



'''simple docstring'''



import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin





@skip_mps
class _UpperCamelCase		(     A      ,       A      ,       unittest.TestCase		):





    '''simple docstring'''





    lowerCAmelCase__					    =    IFInpaintingPipeline
    lowerCAmelCase__					    =    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
    lowerCAmelCase__					    =    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
    lowerCAmelCase__					    =    PipelineTesterMixin.required_optional_params - {"""latents"""}

    def 				__lowerCamelCase     (							self  :  Optional[Any]):







           '''simple docstring'''

           return self._get_dummy_components()

    def 				__lowerCamelCase     (							self  :  Union[str, Any]  ,       _lowerCAmelCase  :  List[str]  ,       _lowerCAmelCase  :  Optional[Any]=0):







           '''simple docstring'''

           if str(_lowerCAmelCase).startswith('mps'):
                  __lowercase       	=torch.manual_seed(_lowerCAmelCase)
           else:
                  __lowercase       	=torch.Generator(device=_lowerCAmelCase).manual_seed(_lowerCAmelCase)

           __lowercase       	=floats_tensor((1, 3, 3_2, 3_2)  ,       rng=random.Random(_lowerCAmelCase)).to(_lowerCAmelCase)
           __lowercase       	=floats_tensor((1, 3, 3_2, 3_2)  ,       rng=random.Random(_lowerCAmelCase)).to(_lowerCAmelCase)

           __lowercase       	={
               'prompt': 'A painting of a squirrel eating a burger',
               'image': image,
               'mask_image': mask_image,
               'generator': generator,
               'num_inference_steps': 2,
               'output_type': 'numpy',
           }

           return inputs

    @unittest.skipIf(
        torch_device != 'cuda' or not is_xformers_available()  ,       reason='XFormers attention is only available with CUDA and `xformers` installed'  ,       )
    def 				__lowerCamelCase     (							self  :  List[str]):







           '''simple docstring'''

           self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3)

    def 				__lowerCamelCase     (							self  :  List[str]):







           '''simple docstring'''

           self._test_save_load_optional_components()

    @unittest.skipIf(torch_device != 'cuda'  ,       reason='float16 requires CUDA')
    def 				__lowerCamelCase     (							self  :  int):







           '''simple docstring'''

           super().test_save_load_floataa(expected_max_diff=1e-1)

    def 				__lowerCamelCase     (							self  :  int):







           '''simple docstring'''

           self._test_attention_slicing_forward_pass(expected_max_diff=1e-2)

    def 				__lowerCamelCase     (							self  :  Any):







           '''simple docstring'''

           self._test_save_load_local()

    def 				__lowerCamelCase     (							self  :  Optional[Any]):







           '''simple docstring'''

           self._test_inference_batch_single_identical(
               expected_max_diff=1e-2  ,       )








'''simple docstring'''



# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


lowerCamelCase	 =       """Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine"""



def   _A       (   ):



							"""simple docstring"""



							__lowercase       	=_ask_options(
							    'In which compute environment are you running?'  ,   ['This machine', 'AWS (Amazon SageMaker)']  ,   _convert_compute_environment  ,   )
							if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
														__lowercase       	=get_sagemaker_input()
							else:
														__lowercase       	=get_cluster_input()
							return config



def   _A       (   _lowerCAmelCase=None					):



							"""simple docstring"""



							if subparsers is not None:
														__lowercase       	=subparsers.add_parser('config'  ,   description=_lowerCAmelCase					)
							else:
														__lowercase       	=argparse.ArgumentParser('Accelerate config command'  ,   description=_lowerCAmelCase					)

							parser.add_argument(
							    '--config_file'  ,   default=_lowerCAmelCase  ,   help=(
							        'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
							        'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
							        'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
							        'with \'huggingface\'.'
							    )  ,   )

							if subparsers is not None:
														parser.set_defaults(func=_lowerCAmelCase					)
							return parser



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=get_user_input()
							if args.config_file is not None:
														__lowercase       	=args.config_file
							else:
														if not os.path.isdir(_lowerCAmelCase					):
																					os.makedirs(_lowerCAmelCase					)
														__lowercase       	=default_yaml_config_file

							if config_file.endswith('.json'					):
														config.to_json_file(_lowerCAmelCase					)
							else:
														config.to_yaml_file(_lowerCAmelCase					)
							print(f"""accelerate configuration saved at {config_file}"""					)



def   _A       (   ):



							"""simple docstring"""



							__lowercase       	=config_command_parser()
							__lowercase       	=parser.parse_args()
							config_command(_lowerCAmelCase					)


if __name__ == "__main__":
		main()



