


"""simple docstring"""



import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
 import torch

if is_soundfile_availble():
 import soundfile as sf

if is_vision_available():
 from PIL import Image






def       lowerCamelCase					(a_						:Union[str, Any]="")     ->							str:
       lowercase		:Optional[int]       							=				tempfile.mkdtemp()
       return os.path.join(a_				,				str(uuid.uuida()) + suffix)
@require_soundfile
@require_torch
class 					__magic_name__		(			unittest.TestCase     ):






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:Optional[int]       							=				torch.rand(1_2  ,     dtype=torch.floataa				) - 0.5
              lowercase		:Union[str, Any]       							=				AgentAudio(snake_case__				)
              lowercase		:Tuple       							=				str(agent_type.to_string()				)

              # Ensure that the tensor and the agent_type's tensor are the same
              self.assertTrue(torch.allclose(snake_case__  ,     agent_type.to_raw()  ,     atol=1e-4				)				)

              del agent_type

              # Ensure the path remains even after the object deletion
              self.assertTrue(os.path.exists(snake_case__				)				)

              # Ensure that the file contains the same value as the original tensor
              lowercase							,  lowercase		:Union[str, Any]       							=				sf.read(snake_case__				)
              self.assertTrue(torch.allclose(snake_case__  ,     torch.tensor(snake_case__				)  ,     atol=1e-4				)				)







       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:List[Any]       							=				torch.rand(1_2  ,     dtype=torch.floataa				) - 0.5
              lowercase		:List[str]       							=				get_new_path(suffix='''.wav'''				)
              sf.write(snake_case__  ,     snake_case__  ,     1_6_0_0_0				)

              lowercase		:Tuple       							=				AgentAudio(snake_case__				)

              self.assertTrue(torch.allclose(snake_case__  ,     agent_type.to_raw()  ,     atol=1e-4				)				)
              self.assertEqual(agent_type.to_string()  ,     snake_case__				)







@require_vision
@require_torch
class 					__magic_name__		(			unittest.TestCase     ):






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:Optional[int]       							=				torch.randint(0  ,     2_5_6  ,     (6_4, 6_4, 3)				)
              lowercase		:List[Any]       							=				AgentImage(snake_case__				)
              lowercase		:Any       							=				str(agent_type.to_string()				)

              # Ensure that the tensor and the agent_type's tensor are the same
              self.assertTrue(torch.allclose(snake_case__  ,     agent_type._tensor  ,     atol=1e-4				)				)

              self.assertIsInstance(agent_type.to_raw()  ,     Image.Image				)

              # Ensure the path remains even after the object deletion
              del agent_type
              self.assertTrue(os.path.exists(snake_case__				)				)






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              lowercase		:List[str]       							=				Path(get_tests_dir('''fixtures/tests_samples/COCO'''				)				) / '''000000039769.png'''
              lowercase		:Optional[int]       							=				Image.open(snake_case__				)
              lowercase		:List[Any]       							=				AgentImage(snake_case__				)

              self.assertTrue(path.samefile(agent_type.to_string()				)				)
              self.assertTrue(image == agent_type.to_raw()				)

              # Ensure the path remains even after the object deletion
              del agent_type
              self.assertTrue(os.path.exists(snake_case__				)				)







       def  __snake_case						(   self  :    int				):

              '''simple docstring'''






              lowercase		:Optional[Any]       							=				Path(get_tests_dir('''fixtures/tests_samples/COCO'''				)				) / '''000000039769.png'''
              lowercase		:Any       							=				Image.open(snake_case__				)
              lowercase		:str       							=				AgentImage(snake_case__				)

              self.assertFalse(path.samefile(agent_type.to_string()				)				)
              self.assertTrue(image == agent_type.to_raw()				)

              # Ensure the path remains even after the object deletion
              del agent_type
              self.assertTrue(os.path.exists(snake_case__				)				)







class 					__magic_name__		(			unittest.TestCase     ):






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              lowercase		:Union[str, Any]       							=				'''Hey!'''
              lowercase		:str       							=				AgentText(snake_case__				)

              self.assertEqual(snake_case__  ,     agent_type.to_string()				)
              self.assertEqual(snake_case__  ,     agent_type.to_raw()				)
              self.assertEqual(snake_case__  ,     snake_case__				)





"""simple docstring"""



import unittest

import torch

from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism

from .test_modeling_common import ModelTesterMixin, UNetTesterMixin


enable_full_determinism()
class 					__magic_name__		(			__UpperCAmelCase			,						__UpperCAmelCase			,						unittest.TestCase     ):
       __A			:      List[str]        =   VQModel
       __A			:      Any        =   "sample"






       @property
       def  __snake_case						(   self  :    int  ,     snake_case__  :    int=(3_2, 3_2)				):

              '''simple docstring'''






              lowercase		:Optional[int]       							=				4
              lowercase		:Tuple       							=				3

              lowercase		:List[str]       							=				floats_tensor((batch_size, num_channels) + sizes				).to(snake_case__				)

              return {"sample": image}






       @property
       def  __snake_case						(   self  :    Union[str, Any]				):

              '''simple docstring'''






              return (3, 3_2, 3_2)






       @property
       def  __snake_case						(   self  :    List[str]				):

              '''simple docstring'''






              return (3, 3_2, 3_2)






       def  __snake_case						(   self  :    Dict				):

              '''simple docstring'''






              lowercase		:Optional[int]       							=				{
                  '''block_out_channels''': [3_2, 6_4],
                  '''in_channels''': 3,
                  '''out_channels''': 3,
                  '''down_block_types''': ['''DownEncoderBlock2D''', '''DownEncoderBlock2D'''],
                  '''up_block_types''': ['''UpDecoderBlock2D''', '''UpDecoderBlock2D'''],
                  '''latent_channels''': 3,
              }
              lowercase		:Dict       							=				self.dummy_input
              return init_dict, inputs_dict






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              pass






       def  __snake_case						(   self  :    Union[str, Any]				):

              '''simple docstring'''






              pass






       def  __snake_case						(   self  :    Dict				):

              '''simple docstring'''






              lowercase							,  lowercase		:Optional[int]       							=				VQModel.from_pretrained('''fusing/vqgan-dummy'''  ,     output_loading_info=snake_case__				)
              self.assertIsNotNone(snake_case__				)
              self.assertEqual(len(loading_info['''missing_keys''']				)  ,     0				)

              model.to(snake_case__				)
              lowercase		:List[str]       							=				model(**self.dummy_input				)

              assert image is not None, "Make sure output is not None"







       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              lowercase		:Optional[int]       							=				VQModel.from_pretrained('''fusing/vqgan-dummy'''				)
              model.to(snake_case__				).eval()

              torch.manual_seed(0				)
              if torch.cuda.is_available():
                     torch.cuda.manual_seed_all(0				)

              lowercase		:List[Any]       							=				torch.randn(1  ,     model.config.in_channels  ,     model.config.sample_size  ,     model.config.sample_size				)
              lowercase		:int       							=				image.to(snake_case__				)
              with torch.no_grad():
                     lowercase		:str       							=				model(snake_case__				).sample

              lowercase		:List[Any]       							=				output[0, -1, -3:, -3:].flatten().cpu()
              # fmt: off
              lowercase		:Tuple       							=				torch.tensor([-0.01_53, -0.40_44, -0.18_80, -0.51_61, -0.24_18, -0.40_72, -0.16_12, -0.06_33, -0.01_43]				)
              # fmt: on
              self.assertTrue(torch.allclose(snake_case__  ,     snake_case__  ,     atol=1e-3				)				)

