
'''simple docstring'''





import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict







@pytest.mark.parametrize(
    "files"   ,       [
        ["full:README.md", "dataset_infos.json"],
        ["empty:README.md", "dataset_infos.json"],
        ["dataset_infos.json"],
        ["full:README.md"],
    ]   ,       )
def snake_case_     (					lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Tuple				       =							tmp_path_factory.mktemp("dset_infos_dir"		)
  if "full:README.md" in files:
    with open(dataset_infos_dir / "README.md"   ,       "w"		) as f:
      f.write("---\ndataset_info:\n  dataset_size: 42\n---"		)
  if "empty:README.md" in files:
    with open(dataset_infos_dir / "README.md"   ,       "w"		) as f:
      f.write(""		)
    # we want to support dataset_infos.json for backward compatibility
  if "dataset_infos.json" in files:
    with open(dataset_infos_dir / "dataset_infos.json"   ,       "w"		) as f:
      f.write("{\"default\": {\"dataset_size\": 42}}"		)
  UpperCAmelCase__      :					List[str]				       =							DatasetInfosDict.from_directory(lowercase__		)
  assert dataset_infos
  assert dataset_infos["default"].dataset_size == 4_2







@pytest.mark.parametrize(
    "dataset_info"   ,       [
        DatasetInfo(),
        DatasetInfo(
            description="foo"   ,       features=Features({"a": Value("int32"		)}		)   ,       builder_name="builder"   ,       config_name="config"   ,       version="1.0.0"   ,       splits=[{"name": "train"}]   ,       download_size=4_2   ,       ),
    ]   ,       )
def snake_case_     (					lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Optional[int]				       =							str(lowercase__		)
  dataset_info.write_to_directory(lowercase__		)
  UpperCAmelCase__      :					Union[str, Any]				       =							DatasetInfo.from_directory(lowercase__		)
  assert dataset_info == reloaded
  assert os.path.exists(os.path.join(lowercase__   ,       "dataset_info.json"		)		)







def snake_case_     (					):
  UpperCAmelCase__      :					Tuple				       =							DatasetInfo(
      description="foo"   ,       citation="bar"   ,       homepage="https://foo.bar"   ,       license="CC0"   ,       features=Features({"a": Value("int32"		)}		)   ,       post_processed={}   ,       supervised_keys=()   ,       task_templates=[]   ,       builder_name="builder"   ,       config_name="config"   ,       version="1.0.0"   ,       splits=[{"name": "train", "num_examples": 4_2}]   ,       download_checksums={}   ,       download_size=1_3_3_7   ,       post_processing_size=4_4_2   ,       dataset_size=1_2_3_4   ,       size_in_bytes=1_3_3_7 + 4_4_2 + 1_2_3_4   ,       )
  UpperCAmelCase__      :					Dict				       =							dataset_info._to_yaml_dict()
  assert sorted(lowercase__		) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML		)
  for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
    assert key in dataset_info_yaml_dict
    assert isinstance(dataset_info_yaml_dict[key]   ,       (list, dict, int, str)		)
  UpperCAmelCase__      :					str				       =							yaml.safe_dump(lowercase__		)
  UpperCAmelCase__      :					Dict				       =							yaml.safe_load(lowercase__		)
  assert dataset_info_yaml_dict == reloaded







def snake_case_     (					):
  UpperCAmelCase__      :					Tuple				       =							DatasetInfo()
  UpperCAmelCase__      :					Union[str, Any]				       =							dataset_info._to_yaml_dict()
  assert dataset_info_yaml_dict == {}







@pytest.mark.parametrize(
    "dataset_infos_dict"   ,       [
        DatasetInfosDict(),
        DatasetInfosDict({"default": DatasetInfo()}		),
        DatasetInfosDict({"my_config_name": DatasetInfo()}		),
        DatasetInfosDict(
            {
                "default": DatasetInfo(
                    description="foo"   ,       features=Features({"a": Value("int32"		)}		)   ,       builder_name="builder"   ,       config_name="config"   ,       version="1.0.0"   ,       splits=[{"name": "train"}]   ,       download_size=4_2   ,       )
            }		),
        DatasetInfosDict(
            {
                "v1": DatasetInfo(dataset_size=4_2		),
                "v2": DatasetInfo(dataset_size=1_3_3_7		),
            }		),
    ]   ,       )
def snake_case_     (					lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					List[Any]				       =							str(lowercase__		)
  dataset_infos_dict.write_to_directory(lowercase__		)
  UpperCAmelCase__      :					List[Any]				       =							DatasetInfosDict.from_directory(lowercase__		)

  # the config_name of the dataset_infos_dict take over the attribute
  for config_name, dataset_info in dataset_infos_dict.items():
    UpperCAmelCase__      :					Optional[int]				       =							config_name
    # the yaml representation doesn't include fields like description or citation
    # so we just test that we can recover what we can from the yaml
    UpperCAmelCase__      :					Optional[int]				       =							DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()		)
  assert dataset_infos_dict == reloaded

  if dataset_infos_dict:
    assert os.path.exists(os.path.join(lowercase__   ,       "README.md"		)		)





'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


SCREAMING_SNAKE_CASE     =       {}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE     =       ["""GPTSw3Tokenizer"""]


if TYPE_CHECKING:
      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_gpt_swa import GPTSwaTokenizer

else:
      import sys

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



