




'''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():

_snake_case				:				Dict       							=		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'
)


_snake_case				:				int       							=		{
    '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': []},
                    ],
                },
            ],
        }
    ],
}


_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### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'


_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#### Extra Ignored Subsection\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'

_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': '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': []},
                    ],
                },
            ],
        }
    ],
}

_snake_case				:				Union[str, 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'

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

_snake_case				:				Dict       							=		'\\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'

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

_snake_case				:				List[str]       							=		'\\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'

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

_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\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n'
_snake_case				:				Union[str, Any]       							=		'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).'


_snake_case				:				str       							=		'\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n'
_snake_case				:				List[Any]       							=		'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\'.'

_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### Languages\nLanguage Text\n'

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


_snake_case				:				Dict       							=		'\\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'

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

_snake_case				:				Dict       							=		'\\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'
_snake_case				:				Union[str, Any]       							=		'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.'

_snake_case				:				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'

_snake_case				:				Union[str, Any]       							=		'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.'

_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'

_snake_case				:				Dict       							=		'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.'

_snake_case				:				Union[str, Any]       							=		''

_snake_case				:				Any       							=		'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.'

_snake_case				:				Dict       							=		'\\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'

_snake_case				:				List[Any]       							=		'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 		snake_case_   (UpperCamelCase	:  List[str]			,						UpperCamelCase	:  int				):





							'''simple docstring'''


							assert ReadMe.from_string(UpperCamelCase			,						UpperCamelCase				).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 		snake_case_   (UpperCamelCase	:  int			,						UpperCamelCase	:  Union[str, Any]				):





							'''simple docstring'''


							with pytest.raises(UpperCamelCase			,						match=re.escape(expected_error.format(path='''root'''				)				)				):
														_a     					=    ReadMe.from_string(UpperCamelCase			,						UpperCamelCase				)
														readme.validate()
@pytest.mark.parametrize(
    '''readme_md, expected_error'''			,						[
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]			,						)
def 		snake_case_   (UpperCamelCase	:  Dict			,						UpperCamelCase	:  int				):





							'''simple docstring'''


							with pytest.raises(UpperCamelCase			,						match=re.escape(expected_error.format(path='''root'''				)				)				):
														ReadMe.from_string(UpperCamelCase			,						UpperCamelCase				)
@pytest.mark.parametrize(
    '''readme_md,'''			,						[
        (README_MULTIPLE_SAME_HEADING_1),
    ]			,						)
def 		snake_case_   (UpperCamelCase	:  Optional[Any]				):





							'''simple docstring'''


							ReadMe.from_string(UpperCamelCase			,						UpperCamelCase			,						suppress_parsing_errors=UpperCamelCase				)
@pytest.mark.parametrize(
    '''readme_md, expected_dict'''			,						[
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ]			,						)
def 		snake_case_   (UpperCamelCase	:  Optional[int]			,						UpperCamelCase	:  str				):





							'''simple docstring'''


							with tempfile.TemporaryDirectory() as tmp_dir:
														_a     					=    Path(UpperCamelCase				) / '''README.md'''
														with open(UpperCamelCase			,						'''w+'''				) as readme_file:
																					readme_file.write(UpperCamelCase				)
														_a     					=    ReadMe.from_readme(UpperCamelCase			,						UpperCamelCase				).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 		snake_case_   (UpperCamelCase	:  int			,						UpperCamelCase	:  Tuple				):





							'''simple docstring'''


							with tempfile.TemporaryDirectory() as tmp_dir:
														_a     					=    Path(UpperCamelCase				) / '''README.md'''
														with open(UpperCamelCase			,						'''w+'''				) as readme_file:
																					readme_file.write(UpperCamelCase				)
														_a     					=    expected_error.format(path=UpperCamelCase				)
														with pytest.raises(UpperCamelCase			,						match=re.escape(UpperCamelCase				)				):
																					_a     					=    ReadMe.from_readme(UpperCamelCase			,						UpperCamelCase				)
																					readme.validate()
@pytest.mark.parametrize(
    '''readme_md, expected_error'''			,						[
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]			,						)
def 		snake_case_   (UpperCamelCase	:  Dict			,						UpperCamelCase	:  List[Any]				):





							'''simple docstring'''


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

@pytest.mark.parametrize(
    '''readme_md,'''			,						[
        (README_MULTIPLE_SAME_HEADING_1),
    ]			,						)
def 		snake_case_   (UpperCamelCase	:  Optional[Any]				):





							'''simple docstring'''


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







'''simple docstring'''


import unittest

from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
				import torch

				from transformers.models.trocr.modeling_trocr import TrOCRDecoder, TrOCRForCausalLM

@require_torch
class       A   :







							def __init__(  self	:  Union[str, Any]							,      lowerCAmelCase_	:  List[Any]							,      lowerCAmelCase_	:  Union[str, Any]=99							,      lowerCAmelCase_	:  Optional[int]=13							,      lowerCAmelCase_	:  Tuple=16							,      lowerCAmelCase_	:  Optional[int]=7							,      lowerCAmelCase_	:  Optional[Any]=True							,      lowerCAmelCase_	:  Union[str, Any]=True							,      lowerCAmelCase_	:  Any=True							,      lowerCAmelCase_	:  Union[str, Any]=False							,      lowerCAmelCase_	:  int=True							,      lowerCAmelCase_	:  Tuple=2							,      lowerCAmelCase_	:  Any=32							,      lowerCAmelCase_	:  str=4							,      lowerCAmelCase_	:  Optional[Any]=4							,      lowerCAmelCase_	:  Optional[Any]=30							,      lowerCAmelCase_	:  int=0							,      lowerCAmelCase_	:  Any=1							,      lowerCAmelCase_	:  str=2							,      lowerCAmelCase_	:  Union[str, Any]=None							,      )      ->							Any:


														"""simple docstring"""


														_a     					=    parent
														_a     					=    batch_size
														_a     					=    decoder_seq_length
														# For common tests
														_a     					=    self.decoder_seq_length
														_a     					=    is_training
														_a     					=    use_attention_mask
														_a     					=    use_labels

														_a     					=    vocab_size
														_a     					=    d_model
														_a     					=    d_model
														_a     					=    decoder_layers
														_a     					=    decoder_layers
														_a     					=    decoder_ffn_dim
														_a     					=    decoder_attention_heads
														_a     					=    decoder_attention_heads
														_a     					=    eos_token_id
														_a     					=    bos_token_id
														_a     					=    pad_token_id
														_a     					=    decoder_start_token_id
														_a     					=    use_cache
														_a     					=    max_position_embeddings

														_a     					=    None
														_a     					=    decoder_seq_length
														_a     					=    2
														_a     					=    1







							def        __lowerCAmelCase      (  self	:  str )      ->							str:


														"""simple docstring"""


														_a     					=    ids_tensor([self.batch_size, self.decoder_seq_length]							,      self.vocab_size )

														_a     					=    None
														if self.use_attention_mask:
																					_a     					=    ids_tensor([self.batch_size, self.decoder_seq_length]							,      vocab_size=2 )

														_a     					=    None
														if self.use_labels:
																					_a     					=    ids_tensor([self.batch_size, self.decoder_seq_length]							,      self.vocab_size )

														_a     					=    TrOCRConfig(
														    vocab_size=self.vocab_size							,      d_model=self.d_model							,      decoder_layers=self.decoder_layers							,      decoder_ffn_dim=self.decoder_ffn_dim							,      decoder_attention_heads=self.decoder_attention_heads							,      eos_token_id=self.eos_token_id							,      bos_token_id=self.bos_token_id							,      use_cache=self.use_cache							,      pad_token_id=self.pad_token_id							,      decoder_start_token_id=self.decoder_start_token_id							,      max_position_embeddings=self.max_position_embeddings							,      )

														return (config, input_ids, attention_mask, lm_labels)







							def        __lowerCAmelCase      (  self	:  List[str]							,      lowerCAmelCase_	:  Any							,      lowerCAmelCase_	:  Dict							,      lowerCAmelCase_	:  Optional[Any]							,      lowerCAmelCase_	:  int							,      )      ->							int:


														"""simple docstring"""


														_a     					=    True
														_a     					=    TrOCRDecoder(config=lowerCAmelCase_ ).to(lowerCAmelCase_ ).eval()
														_a     					=    input_ids[:2]

														input_ids[input_ids == 0] += 1
														# first forward pass
														_a     					=    model(lowerCAmelCase_							,      use_cache=lowerCAmelCase_ )
														_a     					=    model(lowerCAmelCase_ )
														_a     					=    model(lowerCAmelCase_							,      use_cache=lowerCAmelCase_ )

														self.parent.assertTrue(len(lowerCAmelCase_ ) == len(lowerCAmelCase_ ) )
														self.parent.assertTrue(len(lowerCAmelCase_ ) == len(lowerCAmelCase_ ) + 1 )

														_a     					=    outputs['''past_key_values''']

														# create hypothetical next token and extent to next_input_ids
														_a     					=    ids_tensor((2, 1)							,      config.vocab_size - 1 ) + 1

														# append to next input_ids and
														_a     					=    torch.cat([input_ids, next_tokens]							,      dim=-1 )

														_a     					=    model(lowerCAmelCase_ )['''last_hidden_state''']
														_a     					=    model(lowerCAmelCase_							,      past_key_values=lowerCAmelCase_ )['''last_hidden_state''']

														# select random slice
														_a     					=    ids_tensor((1,)							,      output_from_past.shape[-1] ).item()
														_a     					=    output_from_no_past[:, next_input_ids.shape[-1] - 1, random_slice_idx].detach()
														_a     					=    output_from_past[:, 0, random_slice_idx].detach()

														# test that outputs are equal for slice
														assert torch.allclose(lowerCAmelCase_							,      lowerCAmelCase_							,      atol=1e-3 )







							def        __lowerCAmelCase      (  self	:  int )      ->							List[str]:


														"""simple docstring"""


														_a     					=    self.prepare_config_and_inputs()
														_a					,							_a					,							_a					,							_a     					=    config_and_inputs

														_a     					=    {'''input_ids''': input_ids, '''attention_mask''': attention_mask}
														return config, inputs_dict



@require_torch
class       A   (		_a					,_a					,_a					,unittest.TestCase   ):
							lowercase_          =    (TrOCRDecoder, TrOCRForCausalLM) if is_torch_available() else ()
							lowercase_          =    (TrOCRForCausalLM,) if is_torch_available() else ()
							lowercase_          =    {'text-generation': TrOCRForCausalLM} if is_torch_available() else {}
							lowercase_          =    True
							lowercase_          =    False







							def        __lowerCAmelCase      (  self	:  List[str] )      ->							str:


														"""simple docstring"""


														_a     					=    TrOCRStandaloneDecoderModelTester(self							,      is_training=lowerCAmelCase_ )
														_a     					=    ConfigTester(self							,      config_class=lowerCAmelCase_ )







							def        __lowerCAmelCase      (  self	:  List[str] )      ->							Any:


														"""simple docstring"""


														pass







							def        __lowerCAmelCase      (  self	:  Tuple )      ->							Dict:


														"""simple docstring"""


														pass







							def        __lowerCAmelCase      (  self	:  Tuple )      ->							Optional[int]:


														"""simple docstring"""


														pass







							def        __lowerCAmelCase      (  self	:  Union[str, Any] )      ->							Optional[int]:


														"""simple docstring"""


														self.config_tester.run_common_tests()







							def        __lowerCAmelCase      (  self	:  Tuple )      ->							Optional[int]:


														"""simple docstring"""


														_a     					=    self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_decoder_model_past(*lowerCAmelCase_ )







							def        __lowerCAmelCase      (  self	:  Optional[int] )      ->							str:


														"""simple docstring"""


														return







							@unittest.skip('''The model doesn\'t support left padding''' )  # and it's not used enough to be worth fixing :)
							def        __lowerCAmelCase      (  self	:  Union[str, Any] )      ->							Optional[int]:


														"""simple docstring"""


														pass

