



import gc
import random
import unittest

import numpy as np
import torch
from PIL import Image

from diffusers import (
    DDIMScheduler,
    KandinskyVaaInpaintPipeline,
    KandinskyVaaPriorPipeline,
    UNetaDConditionModel,
    VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu

from ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference


enable_full_determinism()



class    UpperCAmelCase__(				lowerCamelCase  ,				unittest.TestCase						):

   '''simple docstring'''




   A     :	List[str]												=     KandinskyVaaInpaintPipeline
   A     :	Optional[int]												=     ["image_embeds", "negative_image_embeds", "image", "mask_image"]
   A     :	str												=     [
       "image_embeds",
       "negative_image_embeds",
       "image",
       "mask_image",
   ]
   A     :	Dict												=     [
       "generator",
       "height",
       "width",
       "latents",
       "guidance_scale",
       "num_inference_steps",
       "return_dict",
       "guidance_scale",
       "num_images_per_prompt",
       "output_type",
       "return_dict",
   ]
   A     :	List[Any]												=     False


   @property
   def       UpperCAmelCase		(    self	:      Dict)						->					List[Any]:




         """simple docstring"""

         return 32


   @property
   def       UpperCAmelCase		(    self	:      List[Any])						->					Dict:




         """simple docstring"""

         return 32


   @property
   def       UpperCAmelCase		(    self	:      int)						->					Any:




         """simple docstring"""

         return self.time_input_dim


   @property
   def       UpperCAmelCase		(    self	:      Tuple)						->					Any:




         """simple docstring"""

         return self.time_input_dim * 4


   @property
   def       UpperCAmelCase		(    self	:      Optional[Any])						->					Optional[Any]:




         """simple docstring"""

         return 1_00


   @property
   def       UpperCAmelCase		(    self	:      Union[str, Any])						->					Tuple:




         """simple docstring"""

         torch.manual_seed(0)

         lowercase__  =	{
             'in_channels': 9,
             # Out channels is double in channels because predicts mean and variance
             'out_channels': 8,
             'addition_embed_type': 'image',
             'down_block_types': ('ResnetDownsampleBlock2D', 'SimpleCrossAttnDownBlock2D'),
             'up_block_types': ('SimpleCrossAttnUpBlock2D', 'ResnetUpsampleBlock2D'),
             'mid_block_type': 'UNetMidBlock2DSimpleCrossAttn',
             'block_out_channels': (self.block_out_channels_a, self.block_out_channels_a * 2),
             'layers_per_block': 1,
             'encoder_hid_dim': self.text_embedder_hidden_size,
             'encoder_hid_dim_type': 'image_proj',
             'cross_attention_dim': self.cross_attention_dim,
             'attention_head_dim': 4,
             'resnet_time_scale_shift': 'scale_shift',
             'class_embed_type': None,
         }

         lowercase__  =	UNetaDConditionModel(**lowerCAmelCase)
         return model


   @property
   def       UpperCAmelCase		(    self	:      Dict)						->					Dict:




         """simple docstring"""

         return {
             "block_out_channels": [32, 64],
             "down_block_types": ["DownEncoderBlock2D", "AttnDownEncoderBlock2D"],
             "in_channels": 3,
             "latent_channels": 4,
             "layers_per_block": 1,
             "norm_num_groups": 8,
             "norm_type": "spatial",
             "num_vq_embeddings": 12,
             "out_channels": 3,
             "up_block_types": [
                 "AttnUpDecoderBlock2D",
                 "UpDecoderBlock2D",
             ],
             "vq_embed_dim": 4,
         }


   @property
   def       UpperCAmelCase		(    self	:      Optional[int])						->					List[Any]:




         """simple docstring"""

         torch.manual_seed(0)
         lowercase__  =	VQModel(**self.dummy_movq_kwargs)
         return model


   def       UpperCAmelCase		(    self	:      Dict)						->					int:




         """simple docstring"""

         lowercase__  =	self.dummy_unet
         lowercase__  =	self.dummy_movq

         lowercase__  =	DDIMScheduler(
             num_train_timesteps=10_00      ,					beta_schedule='linear'      ,					beta_start=0.0_00_85      ,					beta_end=0.0_12      ,					clip_sample=lowerCAmelCase      ,					set_alpha_to_one=lowerCAmelCase      ,					steps_offset=1      ,					prediction_type='epsilon'      ,					thresholding=lowerCAmelCase      ,					)

         lowercase__  =	{
             'unet': unet,
             'scheduler': scheduler,
             'movq': movq,
         }

         return components


   def       UpperCAmelCase		(    self	:      Union[str, Any]      ,					lowerCAmelCase	:      int      ,					lowerCAmelCase	:      List[str]=0)						->					Dict:




         """simple docstring"""

         lowercase__  =	floats_tensor((1, self.text_embedder_hidden_size)      ,					rng=random.Random(lowerCAmelCase)).to(lowerCAmelCase)
         lowercase__  =	floats_tensor((1, self.text_embedder_hidden_size)      ,					rng=random.Random(seed + 1)).to(
             lowerCAmelCase)
         # create init_image
         lowercase__  =	floats_tensor((1, 3, 64, 64)      ,					rng=random.Random(lowerCAmelCase)).to(lowerCAmelCase)
         lowercase__  =	image.cpu().permute(0      ,					2      ,					3      ,					1)[0]
         lowercase__  =	Image.fromarray(np.uinta(lowerCAmelCase)).convert('RGB').resize((2_56, 2_56))
         # create mask
         lowercase__  =	np.ones((64, 64)      ,					dtype=np.floataa)
         lowercase__  =	0

         if str(lowerCAmelCase).startswith('mps'):
               lowercase__  =	torch.manual_seed(lowerCAmelCase)
         else:
               lowercase__  =	torch.Generator(device=lowerCAmelCase).manual_seed(lowerCAmelCase)
         lowercase__  =	{
             'image': init_image,
             'mask_image': mask,
             'image_embeds': image_embeds,
             'negative_image_embeds': negative_image_embeds,
             'generator': generator,
             'height': 64,
             'width': 64,
             'num_inference_steps': 2,
             'guidance_scale': 4.0,
             'output_type': 'np',
         }
         return inputs


   def       UpperCAmelCase		(    self	:      List[str])						->					Any:




         """simple docstring"""

         lowercase__  =	'cpu'

         lowercase__  =	self.get_dummy_components()

         lowercase__  =	self.pipeline_class(**lowerCAmelCase)
         lowercase__  =	pipe.to(lowerCAmelCase)

         pipe.set_progress_bar_config(disable=lowerCAmelCase)

         lowercase__  =	pipe(**self.get_dummy_inputs(lowerCAmelCase))
         lowercase__  =	output.images

         lowercase__  =	pipe(
             **self.get_dummy_inputs(lowerCAmelCase)      ,					return_dict=lowerCAmelCase      ,					)[0]

         lowercase__  =	image[0, -3:, -3:, -1]
         lowercase__  =	image_from_tuple[0, -3:, -3:, -1]

         print(f'''image.shape {image.shape}''')

         assert image.shape == (1, 64, 64, 3)

         lowercase__  =	np.array(
             [0.50_77_59_03, 0.49_52_71_95, 0.48_82_45_43, 0.50_19_22_37, 0.48_64_49_06, 0.49_37_38_14, 0.4_78_05_98, 0.47_23_48_27, 0.48_32_78_48])

         assert (
             np.abs(image_slice.flatten() - expected_slice).max() < 1E-2
         ), f''' expected_slice {expected_slice}, but got {image_slice.flatten()}'''
         assert (
             np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1E-2
         ), f''' expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}'''



   def       UpperCAmelCase		(    self	:      List[str])						->					Optional[int]:




         """simple docstring"""

         super().test_inference_batch_single_identical(expected_max_diff=3E-3)



@slow
@require_torch_gpu
class    UpperCAmelCase__(				unittest.TestCase						):

   '''simple docstring'''




   def       UpperCAmelCase		(    self	:      Union[str, Any])						->					Any:




         """simple docstring"""

         super().tearDown()
         gc.collect()
         torch.cuda.empty_cache()



   def       UpperCAmelCase		(    self	:      Optional[Any])						->					str:




         """simple docstring"""

         lowercase__  =	load_numpy(
             'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
             '/kandinskyv22/kandinskyv22_inpaint_cat_with_hat_fp16.npy')

         lowercase__  =	load_image(
             'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main' '/kandinsky/cat.png')
         lowercase__  =	np.ones((7_68, 7_68)      ,					dtype=np.floataa)
         lowercase__  =	0

         lowercase__  =	'a hat'

         lowercase__  =	KandinskyVaaPriorPipeline.from_pretrained(
             'kandinsky-community/kandinsky-2-2-prior'      ,					torch_dtype=torch.floataa)
         pipe_prior.to(lowerCAmelCase)

         lowercase__  =	KandinskyVaaInpaintPipeline.from_pretrained(
             'kandinsky-community/kandinsky-2-2-decoder-inpaint'      ,					torch_dtype=torch.floataa)
         lowercase__  =	pipeline.to(lowerCAmelCase)
         pipeline.set_progress_bar_config(disable=lowerCAmelCase)

         lowercase__  =	torch.Generator(device='cpu').manual_seed(0)
         lowercase__,						lowercase__  =	pipe_prior(
             lowerCAmelCase      ,					generator=lowerCAmelCase      ,					num_inference_steps=5      ,					negative_prompt=''      ,					).to_tuple()

         lowercase__  =	pipeline(
             image=lowerCAmelCase      ,					mask_image=lowerCAmelCase      ,					image_embeds=lowerCAmelCase      ,					negative_image_embeds=lowerCAmelCase      ,					generator=lowerCAmelCase      ,					num_inference_steps=1_00      ,					height=7_68      ,					width=7_68      ,					output_type='np'      ,					)

         lowercase__  =	output.images[0]

         assert image.shape == (7_68, 7_68, 3)

         assert_mean_pixel_difference(lowerCAmelCase      ,					lowerCAmelCase)





from datasets.utils.patching import _PatchedModuleObj, patch_submodule

from . import _test_patching

def 	_lowerCAmelCase (    ):
      import os as original_os
      from os import path as original_path
      from os import rename as original_rename
      from os.path import dirname as original_dirname
      from os.path import join as original_join

      assert _test_patching.os is original_os
      assert _test_patching.path is original_path
      assert _test_patching.join is original_join

      assert _test_patching.renamed_os is original_os
      assert _test_patching.renamed_path is original_path
      assert _test_patching.renamed_join is original_join

      lowercase__  =	'__test_patch_submodule_mock__'
      with patch_submodule(_test_patching    ,	'os.path.join'    ,	A__						):
            # Every way to access os.path.join must be patched, and the rest must stay untouched

            # check os.path.join
            assert isinstance(_test_patching.os    ,	_PatchedModuleObj						)
            assert isinstance(_test_patching.os.path    ,	_PatchedModuleObj						)
            assert _test_patching.os.path.join is mock

            # check path.join
            assert isinstance(_test_patching.path    ,	_PatchedModuleObj						)
            assert _test_patching.path.join is mock

            # check join
            assert _test_patching.join is mock

            # check that the other attributes are untouched
            assert _test_patching.os.rename is original_rename
            assert _test_patching.path.dirname is original_dirname
            assert _test_patching.os.path.dirname is original_dirname

            # Even renamed modules or objects must be patched

            # check renamed_os.path.join
            assert isinstance(_test_patching.renamed_os    ,	_PatchedModuleObj						)
            assert isinstance(_test_patching.renamed_os.path    ,	_PatchedModuleObj						)
            assert _test_patching.renamed_os.path.join is mock

            # check renamed_path.join
            assert isinstance(_test_patching.renamed_path    ,	_PatchedModuleObj						)
            assert _test_patching.renamed_path.join is mock

            # check renamed_join
            assert _test_patching.renamed_join is mock

            # check that the other attributes are untouched
            assert _test_patching.renamed_os.rename is original_rename
            assert _test_patching.renamed_path.dirname is original_dirname
            assert _test_patching.renamed_os.path.dirname is original_dirname

      # check that everthing is back to normal when the patch is over

      assert _test_patching.os is original_os
      assert _test_patching.path is original_path
      assert _test_patching.join is original_join

      assert _test_patching.renamed_os is original_os
      assert _test_patching.renamed_path is original_path
      assert _test_patching.renamed_join is original_join

def 	_lowerCAmelCase (    ):
      assert _test_patching.open is open

      lowercase__  =	'__test_patch_submodule_builtin_mock__'
      # _test_patching has "open" in its globals
      assert _test_patching.open is open
      with patch_submodule(_test_patching    ,	'open'    ,	A__						):
            assert _test_patching.open is mock

      # check that everthing is back to normal when the patch is over

      assert _test_patching.open is open

def 	_lowerCAmelCase (    ):
      # pandas.read_csv is not present in _test_patching
      lowercase__  =	'__test_patch_submodule_missing_mock__'
      with patch_submodule(_test_patching    ,	'pandas.read_csv'    ,	A__						):
            pass

def 	_lowerCAmelCase (    ):
      # builtin should always be mocked even if they're not in the globals
      # in case they're loaded at one point
      lowercase__  =	'__test_patch_submodule_missing_builtin_mock__'
      # _test_patching doesn't have "len" in its globals
      assert getattr(_test_patching    ,	'len'    ,	A__						) is None
      with patch_submodule(_test_patching    ,	'len'    ,	A__						):
            assert _test_patching.len is mock
      assert _test_patching.len is len

def 	_lowerCAmelCase (    ):
      lowercase__  =	'__test_patch_submodule_start_and_stop_mock__'
      lowercase__  =	patch_submodule(_test_patching    ,	'open'    ,	A__						)
      assert _test_patching.open is open
      patch.start()
      assert _test_patching.open is mock
      patch.stop()
      assert _test_patching.open is open

def 	_lowerCAmelCase (    ):
      from os import rename as original_rename
      from os.path import dirname as original_dirname
      from os.path import join as original_join

      lowercase__  =	'__test_patch_submodule_successive_join__'
      lowercase__  =	'__test_patch_submodule_successive_dirname__'
      lowercase__  =	'__test_patch_submodule_successive_rename__'
      assert _test_patching.os.path.join is original_join
      assert _test_patching.os.path.dirname is original_dirname
      assert _test_patching.os.rename is original_rename

      with patch_submodule(_test_patching    ,	'os.path.join'    ,	A__						):
            with patch_submodule(_test_patching    ,	'os.rename'    ,	A__						):
                  with patch_submodule(_test_patching    ,	'os.path.dirname'    ,	A__						):
                        assert _test_patching.os.path.join is mock_join
                        assert _test_patching.os.path.dirname is mock_dirname
                        assert _test_patching.os.rename is mock_rename

    # try another order
      with patch_submodule(_test_patching    ,	'os.rename'    ,	A__						):
            with patch_submodule(_test_patching    ,	'os.path.join'    ,	A__						):
                  with patch_submodule(_test_patching    ,	'os.path.dirname'    ,	A__						):
                        assert _test_patching.os.path.join is mock_join
                        assert _test_patching.os.path.dirname is mock_dirname
                        assert _test_patching.os.rename is mock_rename

      assert _test_patching.os.path.join is original_join
      assert _test_patching.os.path.dirname is original_dirname
      assert _test_patching.os.rename is original_rename

def 	_lowerCAmelCase (    ):
      lowercase__  =	'__test_patch_submodule_doesnt_exist_mock__'
      with patch_submodule(_test_patching    ,	'__module_that_doesn_exist__.__attribute_that_doesn_exist__'    ,	A__						):
            pass
      with patch_submodule(_test_patching    ,	'os.__attribute_that_doesn_exist__'    ,	A__						):
            pass
