






"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__  			=					{"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__  			=					[
					    """IBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """IBertForMaskedLM""",
					    """IBertForMultipleChoice""",
					    """IBertForQuestionAnswering""",
					    """IBertForSequenceClassification""",
					    """IBertForTokenClassification""",
					    """IBertModel""",
					    """IBertPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_ibert import (
										    IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    IBertForMaskedLM,
										    IBertForMultipleChoice,
										    IBertForQuestionAnswering,
										    IBertForSequenceClassification,
										    IBertForTokenClassification,
										    IBertModel,
										    IBertPreTrainedModel,
										)

else:
					import sys

					lowercase__  			=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset




@pytest.mark.parametrize('''dataset_size'''		,  [None, 400 * 2**20, 600 * 2**20]   )
@pytest.mark.parametrize('''input_in_memory_max_size'''		,  ['''default''', 0, 100 * 2**20, 900 * 2**20]   )
def 							a		(				snake_case__:   int		,  snake_case__:   Dict		,  snake_case__:   Dict   ):


				'''simple docstring'''
				if input_in_memory_max_size != "default":
								monkeypatch.setattr(datasets.config		,  '''IN_MEMORY_MAX_SIZE'''		,  snake_case__   )
				lowercase_	    =   datasets.config.IN_MEMORY_MAX_SIZE
				if input_in_memory_max_size == "default":
								assert in_memory_max_size == 0
				else:
								assert in_memory_max_size == input_in_memory_max_size
				if dataset_size and in_memory_max_size:
								lowercase_	    =   dataset_size < in_memory_max_size
				else:
								lowercase_	    =   False
				lowercase_	    =   is_small_dataset(snake_case__   )
				assert result == expected




