


'''simple docstring'''

from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url

@pytest.mark.parametrize('''repo_id''',				['''canonical_dataset_name''', '''org-name/dataset-name'''])
@pytest.mark.parametrize('''path''',				['''filename.csv''', '''filename with blanks.csv'''])
@pytest.mark.parametrize('''revision''',				[None, '''v2'''])
def 							__magic_name__(						lowerCamelCase,				lowerCamelCase,				lowerCamelCase):
						__lowerCAmelCase							       =				hf_hub_url(repo_id=lowerCamelCase,				path=lowerCamelCase,				revision=lowerCamelCase)
						assert url == F"""https://huggingface.co/datasets/{repo_id}/resolve/{revision or "main"}/{quote(lowerCamelCase)}"""





'''simple docstring'''

from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable


_UpperCAmelCase				: str							    =				{
    """configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXJapaneseConfig"""],
    """tokenization_gpt_neox_japanese""": ["""GPTNeoXJapaneseTokenizer"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: Union[str, Any]							    =				[
	    """GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """GPTNeoXJapaneseForCausalLM""",
	    """GPTNeoXJapaneseLayer""",
	    """GPTNeoXJapaneseModel""",
	    """GPTNeoXJapanesePreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
	from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpt_neox_japanese import (
		    GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTNeoXJapaneseForCausalLM,
		    GPTNeoXJapaneseLayer,
		    GPTNeoXJapaneseModel,
		    GPTNeoXJapanesePreTrainedModel,
		)


else:
	import sys

	_UpperCAmelCase				: int							    =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

