






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(
    '''\
name: ""
allow_empty: false
allow_empty_text: true
subsections:
  - name: "Dataset Card for X" # First-level markdown heading
    allow_empty: false
    allow_empty_text: true
    subsections:
      - name: "Table of Contents"
        allow_empty: false
        allow_empty_text: false
        subsections: null
      - name: "Dataset Description"
        allow_empty: false
        allow_empty_text: false
        subsections:
          - name: "Dataset Summary"
            allow_empty: false
            allow_empty_text: false
            subsections: null
          - name: "Supported Tasks and Leaderboards"
            allow_empty: true
            allow_empty_text: true
            subsections: null
          - name: Languages
            allow_empty: false
            allow_empty_text: true
            subsections: null
'''
)


_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      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''


_a      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
#### Extra Ignored Subsection
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

_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      	=  '''\
---
---
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

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

_a      	=  '''\
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

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

_a      	=  '''\
---
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

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

_a      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
### Supported Tasks and Leaderboards
### Languages
Language Text
'''
_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      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
'''
_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      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Languages
Language Text
'''

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


_a      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
'''

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

_a      	=  '''\
---
language:
- zh
- en
---

## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''
_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      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
# Dataset Card My Dataset
'''

_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      	=  '''\
---
language:
- zh
- en
---

# Dataset Card My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

_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      	=  '''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

_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    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  List[str]:





						"""simple docstring"""



						assert ReadMe.from_string(__lowerCAmelCase ,		__lowerCAmelCase	).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    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  Any:





						"""simple docstring"""



						with pytest.raises(__lowerCAmelCase ,		match=re.escape(expected_error.format(path='root'	)	)	):
												_UpperCAmelCase									=			ReadMe.from_string(__lowerCAmelCase ,		__lowerCAmelCase	)
												readme.validate()


@pytest.mark.parametrize(
    'readme_md, expected_error' ,		[
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ] ,		)
def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  Union[str, Any]:





						"""simple docstring"""



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


@pytest.mark.parametrize(
    'readme_md,' ,		[
        (README_MULTIPLE_SAME_HEADING_1),
    ] ,		)
def __A    (      __lowerCAmelCase	)->  Optional[Any]:





						"""simple docstring"""



						ReadMe.from_string(__lowerCAmelCase ,		__lowerCAmelCase ,		suppress_parsing_errors=__lowerCAmelCase	)


@pytest.mark.parametrize(
    'readme_md, expected_dict' ,		[
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ] ,		)
def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  int:





						"""simple docstring"""



						with tempfile.TemporaryDirectory() as tmp_dir:
												_UpperCAmelCase									=			Path(__lowerCAmelCase	) / 'README.md'
												with open(__lowerCAmelCase ,		'w+'	) as readme_file:
																		readme_file.write(__lowerCAmelCase	)
												_UpperCAmelCase									=			ReadMe.from_readme(__lowerCAmelCase ,		__lowerCAmelCase	).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    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  int:





						"""simple docstring"""



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


@pytest.mark.parametrize(
    'readme_md, expected_error' ,		[
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ] ,		)
def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  Union[str, Any]:





						"""simple docstring"""



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


@pytest.mark.parametrize(
    'readme_md,' ,		[
        (README_MULTIPLE_SAME_HEADING_1),
    ] ,		)
def __A    (      __lowerCAmelCase	)->  Union[str, Any]:





						"""simple docstring"""



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

import argparse

import torch
from torch import nn

from transformers import MBartConfig, MBartForConditionalGeneration




def    lowerCAmelCase_ (     __A							)     ->				Dict:







      '''simple docstring'''


      UpperCAmelCase__								=  [
          "encoder.version",
          "decoder.version",
          "model.encoder.version",
          "model.decoder.version",
          "_float_tensor",
          "decoder.output_projection.weight",
      ]
      for k in ignore_keys:
            state_dict.pop(__A,  __A							)




def    lowerCAmelCase_ (     __A							)     ->				Optional[int]:







      '''simple docstring'''


      UpperCAmelCase__		,      UpperCAmelCase__								=  emb.weight.shape
      UpperCAmelCase__								=  nn.Linear(__A,  __A,  bias=__A							)
      UpperCAmelCase__								=  emb.weight.data
      return lin_layer




def    lowerCAmelCase_ (     __A,  __A="facebook/mbart-large-en-ro",  __A=False,  __A=False							)     ->				Tuple:







      '''simple docstring'''


      UpperCAmelCase__								=  torch.load(__A,  map_location="cpu"							)["model"]
      remove_ignore_keys_(__A							)
      UpperCAmelCase__								=  state_dict["encoder.embed_tokens.weight"].shape[0]

      UpperCAmelCase__								=  MBartConfig.from_pretrained(__A,  vocab_size=__A							)
      if mbart_aa and finetuned:
            UpperCAmelCase__								=  "relu"

      UpperCAmelCase__								=  state_dict["decoder.embed_tokens.weight"]
      UpperCAmelCase__								=  MBartForConditionalGeneration(__A							)
      model.model.load_state_dict(__A							)

      if finetuned:
            UpperCAmelCase__								=  make_linear_from_emb(model.model.shared							)

      return model


if __name__ == "__main__":
      UpperCamelCase__											=					argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          'fairseq_path', type=str, help='bart.large, bart.large.cnn or a path to a model.pt on local filesystem.'
      )
      parser.add_argument('pytorch_dump_folder_path', default=None, type=str, help='Path to the output PyTorch model.')
      parser.add_argument(
          '--hf_config',
          default='facebook/mbart-large-cc25',
          type=str,
          help='Which huggingface architecture to use: mbart-large',
      )
      parser.add_argument('--mbart_50', action='store_true', help='whether the model is mMART-50 checkpoint')
      parser.add_argument('--finetuned', action='store_true', help='whether the model is a fine-tuned checkpoint')
      UpperCamelCase__											=					parser.parse_args()
      UpperCamelCase__											=					convert_fairseq_mbart_checkpoint_from_disk(
          args.fairseq_path, hf_config_path=args.hf_config, finetuned=args.finetuned, mbart_aa=args.mbart_aa
      )
      model.save_pretrained(args.pytorch_dump_folder_path)



