


import tempfile

import torch

from diffusers import PNDMScheduler

from .test_schedulers import SchedulerCommonTest







class 	snake_case_       (lowerCamelCase_				):
					UpperCAmelCase__ :   str   				=      (PNDMScheduler,)
					UpperCAmelCase__ :   Tuple   				=      (('''num_inference_steps''', 5_0),)
					def 			lowerCamelCase__(				self       :Optional[int]      ,**__snake_case       :int				) ->   Optional[Any]:
												a__					=					{
												    'num_train_timesteps': 10_00,
												    'beta_start': 0.00_01,
												    'beta_end': 0.02,
												    'beta_schedule': 'linear',
												}

												config.update(**__snake_case				)
												return config
					def 			lowerCamelCase__(				self       :Optional[Any]      ,__snake_case       :Optional[Any]=0      ,**__snake_case       :Dict				) ->   Optional[Any]:
												a__					=					dict(self.forward_default_kwargs				)
												a__					=					kwargs.pop('num_inference_steps'      ,__snake_case				)
												a__					=					self.dummy_sample
												a__					=					0.1 * sample
												a__					=					[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]

												for scheduler_class in self.scheduler_classes:
																			a__					=					self.get_scheduler_config(**__snake_case				)
																			a__					=					scheduler_class(**__snake_case				)
																			scheduler.set_timesteps(__snake_case				)
																			# copy over dummy past residuals
																			a__					=					dummy_past_residuals[:]

																			with tempfile.TemporaryDirectory() as tmpdirname:
																										scheduler.save_config(__snake_case				)
																										a__					=					scheduler_class.from_pretrained(__snake_case				)
																										new_scheduler.set_timesteps(__snake_case				)
																										# copy over dummy past residuals
																										a__					=					dummy_past_residuals[:]

																			a__					=					scheduler.step_prk(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample
																			a__					=					new_scheduler.step_prk(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample

																			assert torch.sum(torch.abs(output - new_output				)				) < 1E-5, "Scheduler outputs are not identical"

																			a__					=					scheduler.step_plms(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample
																			a__					=					new_scheduler.step_plms(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample

																			assert torch.sum(torch.abs(output - new_output				)				) < 1E-5, "Scheduler outputs are not identical"
					def 			lowerCamelCase__(				self       :int				) ->   str:
												pass
					def 			lowerCamelCase__(				self       :List[str]      ,__snake_case       :int=0      ,**__snake_case       :Union[str, Any]				) ->   List[Any]:
												a__					=					dict(self.forward_default_kwargs				)
												a__					=					kwargs.pop('num_inference_steps'      ,__snake_case				)
												a__					=					self.dummy_sample
												a__					=					0.1 * sample
												a__					=					[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]

												for scheduler_class in self.scheduler_classes:
																			a__					=					self.get_scheduler_config()
																			a__					=					scheduler_class(**__snake_case				)
																			scheduler.set_timesteps(__snake_case				)

																			# copy over dummy past residuals (must be after setting timesteps)
																			a__					=					dummy_past_residuals[:]

																			with tempfile.TemporaryDirectory() as tmpdirname:
																										scheduler.save_config(__snake_case				)
																										a__					=					scheduler_class.from_pretrained(__snake_case				)
																										# copy over dummy past residuals
																										new_scheduler.set_timesteps(__snake_case				)

																										# copy over dummy past residual (must be after setting timesteps)
																										a__					=					dummy_past_residuals[:]

																			a__					=					scheduler.step_prk(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample
																			a__					=					new_scheduler.step_prk(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample

																			assert torch.sum(torch.abs(output - new_output				)				) < 1E-5, "Scheduler outputs are not identical"

																			a__					=					scheduler.step_plms(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample
																			a__					=					new_scheduler.step_plms(__snake_case      ,__snake_case      ,__snake_case      ,**__snake_case				).prev_sample

																			assert torch.sum(torch.abs(output - new_output				)				) < 1E-5, "Scheduler outputs are not identical"
					def 			lowerCamelCase__(				self       :int      ,**__snake_case       :Tuple				) ->   List[Any]:
												a__					=					self.scheduler_classes[0]
												a__					=					self.get_scheduler_config(**__snake_case				)
												a__					=					scheduler_class(**__snake_case				)

												a__					=					10
												a__					=					self.dummy_model()
												a__					=					self.dummy_sample_deter
												scheduler.set_timesteps(__snake_case				)

												for i, t in enumerate(scheduler.prk_timesteps				):
																			a__					=					model(__snake_case      ,__snake_case				)
																			a__					=					scheduler.step_prk(__snake_case      ,__snake_case      ,__snake_case				).prev_sample

												for i, t in enumerate(scheduler.plms_timesteps				):
																			a__					=					model(__snake_case      ,__snake_case				)
																			a__					=					scheduler.step_plms(__snake_case      ,__snake_case      ,__snake_case				).prev_sample

												return sample
					def 			lowerCamelCase__(				self       :Optional[Any]				) ->   Dict:
												a__					=					dict(self.forward_default_kwargs				)

												a__					=					kwargs.pop('num_inference_steps'      ,__snake_case				)

												for scheduler_class in self.scheduler_classes:
																			a__					=					self.get_scheduler_config()
																			a__					=					scheduler_class(**__snake_case				)

																			a__					=					self.dummy_sample
																			a__					=					0.1 * sample

																			if num_inference_steps is not None and hasattr(__snake_case      ,'set_timesteps'				):
																										scheduler.set_timesteps(__snake_case				)
																			elif num_inference_steps is not None and not hasattr(__snake_case      ,'set_timesteps'				):
																										a__					=					num_inference_steps

																			# copy over dummy past residuals (must be done after set_timesteps)
																			a__					=					[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]
																			a__					=					dummy_past_residuals[:]

																			a__					=					scheduler.step_prk(__snake_case      ,0      ,__snake_case      ,**__snake_case				).prev_sample
																			a__					=					scheduler.step_prk(__snake_case      ,1      ,__snake_case      ,**__snake_case				).prev_sample

																			self.assertEqual(output_a.shape      ,sample.shape				)
																			self.assertEqual(output_a.shape      ,output_a.shape				)

																			a__					=					scheduler.step_plms(__snake_case      ,0      ,__snake_case      ,**__snake_case				).prev_sample
																			a__					=					scheduler.step_plms(__snake_case      ,1      ,__snake_case      ,**__snake_case				).prev_sample

																			self.assertEqual(output_a.shape      ,sample.shape				)
																			self.assertEqual(output_a.shape      ,output_a.shape				)
					def 			lowerCamelCase__(				self       :Any				) ->   Tuple:
												for timesteps in [1_00, 10_00]:
																			self.check_over_configs(num_train_timesteps=__snake_case				)
					def 			lowerCamelCase__(				self       :List[str]				) ->   Dict:
												for steps_offset in [0, 1]:
																			self.check_over_configs(steps_offset=__snake_case				)

												a__					=					self.scheduler_classes[0]
												a__					=					self.get_scheduler_config(steps_offset=1				)
												a__					=					scheduler_class(**__snake_case				)
												scheduler.set_timesteps(10				)
												assert torch.equal(
												    scheduler.timesteps      ,torch.LongTensor(
												        [9_01, 8_51, 8_51, 8_01, 8_01, 7_51, 7_51, 7_01, 7_01, 6_51, 6_51, 6_01, 6_01, 5_01, 4_01, 3_01, 2_01, 1_01, 1]				)      ,)
					def 			lowerCamelCase__(				self       :List[str]				) ->   List[str]:
												for beta_start, beta_end in zip([0.00_01, 0.0_01]      ,[0.0_02, 0.02]				):
																			self.check_over_configs(beta_start=__snake_case      ,beta_end=__snake_case				)
					def 			lowerCamelCase__(				self       :Any				) ->   List[Any]:
												for schedule in ["linear", "squaredcos_cap_v2"]:
																			self.check_over_configs(beta_schedule=__snake_case				)
					def 			lowerCamelCase__(				self       :List[Any]				) ->   List[Any]:
												for prediction_type in ["epsilon", "v_prediction"]:
																			self.check_over_configs(prediction_type=__snake_case				)
					def 			lowerCamelCase__(				self       :Any				) ->   Union[str, Any]:
												for t in [1, 5, 10]:
																			self.check_over_forward(time_step=__snake_case				)
					def 			lowerCamelCase__(				self       :Optional[int]				) ->   Dict:
												for t, num_inference_steps in zip([1, 5, 10]      ,[10, 50, 1_00]				):
																			self.check_over_forward(num_inference_steps=__snake_case				)
					def 			lowerCamelCase__(				self       :Optional[Any]				) ->   Optional[int]:
												# earlier version of set_timesteps() caused an error indexing alpha's with inference steps as power of 3
												a__					=					27

												for scheduler_class in self.scheduler_classes:
																			a__					=					self.dummy_sample
																			a__					=					0.1 * sample

																			a__					=					self.get_scheduler_config()
																			a__					=					scheduler_class(**__snake_case				)

																			scheduler.set_timesteps(__snake_case				)

																			# before power of 3 fix, would error on first step, so we only need to do two
																			for i, t in enumerate(scheduler.prk_timesteps[:2]				):
																										a__					=					scheduler.step_prk(__snake_case      ,__snake_case      ,__snake_case				).prev_sample
					def 			lowerCamelCase__(				self       :Union[str, Any]				) ->   Optional[int]:
												with self.assertRaises(__snake_case				):
																			a__					=					self.scheduler_classes[0]
																			a__					=					self.get_scheduler_config()
																			a__					=					scheduler_class(**__snake_case				)

																			scheduler.step_plms(self.dummy_sample      ,1      ,self.dummy_sample				).prev_sample
					def 			lowerCamelCase__(				self       :Any				) ->   str:
												a__					=					self.full_loop()
												a__					=					torch.sum(torch.abs(__snake_case				)				)
												a__					=					torch.mean(torch.abs(__snake_case				)				)

												assert abs(result_sum.item() - 1_98.13_18				) < 1E-2
												assert abs(result_mean.item() - 0.25_80				) < 1E-3
					def 			lowerCamelCase__(				self       :Tuple				) ->   Tuple:
												a__					=					self.full_loop(prediction_type='v_prediction'				)
												a__					=					torch.sum(torch.abs(__snake_case				)				)
												a__					=					torch.mean(torch.abs(__snake_case				)				)

												assert abs(result_sum.item() - 67.39_86				) < 1E-2
												assert abs(result_mean.item() - 0.08_78				) < 1E-3
					def 			lowerCamelCase__(				self       :int				) ->   Any:
												# We specify different beta, so that the first alpha is 0.99
												a__					=					self.full_loop(set_alpha_to_one=__snake_case      ,beta_start=0.01				)
												a__					=					torch.sum(torch.abs(__snake_case				)				)
												a__					=					torch.mean(torch.abs(__snake_case				)				)

												assert abs(result_sum.item() - 2_30.03_99				) < 1E-2
												assert abs(result_mean.item() - 0.29_95				) < 1E-3



					def 			lowerCamelCase__(				self       :Tuple				) ->   int:
												# We specify different beta, so that the first alpha is 0.99
												a__					=					self.full_loop(set_alpha_to_one=__snake_case      ,beta_start=0.01				)
												a__					=					torch.sum(torch.abs(__snake_case				)				)
												a__					=					torch.mean(torch.abs(__snake_case				)				)

												assert abs(result_sum.item() - 1_86.94_82				) < 1E-2
												assert abs(result_mean.item() - 0.24_34				) < 1E-3








import inspect
import os
import unittest
from pathlib import Path

import torch

import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command







class 	snake_case_       (unittest.TestCase				):
					UpperCAmelCase__ :   Optional[Any]   				=      inspect.getfile(accelerate.test_utils				)
					UpperCAmelCase__ :   Tuple   				=      os.path.sep.join(mod_file.split(os.path.sep				)[:-1] + ['''scripts''', '''test_cli.py''']				)

					UpperCAmelCase__ :   Optional[int]   				=      ['''accelerate''', '''launch''']
					UpperCAmelCase__ :   List[str]   				=      Path.home() / '''.cache/huggingface/accelerate'''
					UpperCAmelCase__ :   Union[str, Any]   				=      '''default_config.yaml'''
					UpperCAmelCase__ :   List[Any]   				=      config_folder / config_file
					UpperCAmelCase__ :   Optional[int]   				=      config_folder / '''_default_config.yaml'''

					UpperCAmelCase__ :   int   				=      Path('''tests/test_configs'''				)
					@classmethod
					def 			lowerCamelCase__(				cls       :Any				) ->   int:
												if cls.config_path.is_file():
																			cls.config_path.rename(cls.changed_path				)
					@classmethod
					def 			lowerCamelCase__(				cls       :Dict				) ->   Union[str, Any]:
												if cls.changed_path.is_file():
																			cls.changed_path.rename(cls.config_path				)
					def 			lowerCamelCase__(				self       :Any				) ->   Optional[int]:
												a__					=					self.base_cmd
												if torch.cuda.is_available() and (torch.cuda.device_count() > 1):
																			cmd += ["--multi_gpu"]
												execute_subprocess_async(cmd + [self.test_file_path]      ,env=os.environ.copy()				)
					def 			lowerCamelCase__(				self       :str				) ->   List[Any]:
												for config in sorted(self.test_config_path.glob('**/*.yaml'				)				):
																			with self.subTest(config_file=__snake_case				):
																										execute_subprocess_async(
																										    self.base_cmd + ['--config_file', str(__snake_case				), self.test_file_path]      ,env=os.environ.copy()				)



					def 			lowerCamelCase__(				self       :int				) ->   List[str]:
												execute_subprocess_async(['accelerate', 'test']      ,env=os.environ.copy()				)







class 	snake_case_       (unittest.TestCase				):
					UpperCAmelCase__ :   List[Any]   				=      '''test-tpu'''
					UpperCAmelCase__ :   str   				=      '''us-central1-a'''
					UpperCAmelCase__ :   Optional[Any]   				=      '''ls'''
					UpperCAmelCase__ :   Optional[int]   				=      ['''accelerate''', '''tpu-config''']
					UpperCAmelCase__ :   Any   				=      '''cd /usr/share'''
					UpperCAmelCase__ :   Tuple   				=      '''tests/test_samples/test_command_file.sh'''
					UpperCAmelCase__ :   List[Any]   				=      '''Running gcloud compute tpus tpu-vm ssh'''
					def 			lowerCamelCase__(				self       :Optional[Any]				) ->   Tuple:
												a__					=					run_command(
												    self.cmd
												    + ['--command', self.command, '--tpu_zone', self.tpu_zone, '--tpu_name', self.tpu_name, '--debug']      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :int				) ->   str:
												a__					=					run_command(
												    self.cmd
												    + [
												        '--config_file',
												        'tests/test_configs/0_12_0.yaml',
												        '--command',
												        self.command,
												        '--tpu_zone',
												        self.tpu_zone,
												        '--tpu_name',
												        self.tpu_name,
												        '--debug',
												    ]      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :Any				) ->   Dict:
												a__					=					run_command(
												    self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--debug']      ,return_stdout=__snake_case				)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo "hello world"; echo "this is a second command" --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :Tuple				) ->   str:
												a__					=					run_command(
												    self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--command', self.command, '--debug']      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :Dict				) ->   int:
												a__					=					run_command(
												    self.cmd
												    + [
												        '--config_file',
												        'tests/test_configs/latest.yaml',
												        '--command',
												        self.command,
												        '--command',
												        'echo "Hello World"',
												        '--debug',
												    ]      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls; echo "Hello World" --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :Union[str, Any]				) ->   List[Any]:
												a__					=					run_command(
												    self.cmd
												    + ['--config_file', 'tests/test_configs/latest.yaml', '--command_file', self.command_file, '--debug']      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo "hello world"; echo "this is a second command" --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :int				) ->   int:
												a__					=					run_command(
												    self.cmd
												    + [
												        '--config_file',
												        'tests/test_configs/0_12_0.yaml',
												        '--command_file',
												        self.command_file,
												        '--tpu_zone',
												        self.tpu_zone,
												        '--tpu_name',
												        self.tpu_name,
												        '--debug',
												    ]      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo "hello world"; echo "this is a second command" --worker all'      ,__snake_case      ,)
					def 			lowerCamelCase__(				self       :Union[str, Any]				) ->   List[Any]:
												a__					=					run_command(
												    self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--install_accelerate', '--debug']      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate -U; echo "hello world"; echo "this is a second command" --worker all'      ,__snake_case      ,)



					def 			lowerCamelCase__(				self       :Any				) ->   Optional[int]:
												a__					=					run_command(
												    self.cmd
												    + [
												        '--config_file',
												        'tests/test_configs/latest.yaml',
												        '--install_accelerate',
												        '--accelerate_version',
												        '12.0.0',
												        '--debug',
												    ]      ,return_stdout=__snake_case      ,)
												self.assertIn(
												    F'{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate==12.0.0; echo "hello world"; echo "this is a second command" --worker all'      ,__snake_case      ,)




