
import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	lowercase					  =   min(re.search('^ +'			,							__SCREAMING_SNAKE_CASE							).end() if t.startswith(' '							) else 0 for t in string.splitlines()							)
	return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(__SCREAMING_SNAKE_CASE							)]							)


UpperCAmelCase     				=			'''\
---
language:
- zh
- en
task_ids:
- sentiment-classification
---
# Begin of markdown

Some cool dataset card
'''

UpperCAmelCase     				=			'''\
---
---
# Begin of markdown

Some cool dataset card
'''


UpperCAmelCase     				=			'''\
# Begin of markdown

Some cool dataset card
'''







class 	A_       (      unittest.TestCase       ):




	'''simple docstring'''


	def      SCREAMING_SNAKE_CASE__						(	self	):
		with tempfile.TemporaryDirectory() as tmp_dir:
			lowercase					  =   Path(snake_case	) / 'README.md'
			with open(snake_case		,   'w+'	) as readme_file:
				readme_file.write(snake_case	)
			lowercase					  =   DatasetMetadata.from_readme(snake_case	)
			self.assertDictEqual(snake_case		,   {'language': ['zh', 'en'], 'task_ids': ['sentiment-classification']}	)

			with open(snake_case		,   'w+'	) as readme_file:
				readme_file.write(snake_case	)
			lowercase					  =   DatasetMetadata.from_readme(snake_case	)
			self.assertDictEqual(snake_case		,   {}	)

			with open(snake_case		,   'w+'	) as readme_file:
				readme_file.write(snake_case	)
			lowercase					  =   DatasetMetadata.from_readme(snake_case	)
			self.assertEqual(snake_case		,   {}	)





	def      SCREAMING_SNAKE_CASE__						(	self	):
		lowercase					  =   _dedent(
		    '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            '	)
		assert DatasetMetadata.from_yaml_string(snake_case	)

		lowercase					  =   _dedent(
		    '\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            '	)
		with self.assertRaises(snake_case	):
			DatasetMetadata.from_yaml_string(snake_case	)

		lowercase					  =   _dedent(
		    '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the "Researcher") has requested permission to use the ImageNet database (the "Database") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            '	)
		assert DatasetMetadata.from_yaml_string(snake_case	)



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase     				=			{
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase     				=			[
	    '''DPRContextEncoderTokenizerFast''',
	    '''DPRQuestionEncoderTokenizerFast''',
	    '''DPRReaderTokenizerFast''',
	]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase     				=			[
	    '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DPRContextEncoder''',
	    '''DPRPretrainedContextEncoder''',
	    '''DPRPreTrainedModel''',
	    '''DPRPretrainedQuestionEncoder''',
	    '''DPRPretrainedReader''',
	    '''DPRQuestionEncoder''',
	    '''DPRReader''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase     				=			[
	    '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFDPRContextEncoder''',
	    '''TFDPRPretrainedContextEncoder''',
	    '''TFDPRPretrainedQuestionEncoder''',
	    '''TFDPRPretrainedReader''',
	    '''TFDPRQuestionEncoder''',
	    '''TFDPRReader''',
	]


if TYPE_CHECKING:
	from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
	from .tokenization_dpr import (
	    DPRContextEncoderTokenizer,
	    DPRQuestionEncoderTokenizer,
	    DPRReaderOutput,
	    DPRReaderTokenizer,
	)

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_dpr_fast import (
		    DPRContextEncoderTokenizerFast,
		    DPRQuestionEncoderTokenizerFast,
		    DPRReaderTokenizerFast,
		)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_dpr import (
		    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DPRContextEncoder,
		    DPRPretrainedContextEncoder,
		    DPRPreTrainedModel,
		    DPRPretrainedQuestionEncoder,
		    DPRPretrainedReader,
		    DPRQuestionEncoder,
		    DPRReader,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_dpr import (
		    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDPRContextEncoder,
		    TFDPRPretrainedContextEncoder,
		    TFDPRPretrainedQuestionEncoder,
		    TFDPRPretrainedReader,
		    TFDPRQuestionEncoder,
		    TFDPRReader,
		)

else:
	import sys

	UpperCAmelCase     				=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

