

import unittest

from diffusers import __version__
from diffusers.utils import deprecate



class  __snake_case					(      unittest.TestCase    ):
		__lowerCAmelCase       :		Tuple  	=					'.'.join([str(int(__version__.split('.'    )[0]    ) + 1    )] + __version__.split('.'    )[1:]    )
		__lowerCAmelCase       :		Optional[int]  	=					'0.0.1'

		def   lowerCAmelCase__       (   self):
						SCREAMING_SNAKE_CASE_													=  {'deprecated_arg': 4}

						with self.assertWarns(_A) as warning:
										SCREAMING_SNAKE_CASE_													=  deprecate('deprecated_arg'  ,						self.higher_version  ,						'message'  ,						take_from=_A)

						assert output == 4
						assert (
						    str(warning.warning)
						    == f"""The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."""
						    " message"
						)

		def   lowerCAmelCase__       (   self):
						SCREAMING_SNAKE_CASE_													=  {'deprecated_arg': 4}

						with self.assertWarns(_A) as warning:
										SCREAMING_SNAKE_CASE_													=  deprecate(('deprecated_arg', self.higher_version, 'message')  ,						take_from=_A)

						assert output == 4
						assert (
						    str(warning.warning)
						    == f"""The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."""
						    " message"
						)

		def   lowerCAmelCase__       (   self):
						SCREAMING_SNAKE_CASE_													=  {'deprecated_arg_1': 4, 'deprecated_arg_2': 8}
						with self.assertWarns(_A) as warning:
										SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_													=  deprecate(
										    ('deprecated_arg_1', self.higher_version, 'Hey')  ,						('deprecated_arg_2', self.higher_version, 'Hey')  ,						take_from=_A  ,						)
						assert output_a == 4
						assert output_a == 8
						assert (
						    str(warning.warnings[0].message)
						    == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
						    f""" {self.higher_version}. Hey"""
						)
						assert (
						    str(warning.warnings[1].message)
						    == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
						    f""" {self.higher_version}. Hey"""
						)

		def   lowerCAmelCase__       (   self):
						SCREAMING_SNAKE_CASE_													=  {'deprecated_arg': 4}

						with self.assertRaises(_A) as error:
										deprecate(('wrong_arg', self.higher_version, 'message')  ,						take_from=_A)

						assert "test_deprecate_function_incorrect_arg in" in str(error.exception)
						assert "line" in str(error.exception)
						assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception)

		def   lowerCAmelCase__       (   self):
						with self.assertWarns(_A) as warning:
										deprecate(('deprecated_arg', self.higher_version, 'message'))

						assert (
						    str(warning.warning)
						    == f"""`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message"""
						)

		def   lowerCAmelCase__       (   self):
						with self.assertWarns(_A) as warning:
										deprecate(
										    ('deprecated_arg_1', self.higher_version, 'Hey')  ,						('deprecated_arg_2', self.higher_version, 'Hey')  ,						)
						assert (
						    str(warning.warnings[0].message)
						    == f"""`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey"""
						)
						assert (
						    str(warning.warnings[1].message)
						    == f"""`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey"""
						)

		def   lowerCAmelCase__       (   self):



						class  __snake_case					:
								__lowerCAmelCase       :		Tuple  	=					5

						with self.assertWarns(_A) as warning:
										SCREAMING_SNAKE_CASE_													=  deprecate(('arg', self.higher_version, 'message')  ,						take_from=Args())

						assert arg == 5
						assert (
						    str(warning.warning)
						    == f"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
						)

		def   lowerCAmelCase__       (   self):



						class  __snake_case					:
								__lowerCAmelCase       :		Tuple  	=					5
								__lowerCAmelCase       :		Union[str, Any]  	=					7

						with self.assertWarns(_A) as warning:
										SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_													=  deprecate(
										    ('arg', self.higher_version, 'message')  ,						('foo', self.higher_version, 'message')  ,						('does not exist', self.higher_version, 'message')  ,						take_from=Args()  ,						)

						assert arg_a == 5
						assert arg_a == 7
						assert (
						    str(warning.warning)
						    == f"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
						)
						assert (
						    str(warning.warnings[0].message)
						    == f"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
						)
						assert (
						    str(warning.warnings[1].message)
						    == f"""The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message"""
						)

		def   lowerCAmelCase__       (   self):
						SCREAMING_SNAKE_CASE_													=  {'deprecated_arg': 4}

						with self.assertRaises(_A) as error:
										deprecate(('wrong_arg', self.lower_version, 'message')  ,						take_from=_A)

						assert (
						    str(error.exception)
						    == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
						    f""" {__version__} is >= {self.lower_version}"""
						)

		def   lowerCAmelCase__       (   self):
						with self.assertWarns(_A) as warning:
										deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')  ,						standard_warn=_A)

						assert str(warning.warning) == "This message is better!!!"


		def   lowerCAmelCase__       (   self):
						with self.assertWarns(_A) as warning:
										deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')  ,						standard_warn=_A)
						assert str(warning.warning) == "This message is better!!!"
						assert "diffusers/tests/others/test_utils.py" in warning.filename





import torch

from diffusers import HeunDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest



class  __snake_case					(      lowerCAmelCase__    ):
  __lowerCAmelCase       :		Union[str, Any]  	=					(HeunDiscreteScheduler,)
  __lowerCAmelCase       :		Optional[int]  	=					10

  def   lowerCAmelCase__       (   self  ,						**_A):
      SCREAMING_SNAKE_CASE_													=  {
          'num_train_timesteps': 1100,
          'beta_start': 0.0_0_0_1,
          'beta_end': 0.0_2,
          'beta_schedule': 'linear',
      }

      config.update(**_A)
      return config

  def   lowerCAmelCase__       (   self):
      for timesteps in [10, 50, 100, 1000]:
          self.check_over_configs(num_train_timesteps=_A)

  def   lowerCAmelCase__       (   self):
      for beta_start, beta_end in zip([0.0_0_0_0_1, 0.0_0_0_1, 0.0_0_1]  ,						[0.0_0_0_2, 0.0_0_2, 0.0_2]):
          self.check_over_configs(beta_start=_A  ,						beta_end=_A)

  def   lowerCAmelCase__       (   self):
      for schedule in ["linear", "scaled_linear", "exp"]:
          self.check_over_configs(beta_schedule=_A)

  def   lowerCAmelCase__       (   self):
      for clip_sample_range in [1.0, 2.0, 3.0]:
          self.check_over_configs(clip_sample_range=_A  ,						clip_sample=_A)

  def   lowerCAmelCase__       (   self):
      for prediction_type in ["epsilon", "v_prediction", "sample"]:
          self.check_over_configs(prediction_type=_A)

  def   lowerCAmelCase__       (   self):
      SCREAMING_SNAKE_CASE_													=  self.scheduler_classes[0]
      SCREAMING_SNAKE_CASE_													=  self.get_scheduler_config()
      SCREAMING_SNAKE_CASE_													=  scheduler_class(**_A)

      scheduler.set_timesteps(self.num_inference_steps)

      SCREAMING_SNAKE_CASE_													=  self.dummy_model()
      SCREAMING_SNAKE_CASE_													=  self.dummy_sample_deter * scheduler.init_noise_sigma
      SCREAMING_SNAKE_CASE_													=  sample.to(_A)

      for i, t in enumerate(scheduler.timesteps):
          SCREAMING_SNAKE_CASE_													=  scheduler.scale_model_input(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  model(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  scheduler.step(_A  ,						_A  ,						_A)
          SCREAMING_SNAKE_CASE_													=  output.prev_sample

      SCREAMING_SNAKE_CASE_													=  torch.sum(torch.abs(_A))
      SCREAMING_SNAKE_CASE_													=  torch.mean(torch.abs(_A))

      if torch_device in ["cpu", "mps"]:
          assert abs(result_sum.item() - 0.1_2_3_3) < 1E-2
          assert abs(result_mean.item() - 0.0_0_0_2) < 1E-3
      else:
          # CUDA
          assert abs(result_sum.item() - 0.1_2_3_3) < 1E-2
          assert abs(result_mean.item() - 0.0_0_0_2) < 1E-3

  def   lowerCAmelCase__       (   self):
      SCREAMING_SNAKE_CASE_													=  self.scheduler_classes[0]
      SCREAMING_SNAKE_CASE_													=  self.get_scheduler_config(prediction_type='v_prediction')
      SCREAMING_SNAKE_CASE_													=  scheduler_class(**_A)

      scheduler.set_timesteps(self.num_inference_steps)

      SCREAMING_SNAKE_CASE_													=  self.dummy_model()
      SCREAMING_SNAKE_CASE_													=  self.dummy_sample_deter * scheduler.init_noise_sigma
      SCREAMING_SNAKE_CASE_													=  sample.to(_A)

      for i, t in enumerate(scheduler.timesteps):
          SCREAMING_SNAKE_CASE_													=  scheduler.scale_model_input(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  model(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  scheduler.step(_A  ,						_A  ,						_A)
          SCREAMING_SNAKE_CASE_													=  output.prev_sample

      SCREAMING_SNAKE_CASE_													=  torch.sum(torch.abs(_A))
      SCREAMING_SNAKE_CASE_													=  torch.mean(torch.abs(_A))

      if torch_device in ["cpu", "mps"]:
          assert abs(result_sum.item() - 4.6_934E-07) < 1E-2
          assert abs(result_mean.item() - 6.1_112E-10) < 1E-3
      else:
          # CUDA
          assert abs(result_sum.item() - 4.693_428_650_170_972E-07) < 1E-2
          assert abs(result_mean.item() - 0.0_0_0_2) < 1E-3

  def   lowerCAmelCase__       (   self):
      SCREAMING_SNAKE_CASE_													=  self.scheduler_classes[0]
      SCREAMING_SNAKE_CASE_													=  self.get_scheduler_config()
      SCREAMING_SNAKE_CASE_													=  scheduler_class(**_A)

      scheduler.set_timesteps(self.num_inference_steps  ,						device=_A)

      SCREAMING_SNAKE_CASE_													=  self.dummy_model()
      SCREAMING_SNAKE_CASE_													=  self.dummy_sample_deter.to(_A) * scheduler.init_noise_sigma

      for t in scheduler.timesteps:
          SCREAMING_SNAKE_CASE_													=  scheduler.scale_model_input(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  model(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  scheduler.step(_A  ,						_A  ,						_A)
          SCREAMING_SNAKE_CASE_													=  output.prev_sample

      SCREAMING_SNAKE_CASE_													=  torch.sum(torch.abs(_A))
      SCREAMING_SNAKE_CASE_													=  torch.mean(torch.abs(_A))

      if str(_A).startswith('cpu'):
          # The following sum varies between 148 and 156 on mps. Why?
          assert abs(result_sum.item() - 0.1_2_3_3) < 1E-2
          assert abs(result_mean.item() - 0.0_0_0_2) < 1E-3
      elif str(_A).startswith('mps'):
          # Larger tolerance on mps
          assert abs(result_mean.item() - 0.0_0_0_2) < 1E-2
      else:
          # CUDA
          assert abs(result_sum.item() - 0.1_2_3_3) < 1E-2
          assert abs(result_mean.item() - 0.0_0_0_2) < 1E-3


  def   lowerCAmelCase__       (   self):
      SCREAMING_SNAKE_CASE_													=  self.scheduler_classes[0]
      SCREAMING_SNAKE_CASE_													=  self.get_scheduler_config()
      SCREAMING_SNAKE_CASE_													=  scheduler_class(**_A  ,						use_karras_sigmas=_A)

      scheduler.set_timesteps(self.num_inference_steps  ,						device=_A)

      SCREAMING_SNAKE_CASE_													=  self.dummy_model()
      SCREAMING_SNAKE_CASE_													=  self.dummy_sample_deter.to(_A) * scheduler.init_noise_sigma
      SCREAMING_SNAKE_CASE_													=  sample.to(_A)

      for t in scheduler.timesteps:
          SCREAMING_SNAKE_CASE_													=  scheduler.scale_model_input(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  model(_A  ,						_A)

          SCREAMING_SNAKE_CASE_													=  scheduler.step(_A  ,						_A  ,						_A)
          SCREAMING_SNAKE_CASE_													=  output.prev_sample

      SCREAMING_SNAKE_CASE_													=  torch.sum(torch.abs(_A))
      SCREAMING_SNAKE_CASE_													=  torch.mean(torch.abs(_A))

      assert abs(result_sum.item() - 0.0_0_0_1_5) < 1E-2
      assert abs(result_mean.item() - 1.9_869_554_535_034_695E-07) < 1E-2


