



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 		_lowercase		(       unittest.TestCase	):
   _UpperCAmelCase     	=			inspect.getfile(accelerate.test_utils	)
   _UpperCAmelCase     	=			os.path.sep.join(mod_file.split(os.path.sep	)[:-1] + ['''scripts''', '''test_cli.py''']	)

   _UpperCAmelCase     	=			['''accelerate''', '''launch''']
   _UpperCAmelCase     	=			Path.home() / '''.cache/huggingface/accelerate'''
   _UpperCAmelCase     	=			'''default_config.yaml'''
   _UpperCAmelCase     	=			config_folder / config_file
   _UpperCAmelCase     	=			config_folder / '''_default_config.yaml'''

   _UpperCAmelCase     	=			Path('''tests/test_configs'''	)

   @classmethod
   def 		A							(      cls			:       str							)       ->				List[Any]:


    """simple docstring"""






    if cls.config_path.is_file():
     cls.config_path.rename(cls.changed_path							)

   @classmethod
   def 		A							(      cls			:       Union[str, Any]							)       ->				Any:


    """simple docstring"""






    if cls.changed_path.is_file():
     cls.changed_path.rename(cls.config_path							)

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


    """simple docstring"""






    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 		A							(      self			:       int							)       ->				List[Any]:


    """simple docstring"""






    for config in sorted(self.test_config_path.glob("**/*.yaml"							)							):
     with self.subTest(config_file=__lowerCAmelCase							):
      execute_subprocess_async(
          self.base_cmd + ["--config_file", str(__lowerCAmelCase							), self.test_file_path]							,   env=os.environ.copy()							)




   def 		A							(      self			:       List[Any]							)       ->				Tuple:


    """simple docstring"""






    execute_subprocess_async(["accelerate", "test"]							,   env=os.environ.copy()							)



class 		_lowercase		(       unittest.TestCase	):
   _UpperCAmelCase     	=			'''test-tpu'''
   _UpperCAmelCase     	=			'''us-central1-a'''
   _UpperCAmelCase     	=			'''ls'''
   _UpperCAmelCase     	=			['''accelerate''', '''tpu-config''']
   _UpperCAmelCase     	=			'''cd /usr/share'''
   _UpperCAmelCase     	=			'''tests/test_samples/test_command_file.sh'''
   _UpperCAmelCase     	=			'''Running gcloud compute tpus tpu-vm ssh'''

   def 		A							(      self			:       int							)       ->				List[Any]:


    """simple docstring"""






    a						=		run_command(
        self.cmd
        + ["--command", self.command, "--tpu_zone", self.tpu_zone, "--tpu_name", self.tpu_name, "--debug"]							,   return_stdout=__lowerCAmelCase							,   )
    self.assertIn(
        f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""							,   __lowerCAmelCase							,   )

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


    """simple docstring"""






    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=__lowerCAmelCase							,   )
    self.assertIn(
        f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""							,   __lowerCAmelCase							,   )

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


    """simple docstring"""






    a						=		run_command(
        self.cmd + ["--config_file", "tests/test_configs/latest.yaml", "--debug"]							,   return_stdout=__lowerCAmelCase							)
    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"""							,   __lowerCAmelCase							,   )

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


    """simple docstring"""






    a						=		run_command(
        self.cmd + ["--config_file", "tests/test_configs/latest.yaml", "--command", self.command, "--debug"]							,   return_stdout=__lowerCAmelCase							,   )
    self.assertIn(
        f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""							,   __lowerCAmelCase							,   )

   def 		A							(      self			:       Optional[int]							)       ->				List[Any]:


    """simple docstring"""






    a						=		run_command(
        self.cmd
        + [
            "--config_file",
            "tests/test_configs/latest.yaml",
            "--command",
            self.command,
            "--command",
            "echo \"Hello World\"",
            "--debug",
        ]							,   return_stdout=__lowerCAmelCase							,   )
    self.assertIn(
        f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls; echo \"Hello World\" --worker all"""							,   __lowerCAmelCase							,   )

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


    """simple docstring"""






    a						=		run_command(
        self.cmd
        + ["--config_file", "tests/test_configs/latest.yaml", "--command_file", self.command_file, "--debug"]							,   return_stdout=__lowerCAmelCase							,   )
    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"""							,   __lowerCAmelCase							,   )

   def 		A							(      self			:       Optional[Any]							)       ->				Optional[Any]:


    """simple docstring"""






    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=__lowerCAmelCase							,   )
    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"""							,   __lowerCAmelCase							,   )

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


    """simple docstring"""






    a						=		run_command(
        self.cmd + ["--config_file", "tests/test_configs/latest.yaml", "--install_accelerate", "--debug"]							,   return_stdout=__lowerCAmelCase							,   )
    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"""							,   __lowerCAmelCase							,   )




   def 		A							(      self			:       Optional[Any]							)       ->				Optional[int]:


    """simple docstring"""






    a						=		run_command(
        self.cmd
        + [
            "--config_file",
            "tests/test_configs/latest.yaml",
            "--install_accelerate",
            "--accelerate_version",
            "12.0.0",
            "--debug",
        ]							,   return_stdout=__lowerCAmelCase							,   )
    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"""							,   __lowerCAmelCase							,   )






from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput



class 		_lowercase		(       UpperCAmelCase__	):
   _UpperCAmelCase     	=			42
   _UpperCAmelCase     	=			42

   def __init__(      self			:       Optional[Any]							,   __lowerCAmelCase			:       UNetaDModel							,   __lowerCAmelCase			:       ScoreSdeVeScheduler							)       ->				str:


    """simple docstring"""






    super().__init__()
    self.register_modules(unet=__lowerCAmelCase							,   scheduler=__lowerCAmelCase							)




   @torch.no_grad()
   def __call__(      self			:       int							,   __lowerCAmelCase			:       int = 1							,   __lowerCAmelCase			:       int = 2000							,   __lowerCAmelCase			:       Optional[Union[torch.Generator, List[torch.Generator]]] = None							,   __lowerCAmelCase			:       Optional[str] = "pil"							,   __lowerCAmelCase			:       bool = True							,   **__lowerCAmelCase			:       Any							,   )       ->				Union[ImagePipelineOutput, Tuple]:


    """simple docstring"""






    a						=		self.unet.config.sample_size
    a						=		(batch_size, 3, img_size, img_size)

    a						=		self.unet

    a						=		randn_tensor(__lowerCAmelCase							,   generator=__lowerCAmelCase							) * self.scheduler.init_noise_sigma
    a						=		sample.to(self.device							)

    self.scheduler.set_timesteps(__lowerCAmelCase							)
    self.scheduler.set_sigmas(__lowerCAmelCase							)

    for i, t in enumerate(self.progress_bar(self.scheduler.timesteps							)							):
     a						=		self.scheduler.sigmas[i] * torch.ones(shape[0]							,   device=self.device							)

     # correction step
     for _ in range(self.scheduler.config.correct_steps							):
      a						=		self.unet(__lowerCAmelCase							,   __lowerCAmelCase							).sample
      a						=		self.scheduler.step_correct(__lowerCAmelCase							,   __lowerCAmelCase							,   generator=__lowerCAmelCase							).prev_sample

     # prediction step
     a						=		model(__lowerCAmelCase							,   __lowerCAmelCase							).sample
     a						=		self.scheduler.step_pred(__lowerCAmelCase							,   __lowerCAmelCase							,   __lowerCAmelCase							,   generator=__lowerCAmelCase							)

     a		,  a						=		output.prev_sample, output.prev_sample_mean

    a						=		sample_mean.clamp(0							,   1							)
    a						=		sample.cpu().permute(0							,   2							,   3							,   1							).numpy()
    if output_type == "pil":
     a						=		self.numpy_to_pil(__lowerCAmelCase							)

    if not return_dict:
     return (sample,)

    return ImagePipelineOutput(images=__lowerCAmelCase							)

