"""simple docstring"""




import argparse
import os
import re

import packaging.version


__lowerCamelCase											=  "examples/"
__lowerCamelCase											=  {
    "examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
    "init": (re.compile(R"^__version__\s+=\s+\"([^\"]+)\"\s*$", re.MULTILINE), "__version__ = \"VERSION\"\n"),
    "setup": (re.compile(R"^(\s*)version\s*=\s*\"[^\"]+\",", re.MULTILINE), R"\1version=\"VERSION\","),
    "doc": (re.compile(R"^(\s*)release\s*=\s*\"[^\"]+\"$", re.MULTILINE), "release = \"VERSION\"\n"),
}
__lowerCamelCase											=  {
    "init": "src/transformers/__init__.py",
    "setup": "setup.py",
}
__lowerCamelCase											=  "README.md"






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							with open(UpperCamelCase__       ,    'r'       ,    encoding='utf-8'       ,    newline='\n'				) as f:
														A__	     =							f.read()
							A__     ,  A__	     =							REPLACE_PATTERNS[pattern]
							A__	     =							replace.replace('VERSION'       ,    UpperCamelCase__				)
							A__	     =							re_pattern.sub(UpperCamelCase__       ,    UpperCamelCase__				)
							with open(UpperCamelCase__       ,    'w'       ,    encoding='utf-8'       ,    newline='\n'				) as f:
														f.write(UpperCamelCase__				)






def   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							for folder, directories, fnames in os.walk(UpperCamelCase__				):
														# Removing some of the folders with non-actively maintained examples from the walk
														if "research_projects" in directories:
																					directories.remove('research_projects'				)
														if "legacy" in directories:
																					directories.remove('legacy'				)
														for fname in fnames:
																					if fname.endswith('.py'				):
																												update_version_in_file(os.path.join(UpperCamelCase__       ,    UpperCamelCase__				)       ,    UpperCamelCase__       ,    pattern='examples'				)






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__=False				):






							"""simple docstring"""





							for pattern, fname in REPLACE_FILES.items():
														update_version_in_file(UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				)
							if not patch:
														update_version_in_examples(UpperCamelCase__				)






def   UpperCAmelCase					(	):






							"""simple docstring"""





							A__	     =							'🤗 Transformers currently provides the following architectures'
							A__	     =							'1. Want to contribute a new model?'
							with open(UpperCamelCase__       ,    'r'       ,    encoding='utf-8'       ,    newline='\n'				) as f:
														A__	     =							f.readlines()

							# Find the start of the list.
							A__	     =							0
							while not lines[start_index].startswith(_start_prompt				):
														start_index += 1
							start_index += 1

							A__	     =							start_index
							# Update the lines in the model list.
							while not lines[index].startswith(_end_prompt				):
														if lines[index].startswith('1.'				):
																					A__	     =							lines[index].replace(
																					    'https://huggingface.co/docs/transformers/main/model_doc'       ,    'https://huggingface.co/docs/transformers/model_doc'       ,    )
														index += 1

							with open(UpperCamelCase__       ,    'w'       ,    encoding='utf-8'       ,    newline='\n'				) as f:
														f.writelines(UpperCamelCase__				)






def   UpperCAmelCase					(	):






							"""simple docstring"""





							with open(REPLACE_FILES['init']       ,    'r'				) as f:
														A__	     =							f.read()
							A__	     =							REPLACE_PATTERNS['init'][0].search(UpperCamelCase__				).groups()[0]
							return packaging.version.parse(UpperCamelCase__				)






def   UpperCAmelCase					(	UpperCamelCase__=False				):






							"""simple docstring"""





							A__	     =							get_version()
							if patch and default_version.is_devrelease:
														raise ValueError('Can\'t create a patch version from the dev branch, checkout a released version!'				)
							if default_version.is_devrelease:
														A__	     =							default_version.base_version
							elif patch:
														A__	     =							F'''{default_version.major}.{default_version.minor}.{default_version.micro + 1}'''
							else:
														A__	     =							F'''{default_version.major}.{default_version.minor + 1}.0'''

							# Now let's ask nicely if that's the right one.
							A__	     =							input(F'''Which version are you releasing? [{default_version}]'''				)
							if len(UpperCamelCase__				) == 0:
														A__	     =							default_version

							print(F'''Updating version to {version}.'''				)
							global_version_update(UpperCamelCase__       ,    patch=UpperCamelCase__				)
							if not patch:
														print('Cleaning main README, don\'t forget to run `make fix-copies`.'				)
														clean_main_ref_in_model_list()






def   UpperCAmelCase					(	):






							"""simple docstring"""





							A__	     =							get_version()
							A__	     =							F'''{current_version.major}.{current_version.minor + 1}.0.dev0'''
							A__	     =							current_version.base_version

							# Check with the user we got that right.
							A__	     =							input(F'''Which version are we developing now? [{dev_version}]'''				)
							if len(UpperCamelCase__				) == 0:
														A__	     =							dev_version

							print(F'''Updating version to {version}.'''				)
							global_version_update(UpperCamelCase__				)
							print('Cleaning main README, don\'t forget to run `make fix-copies`.'				)
							clean_main_ref_in_model_list()


if __name__ == "__main__":
				__lowerCamelCase											=  argparse.ArgumentParser()
				parser.add_argument("--post_release", action="store_true", help="Whether this is pre or post release.")
				parser.add_argument("--patch", action="store_true", help="Whether or not this is a patch release.")
				__lowerCamelCase											=  parser.parse_args()
				if not args.post_release:
								pre_release_work(patch=args.patch)
				elif args.patch:
								print("Nothing to do after a patch :-)")
				else:
								post_release_work()






"""simple docstring"""




import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
				import onnxruntime as ort
@nightly
@require_onnxruntime
@require_torch_gpu
class     UpperCamelCase__(			unittest.TestCase ):





						@property
						def 				snake_case__	(       self     )					->				int:
													return (
													    "CUDAExecutionProvider",
													    {
													        "gpu_mem_limit": "15000000000",  # 15GB
													        "arena_extend_strategy": "kSameAsRequested",
													    },
													)





						@property
						def 				snake_case__	(       self     )					->				Union[str, Any]:
													A__	     =							ort.SessionOptions()
													A__	     =							False
													return options





						def 				snake_case__	(       self     )					->				str:
													A__	     =							load_image(
													    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
													    '/in_paint/overture-creations-5sI6fQgYIuo.png'     )
													A__	     =							load_image(
													    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
													    '/in_paint/overture-creations-5sI6fQgYIuo_mask.png'     )
													A__	     =							load_numpy(
													    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
													    '/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy'     )

													# using the PNDM scheduler by default
													A__	     =							OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
													    'CompVis/stable-diffusion-v1-4'		,revision='onnx'		,safety_checker=__UpperCAmelCase		,feature_extractor=__UpperCAmelCase		,provider=self.gpu_provider		,sess_options=self.gpu_options		,)
													pipe.set_progress_bar_config(disable=__UpperCAmelCase     )

													A__	     =							'A red cat sitting on a park bench'

													A__	     =							np.random.RandomState(0     )
													A__	     =							pipe(
													    prompt=__UpperCAmelCase		,image=__UpperCAmelCase		,mask_image=__UpperCAmelCase		,strength=0.7_5		,guidance_scale=7.5		,num_inference_steps=15		,generator=__UpperCAmelCase		,output_type='np'		,)

													A__	     =							output.images[0]

													assert image.shape == (5_12, 5_12, 3)
													assert np.abs(expected_image - image     ).max() < 1e-2





