


"""simple docstring"""
import re
import tempfile
from pathlib import Path

import pytest
import yaml

from datasets.utils.readme import ReadMe


# @pytest.fixture
# def example_yaml_structure():

__SCREAMING_SNAKE_CASE							:			Any						=			yaml.safe_load(
    '\\nname: ""\nallow_empty: false\nallow_empty_text: true\nsubsections:\n  - name: "Dataset Card for X" # First-level markdown heading\n    allow_empty: false\n    allow_empty_text: true\n    subsections:\n      - name: "Table of Contents"\n        allow_empty: false\n        allow_empty_text: false\n        subsections: null\n      - name: "Dataset Description"\n        allow_empty: false\n        allow_empty_text: false\n        subsections:\n          - name: "Dataset Summary"\n            allow_empty: false\n            allow_empty_text: false\n            subsections: null\n          - name: "Supported Tasks and Leaderboards"\n            allow_empty: true\n            allow_empty_text: true\n            subsections: null\n          - name: Languages\n            allow_empty: false\n            allow_empty_text: true\n            subsections: null\n'
)


__SCREAMING_SNAKE_CASE							:			Tuple						=			{
    'name': 'root',
    'text': '',
    'is_empty_text': True,
    'subsections': [
        {
            'name': 'Dataset Card for My Dataset',
            'text': '',
            'is_empty_text': True,
            'subsections': [
                {'name': 'Table of Contents', 'text': 'Some text here.', 'is_empty_text': False, 'subsections': []},
                {
                    'name': 'Dataset Description',
                    'text': 'Some text here.',
                    'is_empty_text': False,
                    'subsections': [
                        {
                            'name': 'Dataset Summary',
                            'text': 'Some text here.',
                            'is_empty_text': False,
                            'subsections': [],
                        },
                        {
                            'name': 'Supported Tasks and Leaderboards',
                            'text': '',
                            'is_empty_text': True,
                            'subsections': [],
                        },
                        {'name': 'Languages', 'text': 'Language Text', 'is_empty_text': False, 'subsections': []},
                    ],
                },
            ],
        }
    ],
}


__SCREAMING_SNAKE_CASE							:			Union[str, Any]						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'


__SCREAMING_SNAKE_CASE							:			Optional[int]						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n#### Extra Ignored Subsection\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			List[Any]						=			{
    'name': 'root',
    'text': '',
    'is_empty_text': True,
    'subsections': [
        {
            'name': 'Dataset Card for My Dataset',
            'text': '',
            'is_empty_text': True,
            'subsections': [
                {'name': 'Table of Contents', 'text': 'Some text here.', 'is_empty_text': False, 'subsections': []},
                {
                    'name': 'Dataset Description',
                    'text': 'Some text here.',
                    'is_empty_text': False,
                    'subsections': [
                        {
                            'name': 'Dataset Summary',
                            'text': 'Some text here.',
                            'is_empty_text': False,
                            'subsections': [
                                {
                                    'name': 'Extra Ignored Subsection',
                                    'text': '',
                                    'is_empty_text': True,
                                    'subsections': [],
                                }
                            ],
                        },
                        {
                            'name': 'Supported Tasks and Leaderboards',
                            'text': '',
                            'is_empty_text': True,
                            'subsections': [],
                        },
                        {'name': 'Languages', 'text': 'Language Text', 'is_empty_text': False, 'subsections': []},
                    ],
                },
            ],
        }
    ],
}

__SCREAMING_SNAKE_CASE							:			Optional[Any]						=			'\\n---\n---\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			Optional[Any]						=			(
    'The following issues were found for the README at `{path}`:\n-\tEmpty YAML markers are present in the README.'
)

__SCREAMING_SNAKE_CASE							:			Optional[int]						=			'\\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			int						=			(
    'The following issues were found for the README at `{path}`:\n-\tNo YAML markers are present in the README.'
)

__SCREAMING_SNAKE_CASE							:			int						=			'\\n---\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			Any						=			'The following issues were found for the README at `{path}`:\n-\tOnly the start of YAML tags present in the README.'

__SCREAMING_SNAKE_CASE							:			List[str]						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'
__SCREAMING_SNAKE_CASE							:			int						=			'The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Dataset Summary` but it is empty.\n-\tExpected some text in section `Dataset Summary` but it is empty (text in subsections are ignored).'


__SCREAMING_SNAKE_CASE							:			int						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n'
__SCREAMING_SNAKE_CASE							:			str						=			'The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Dataset Card for My Dataset` but it is empty.\n-\tSection `Dataset Card for My Dataset` expected the following subsections: `Table of Contents`, `Dataset Description`. Found \'None\'.'

__SCREAMING_SNAKE_CASE							:			str						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			List[str]						=			'The following issues were found for the README at `{path}`:\n-\tSection `Dataset Description` is missing subsection: `Supported Tasks and Leaderboards`.'


__SCREAMING_SNAKE_CASE							:			int						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\n'

__SCREAMING_SNAKE_CASE							:			Tuple						=			'The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Languages` but it is empty.'

__SCREAMING_SNAKE_CASE							:			str						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'
__SCREAMING_SNAKE_CASE							:			str						=			'The following issues were found for the README at `{path}`:\n-\tThe README has no first-level headings. One heading is expected. Skipping further validation for this README.'

__SCREAMING_SNAKE_CASE							:			List[Any]						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n# Dataset Card My Dataset\n'

__SCREAMING_SNAKE_CASE							:			int						=			'The following issues were found for the README at `{path}`:\n-\tThe README has several first-level headings: `Dataset Card for My Dataset`, `Dataset Card My Dataset`. Only one heading is expected. Skipping further validation for this README.'

__SCREAMING_SNAKE_CASE							:			List[str]						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			str						=			'The following issues were found for the README at `{path}`:\n-\tNo first-level heading starting with `Dataset Card for` found in README. Skipping further validation for this README.'

__SCREAMING_SNAKE_CASE							:			Dict						=			''

__SCREAMING_SNAKE_CASE							:			int						=			'The following issues were found for the README at `{path}`:\n-\tThe README has no first-level headings. One heading is expected. Skipping further validation for this README.\n-\tNo YAML markers are present in the README.'

__SCREAMING_SNAKE_CASE							:			str						=			'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

__SCREAMING_SNAKE_CASE							:			str						=			'The following issues were found while parsing the README at `{path}`:\n-\tMultiple sections with the same heading `Dataset Card for My Dataset` have been found. Please keep only one of these sections.'







@pytest.mark.parametrize(
    """readme_md, expected_dict""" ,       [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE )			-> List[Any]:
							assert ReadMe.from_string(A__ ,       A__ ).to_dict() == expected_dict







@pytest.mark.parametrize(
    """readme_md, expected_error""" ,       [
        (README_NO_YAML, EXPECTED_ERROR_README_NO_YAML),
        (README_EMPTY_YAML, EXPECTED_ERROR_README_EMPTY_YAML),
        (README_INCORRECT_YAML, EXPECTED_ERROR_README_INCORRECT_YAML),
        (README_EMPTY, EXPECTED_ERROR_README_EMPTY),
        (README_NONE_SUBSECTION, EXPECTED_ERROR_README_NONE_SUBSECTION),
        (README_MISSING_FIRST_LEVEL, EXPECTED_ERROR_README_MISSING_FIRST_LEVEL),
        (README_MISSING_SUBSECTION, EXPECTED_ERROR_README_MISSING_SUBSECTION),
        (README_MISSING_TEXT, EXPECTED_ERROR_README_MISSING_TEXT),
        (README_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_WRONG_FIRST_LEVEL),
        (README_MULTIPLE_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_MULTIPLE_WRONG_FIRST_LEVEL),
        (README_MISSING_CONTENT, EXPECTED_ERROR_README_MISSING_CONTENT),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE )			-> Tuple:



							with pytest.raises(A__ ,       match=re.escape(expected_error.format(path="""root""" ) ) ):
														snake_case_							=						ReadMe.from_string(A__ ,       A__ )
														readme.validate()







@pytest.mark.parametrize(
    """readme_md, expected_error""" ,       [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE )			-> Optional[Any]:



							with pytest.raises(A__ ,       match=re.escape(expected_error.format(path="""root""" ) ) ):
														ReadMe.from_string(A__ ,       A__ )







@pytest.mark.parametrize(
    """readme_md,""" ,       [
        (README_MULTIPLE_SAME_HEADING_1),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE )			-> Union[str, Any]:
							ReadMe.from_string(A__ ,       A__ ,       suppress_parsing_errors=A__ )







@pytest.mark.parametrize(
    """readme_md, expected_dict""" ,       [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE )			-> Optional[int]:



							with tempfile.TemporaryDirectory() as tmp_dir:
														snake_case_							=						Path(A__ ) / """README.md"""
														with open(A__ ,       """w+""" ) as readme_file:
																					readme_file.write(A__ )
														snake_case_							=						ReadMe.from_readme(A__ ,       A__ ).to_dict()
														assert out["name"] == path
														assert out["text"] == ""
														assert out["is_empty_text"]
														assert out["subsections"] == expected_dict["subsections"]







@pytest.mark.parametrize(
    """readme_md, expected_error""" ,       [
        (README_NO_YAML, EXPECTED_ERROR_README_NO_YAML),
        (README_EMPTY_YAML, EXPECTED_ERROR_README_EMPTY_YAML),
        (README_INCORRECT_YAML, EXPECTED_ERROR_README_INCORRECT_YAML),
        (README_EMPTY, EXPECTED_ERROR_README_EMPTY),
        (README_NONE_SUBSECTION, EXPECTED_ERROR_README_NONE_SUBSECTION),
        (README_MISSING_FIRST_LEVEL, EXPECTED_ERROR_README_MISSING_FIRST_LEVEL),
        (README_MISSING_SUBSECTION, EXPECTED_ERROR_README_MISSING_SUBSECTION),
        (README_MISSING_TEXT, EXPECTED_ERROR_README_MISSING_TEXT),
        (README_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_WRONG_FIRST_LEVEL),
        (README_MULTIPLE_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_MULTIPLE_WRONG_FIRST_LEVEL),
        (README_MISSING_CONTENT, EXPECTED_ERROR_README_MISSING_CONTENT),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE )			-> List[str]:



							with tempfile.TemporaryDirectory() as tmp_dir:
														snake_case_							=						Path(A__ ) / """README.md"""
														with open(A__ ,       """w+""" ) as readme_file:
																					readme_file.write(A__ )
														snake_case_							=						expected_error.format(path=A__ )
														with pytest.raises(A__ ,       match=re.escape(A__ ) ):
																					snake_case_							=						ReadMe.from_readme(A__ ,       A__ )
																					readme.validate()







@pytest.mark.parametrize(
    """readme_md, expected_error""" ,       [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE )			-> List[Any]:



							with tempfile.TemporaryDirectory() as tmp_dir:
														snake_case_							=						Path(A__ ) / """README.md"""
														with open(A__ ,       """w+""" ) as readme_file:
																					readme_file.write(A__ )
														snake_case_							=						expected_error.format(path=A__ )
														with pytest.raises(A__ ,       match=re.escape(A__ ) ):
																					ReadMe.from_readme(A__ ,       A__ )







@pytest.mark.parametrize(
    """readme_md,""" ,       [
        (README_MULTIPLE_SAME_HEADING_1),
    ] ,       )
def   _a (					_SCREAMING_SNAKE_CASE )			-> int:



							with tempfile.TemporaryDirectory() as tmp_dir:
														snake_case_							=						Path(A__ ) / """README.md"""
														with open(A__ ,       """w+""" ) as readme_file:
																					readme_file.write(A__ )
														ReadMe.from_readme(A__ ,       A__ ,       suppress_parsing_errors=A__ )






'''simple docstring'''






import argparse
from pathlib import Path

import torch
from packaging import version
from torch.onnx import export

from diffusers import AutoencoderKL


lowerCAmelCase__											=	version.parse(version.parse(torch.__version__).base_version) < version.parse('''1.11''')


def 		_A     (    A__     ,				A__     ,				A__     ,				A__     ,				A__     ,				A__     ,				A__     ,				A__=False     ,				):






 """simple docstring"""



 output_path.parent.mkdir(parents=A__     ,				exist_ok=A__      )
 # PyTorch deprecated the `enable_onnx_checker` and `use_external_data_format` arguments in v1.11,
 # so we check the torch version for backwards compatibility
 if is_torch_less_than_1_11:
  export(
      A__     ,				A__     ,				f=output_path.as_posix()     ,				input_names=A__     ,				output_names=A__     ,				dynamic_axes=A__     ,				do_constant_folding=A__     ,				use_external_data_format=A__     ,				enable_onnx_checker=A__     ,				opset_version=A__     ,				)
 else:
  export(
      A__     ,				A__     ,				f=output_path.as_posix()     ,				input_names=A__     ,				output_names=A__     ,				dynamic_axes=A__     ,				do_constant_folding=A__     ,				opset_version=A__     ,				)


@torch.no_grad()
def 		_A     (    A__     ,				A__     ,				A__     ,				A__ = False      ):






 """simple docstring"""



 __lowercase							  = torch.floataa if fpaa else torch.floataa
 if fpaa and torch.cuda.is_available():
  __lowercase							  = '''cuda'''
 elif fpaa and not torch.cuda.is_available():
  raise ValueError('''`float16` model export is only supported on GPUs with CUDA'''      )
 else:
  __lowercase							  = '''cpu'''
 __lowercase							  = Path(A__      )

 # VAE DECODER
 __lowercase							  = AutoencoderKL.from_pretrained(model_path + '''/vae'''      )
 __lowercase							  = vae_decoder.config.latent_channels
 # forward only through the decoder part
 __lowercase							  = vae_decoder.decode
 onnx_export(
     A__     ,				model_args=(
         torch.randn(1     ,				A__     ,				25     ,				25      ).to(device=A__     ,				dtype=A__      ),
         False,
     )     ,				output_path=output_path / '''vae_decoder''' / '''model.onnx'''     ,				ordered_input_names=['''latent_sample''', '''return_dict''']     ,				output_names=['''sample''']     ,				dynamic_axes={
         '''latent_sample''': {0: '''batch''', 1: '''channels''', 2: '''height''', 3: '''width'''},
     }     ,				opset=A__     ,				)
 del vae_decoder


if __name__ == "__main__":
 lowerCAmelCase__											=	argparse.ArgumentParser()

 parser.add_argument(
     '''--model_path''',
     type=str,
     required=True,
     help='''Path to the `diffusers` checkpoint to convert (either a local directory or on the Hub).''',
 )

 parser.add_argument('''--output_path''', type=str, required=True, help='''Path to the output model.''')
 parser.add_argument(
     '''--opset''',
     default=14,
     type=int,
     help='''The version of the ONNX operator set to use.''',
 )
 parser.add_argument('''--fp16''', action='''store_true''', default=False, help='''Export the models in `float16` mode''')

 lowerCAmelCase__											=	parser.parse_args()
 print(args.output_path)
 convert_models(args.model_path, args.output_path, args.opset, args.fpaa)
 print('''SD: Done: ONNX''')

