_case_    						=				Node(9)
       snake_case_    						=				Node(5)

       print('''Tree1 is: ''')
       print_preorder(treea)
       print('''Tree2 is: ''')
       print_preorder(treea)
       snake_case_    						=				merge_two_binary_trees(treea, treea)
       print('''Merged Tree is: ''')
       print_preorder(merged_tree)

