






"""simple docstring"""






import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs




class 							lowerCAmelCase__       (    UpperCAmelCase__				):






      '''simple docstring'''

      def __init__(		self  :						int		,			lowercase_  :						Dict		,			lowercase_  :						Dict=None		,			lowercase_  :						Optional[int]=True		,			lowercase_  :						Dict=None		,			**lowercase_  :						Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Tuple							=	parent
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	config_class
          SCREAMING_SNAKE_CASE_   :						str							=	has_text_modality
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	kwargs
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	common_properties
      def _SCREAMING_SNAKE_CASE				(		self  :						Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	self.config_class(**self.inputs_dict)
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	(
              ['''hidden_size''', '''num_attention_heads''', '''num_hidden_layers''']
              if self.common_properties is None
              else self.common_properties
          )

          # Add common fields for text models
          if self.has_text_modality:
              common_properties.extend(['''vocab_size'''])

          # Test that config has the common properties as getters
          for prop in common_properties:
              self.parent.assertTrue(hasattr(lowercase_		,			lowercase_)		,			msg=F'`{prop}` does not exist')

          # Test that config has the common properties as setter
          for idx, name in enumerate(lowercase_):
              try:
                  setattr(lowercase_		,			lowercase_		,			lowercase_)
                  self.parent.assertEqual(
                      getattr(lowercase_		,			lowercase_)		,			lowercase_		,			msg=F'`{name} value {idx} expected, but was {getattr(lowercase_		,			lowercase_)}')
              except NotImplementedError:
                  # Some models might not be able to implement setters for common_properties
                  # In that case, a NotImplementedError is raised
                  pass

        # Test if config class can be called with Config(prop_name=..)
          for idx, name in enumerate(lowercase_):
              try:
                  SCREAMING_SNAKE_CASE_   :						str							=	self.config_class(**{name: idx})
                  self.parent.assertEqual(
                      getattr(lowercase_		,			lowercase_)		,			lowercase_		,			msg=F'`{name} value {idx} expected, but was {getattr(lowercase_		,			lowercase_)}')
              except NotImplementedError:
                  # Some models might not be able to implement setters for common_properties
                  # In that case, a NotImplementedError is raised
                  pass
      def _SCREAMING_SNAKE_CASE				(		self  :						Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Dict							=	self.config_class(**self.inputs_dict)
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	json.loads(config.to_json_string())
          for key, value in self.inputs_dict.items():
              self.parent.assertEqual(obj[key]		,			lowercase_)
      def _SCREAMING_SNAKE_CASE				(		self  :						str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	self.config_class(**self.inputs_dict)

          with tempfile.TemporaryDirectory() as tmpdirname:
              SCREAMING_SNAKE_CASE_   :						List[str]							=	os.path.join(lowercase_		,			'''config.json''')
              config_first.to_json_file(lowercase_)
              SCREAMING_SNAKE_CASE_   :						Dict							=	self.config_class.from_json_file(lowercase_)

          self.parent.assertEqual(config_second.to_dict()		,			config_first.to_dict())
      def _SCREAMING_SNAKE_CASE				(		self  :						str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	self.config_class(**self.inputs_dict)

          with tempfile.TemporaryDirectory() as tmpdirname:
              config_first.save_pretrained(lowercase_)
              SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	self.config_class.from_pretrained(lowercase_)

          self.parent.assertEqual(config_second.to_dict()		,			config_first.to_dict())
      def _SCREAMING_SNAKE_CASE				(		self  :						int):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	self.config_class(**self.inputs_dict)

          SCREAMING_SNAKE_CASE_   :						List[Any]							=	'''test'''
          with tempfile.TemporaryDirectory() as tmpdirname:
              SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	os.path.join(lowercase_		,			lowercase_)
              config_first.save_pretrained(lowercase_)
              SCREAMING_SNAKE_CASE_   :						str							=	self.config_class.from_pretrained(lowercase_		,			subfolder=lowercase_)

          self.parent.assertEqual(config_second.to_dict()		,			config_first.to_dict())
      def _SCREAMING_SNAKE_CASE				(		self  :						str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Any							=	self.config_class(**self.inputs_dict		,			num_labels=5)
          self.parent.assertEqual(len(config.idalabel)		,			5)
          self.parent.assertEqual(len(config.labelaid)		,			5)

          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	3
          self.parent.assertEqual(len(config.idalabel)		,			3)
          self.parent.assertEqual(len(config.labelaid)		,			3)
      def _SCREAMING_SNAKE_CASE				(		self  :						Optional[Any]):




          '''simple docstring'''


          if self.config_class.is_composition:
              return
          SCREAMING_SNAKE_CASE_   :						Dict							=	self.config_class()
          self.parent.assertIsNotNone(lowercase_)
      def _SCREAMING_SNAKE_CASE				(		self  :						Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	copy.deepcopy(lowercase_)
          SCREAMING_SNAKE_CASE_   :						List[str]							=	self.config_class(**lowercase_)
          SCREAMING_SNAKE_CASE_   :						str							=	[]
          for key, value in config_common_kwargs.items():
              if key == "torch_dtype":
                  if not is_torch_available():
                      continue
                  else:
                      import torch

                      if config.torch_dtype != torch.floataa:
                          wrong_values.append(('''torch_dtype''', config.torch_dtype, torch.floataa))
              elif getattr(lowercase_		,			lowercase_) != value:
                  wrong_values.append((key, getattr(lowercase_		,			lowercase_), value))

          if len(lowercase_) > 0:
              SCREAMING_SNAKE_CASE_   :						Tuple							=	'''\n'''.join([F'- {v[0]}: got {v[1]} instead of {v[2]}' for v in wrong_values])
              raise ValueError(F'The following keys were not properly set in the config:\n{errors}')



      def _SCREAMING_SNAKE_CASE				(		self  :						str):




          '''simple docstring'''


          self.create_and_test_config_common_properties()
          self.create_and_test_config_to_json_string()
          self.create_and_test_config_to_json_file()
          self.create_and_test_config_from_and_save_pretrained()
          self.create_and_test_config_from_and_save_pretrained_subfolder()
          self.create_and_test_config_with_num_labels()
          self.check_config_can_be_init_without_params()
          self.check_config_arguments_init()










"""simple docstring"""






import unittest

import numpy as np
import torch

from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()




class 							lowerCAmelCase__       (    unittest.TestCase				):






      '''simple docstring'''

      @property
      def _SCREAMING_SNAKE_CASE				(		self  :						Tuple):




          '''simple docstring'''


          torch.manual_seed(0)
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	UNetaDModel(
              block_out_channels=(32, 64)		,			layers_per_block=2		,			sample_size=32		,			in_channels=3		,			out_channels=3		,			down_block_types=('''DownBlock2D''', '''AttnDownBlock2D''')		,			up_block_types=('''AttnUpBlock2D''', '''UpBlock2D''')		,			)
          return model



      def _SCREAMING_SNAKE_CASE				(		self  :						Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						int							=	self.dummy_uncond_unet
          SCREAMING_SNAKE_CASE_   :						int							=	ScoreSdeVeScheduler()

          SCREAMING_SNAKE_CASE_   :						List[str]							=	ScoreSdeVePipeline(unet=lowercase_		,			scheduler=lowercase_)
          sde_ve.to(lowercase_)
          sde_ve.set_progress_bar_config(disable=lowercase_)

          SCREAMING_SNAKE_CASE_   :						Tuple							=	torch.manual_seed(0)
          SCREAMING_SNAKE_CASE_   :						Dict							=	sde_ve(num_inference_steps=2		,			output_type='''numpy'''		,			generator=lowercase_).images

          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	torch.manual_seed(0)
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	sde_ve(num_inference_steps=2		,			output_type='''numpy'''		,			generator=lowercase_		,			return_dict=lowercase_)[
              0
          ]

          SCREAMING_SNAKE_CASE_   :						Dict							=	image[0, -3:, -3:, -1]
          SCREAMING_SNAKE_CASE_   :						List[Any]							=	image_from_tuple[0, -3:, -3:, -1]

          assert image.shape == (1, 32, 32, 3)
          SCREAMING_SNAKE_CASE_   :						str							=	np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0])

          assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
          assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2




@slow
@require_torch
class 							lowerCAmelCase__       (    unittest.TestCase				):






      '''simple docstring'''

      def _SCREAMING_SNAKE_CASE				(		self  :						Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	'''google/ncsnpp-church-256'''
          SCREAMING_SNAKE_CASE_   :						str							=	UNetaDModel.from_pretrained(lowercase_)

          SCREAMING_SNAKE_CASE_   :						Any							=	ScoreSdeVeScheduler.from_pretrained(lowercase_)

          SCREAMING_SNAKE_CASE_   :						Any							=	ScoreSdeVePipeline(unet=lowercase_		,			scheduler=lowercase_)
          sde_ve.to(lowercase_)
          sde_ve.set_progress_bar_config(disable=lowercase_)

          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	torch.manual_seed(0)
          SCREAMING_SNAKE_CASE_   :						List[str]							=	sde_ve(num_inference_steps=10		,			output_type='''numpy'''		,			generator=lowercase_).images

          SCREAMING_SNAKE_CASE_   :						Any							=	image[0, -3:, -3:, -1]

          assert image.shape == (1, 256, 256, 3)

          SCREAMING_SNAKE_CASE_   :						int							=	np.array([0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0])

          assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2


