





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_								=		{
    "configuration_bigbird_pegasus": [
        "BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BigBirdPegasusConfig",
        "BigBirdPegasusOnnxConfig",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase_								=		[
      "BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BigBirdPegasusForCausalLM",
      "BigBirdPegasusForConditionalGeneration",
      "BigBirdPegasusForQuestionAnswering",
      "BigBirdPegasusForSequenceClassification",
      "BigBirdPegasusModel",
      "BigBirdPegasusPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_bigbird_pegasus import (
      BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BigBirdPegasusConfig,
      BigBirdPegasusOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
        BigBirdPegasusForCausalLM,
        BigBirdPegasusForConditionalGeneration,
        BigBirdPegasusForQuestionAnswering,
        BigBirdPegasusForSequenceClassification,
        BigBirdPegasusModel,
        BigBirdPegasusPreTrainedModel,
    )


else:
  import sys

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






"""simple docstring"""
import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict



@pytest.mark.parametrize(
    '''split_dict''' ,   [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train''' ,   num_bytes=13_37 ,   num_examples=42 ,   dataset_name='''my_dataset'''							)}							),
        SplitDict({'''train''': SplitInfo(name='''train''' ,   num_bytes=13_37 ,   num_examples=42							)}							),
        SplitDict({'''train''': SplitInfo()}							),
    ] ,   )
def      __lowerCamelCase   (							a_     :		SplitDict							)			->      Optional[int]:
      __SCREAMING_SNAKE_CASE   :Tuple						=  split_dict._to_yaml_list()
      assert len(a_							) == len(a_							)
      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  SplitDict._from_yaml_list(a_							)
      for split_name, split_info in split_dict.items():
            # dataset_name field is deprecated, and is therefore not part of the YAML dump
            __SCREAMING_SNAKE_CASE   :int						=  None
            # the split name of split_dict takes over the name of the split info object
            __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  split_name
      assert split_dict == reloaded







@pytest.mark.parametrize(
    '''split_info''' ,   [SplitInfo(), SplitInfo(dataset_name=a_							), SplitInfo(dataset_name='''my_dataset'''							)]							)
def      __lowerCamelCase   (							a_     :		Dict							)			->      Any:
      # For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
      # field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  asdict(SplitDict({'''train''': split_info}							)							)
      assert "dataset_name" in split_dict_asdict["train"]
      assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name