

import re
import tempfile
from pathlib import Path

import pytest
import yaml

from datasets.utils.readme import ReadMe


# @pytest.fixture
# def example_yaml_structure():

A											=     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'
)


A											=     {
    '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': []},
                    ],
                },
            ],
        }
    ],
}


A											=     '\\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'


A											=     '\\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'

A											=     {
    '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': []},
                    ],
                },
            ],
        }
    ],
}

A											=     '\\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'

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

A											=     '\\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'

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

A											=     '\\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'

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

A											=     '\\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'
A											=     '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).'


A											=     '\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n'
A											=     '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\'.'

A											=     '\\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'

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


A											=     '\\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'

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

A											=     '\\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'
A											=     '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.'

A											=     '\\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'

A											=     '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.'

A											=     '\\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'

A											=     '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.'

A											=     ''

A											=     '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.'

A											=     '\\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'

A											=     '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(lowercase__			, lowercase__	):





	'''simple docstring'''
	assert ReadMe.from_string(lowercase__			, lowercase__	).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(lowercase__			, lowercase__	):





	'''simple docstring'''
	with pytest.raises(lowercase__			, match=re.escape(expected_error.format(path='root'	)	)	):
		snake_case_      		= ReadMe.from_string(lowercase__			, lowercase__	)
		readme.validate()





@pytest.mark.parametrize(
    'readme_md, expected_error'			, [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]			, )
def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	with pytest.raises(lowercase__			, match=re.escape(expected_error.format(path='root'	)	)	):
		ReadMe.from_string(lowercase__			, lowercase__	)





@pytest.mark.parametrize(
    'readme_md,'			, [
        (README_MULTIPLE_SAME_HEADING_1),
    ]			, )
def a(lowercase__	):





	'''simple docstring'''
	ReadMe.from_string(lowercase__			, lowercase__			, suppress_parsing_errors=lowercase__	)





@pytest.mark.parametrize(
    'readme_md, expected_dict'			, [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ]			, )
def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	with tempfile.TemporaryDirectory() as tmp_dir:
		snake_case_      		= Path(lowercase__	) / 'README.md'
		with open(lowercase__			, 'w+'	) as readme_file:
			readme_file.write(lowercase__	)
		snake_case_      		= ReadMe.from_readme(lowercase__			, lowercase__	).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(lowercase__			, lowercase__	):





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





@pytest.mark.parametrize(
    'readme_md, expected_error'			, [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]			, )
def a(lowercase__			, lowercase__	):





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






@pytest.mark.parametrize(
    'readme_md,'			, [
        (README_MULTIPLE_SAME_HEADING_1),
    ]			, )
def a(lowercase__	):





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



import unittest

import numpy as np
import torch

from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()


class SCREAMING_SNAKE_CASE  (		unittest.TestCase							):






			"""simple docstring"""




			@property
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				torch.manual_seed(0							)
				snake_case_      		= UNetaDModel(
				    block_out_channels=(32, 64) ,				layers_per_block=2 ,				sample_size=32 ,				in_channels=3 ,				out_channels=3 ,				down_block_types=('DownBlock2D', 'AttnDownBlock2D') ,				up_block_types=('AttnUpBlock2D', 'UpBlock2D') ,				)
				return model







			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				snake_case_      		= self.dummy_uncond_unet
				snake_case_      		= ScoreSdeVeScheduler()

				snake_case_      		= ScoreSdeVePipeline(unet=__UpperCamelCase ,				scheduler=__UpperCamelCase							)
				sde_ve.to(__UpperCamelCase							)
				sde_ve.set_progress_bar_config(disable=__UpperCamelCase							)

				snake_case_      		= torch.manual_seed(0							)
				snake_case_      		= sde_ve(num_inference_steps=2 ,				output_type='numpy' ,				generator=__UpperCamelCase							).images

				snake_case_      		= torch.manual_seed(0							)
				snake_case_      		= sde_ve(num_inference_steps=2 ,				output_type='numpy' ,				generator=__UpperCamelCase ,				return_dict=__UpperCamelCase							)[
				    0
				]

				snake_case_      		= image[0, -3:, -3:, -1]
				snake_case_      		= image_from_tuple[0, -3:, -3:, -1]

				assert image.shape == (1, 32, 32, 3)
				snake_case_      		= np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]							)

				assert np.abs(image_slice.flatten() - expected_slice							).max() < 1E-2
				assert np.abs(image_from_tuple_slice.flatten() - expected_slice							).max() < 1E-2







@slow
@require_torch
class SCREAMING_SNAKE_CASE  (		unittest.TestCase							):






			"""simple docstring"""




			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				snake_case_      		= 'google/ncsnpp-church-256'
				snake_case_      		= UNetaDModel.from_pretrained(__UpperCamelCase							)

				snake_case_      		= ScoreSdeVeScheduler.from_pretrained(__UpperCamelCase							)

				snake_case_      		= ScoreSdeVePipeline(unet=__UpperCamelCase ,				scheduler=__UpperCamelCase							)
				sde_ve.to(__UpperCamelCase							)
				sde_ve.set_progress_bar_config(disable=__UpperCamelCase							)

				snake_case_      		= torch.manual_seed(0							)
				snake_case_      		= sde_ve(num_inference_steps=10 ,				output_type='numpy' ,				generator=__UpperCamelCase							).images

				snake_case_      		= image[0, -3:, -3:, -1]

				assert image.shape == (1, 2_56, 2_56, 3)

				snake_case_      		= np.array([0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]							)

				assert np.abs(image_slice.flatten() - expected_slice							).max() < 1E-2
