





"""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 						lowerCAmelCase_      (    lowercase_  :				str					, lowercase_  :				Any						):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE					:     Optional[int]   				=			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}}'''						)
 __SCREAMING_SNAKE_CASE					:     Union[str, Any]   				=			DatasetInfosDict.from_directory(lowercase_						)
 assert dataset_infos
 assert dataset_infos["default"].dataset_size == 42




@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=42					, ),
    ]					, )
def 						lowerCAmelCase_      (    lowercase_  :				Tuple					, lowercase_  :				DatasetInfo						):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE					:     Any   				=			str(lowercase_						)
 dataset_info.write_to_directory(lowercase_						)
 __SCREAMING_SNAKE_CASE					:     List[Any]   				=			DatasetInfo.from_directory(lowercase_						)
 assert dataset_info == reloaded
 assert os.path.exists(os.path.join(lowercase_					, '''dataset_info.json'''						)						)




def 						lowerCAmelCase_      (    ):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE					:     Union[str, Any]   				=			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''': 42}]					, download_checksums={}					, download_size=1337					, post_processing_size=442					, dataset_size=1234					, size_in_bytes=1337 + 442 + 1234					, )
 __SCREAMING_SNAKE_CASE					:     int   				=			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)						)
 __SCREAMING_SNAKE_CASE					:     str   				=			yaml.safe_dump(lowercase_						)
 __SCREAMING_SNAKE_CASE					:     str   				=			yaml.safe_load(lowercase_						)
 assert dataset_info_yaml_dict == reloaded




def 						lowerCAmelCase_      (    ):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE					:     Tuple   				=			DatasetInfo()
 __SCREAMING_SNAKE_CASE					:     Optional[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=42					, )
            }						),
        DatasetInfosDict(
            {
                '''v1''': DatasetInfo(dataset_size=42						),
                '''v2''': DatasetInfo(dataset_size=1337						),
            }						),
    ]					, )
def 						lowerCAmelCase_      (    lowercase_  :				Tuple					, lowercase_  :				DatasetInfosDict						):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE					:     Union[str, Any]   				=			str(lowercase_						)
 dataset_infos_dict.write_to_directory(lowercase_						)
 __SCREAMING_SNAKE_CASE					:     Tuple   				=			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():
  __SCREAMING_SNAKE_CASE					:     str   				=			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
  __SCREAMING_SNAKE_CASE					:     Optional[Any]   				=			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_flax_available,
    is_tf_available,
    is_torch_available,
)


_UpperCamelCase						:  Optional[int]							       =				{
    "configuration_vision_text_dual_encoder": ["VisionTextDualEncoderConfig"],
    "processing_vision_text_dual_encoder": ["VisionTextDualEncoderProcessor"],
}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase						:  Dict							       =				["VisionTextDualEncoderModel"]


try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase						:  int							       =				["FlaxVisionTextDualEncoderModel"]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase						:  Tuple							       =				["TFVisionTextDualEncoderModel"]


if TYPE_CHECKING:
     from .configuration_vision_text_dual_encoder import VisionTextDualEncoderConfig
     from .processing_vision_text_dual_encoder import VisionTextDualEncoderProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_vision_text_dual_encoder import VisionTextDualEncoderModel

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_vision_text_dual_encoder import FlaxVisionTextDualEncoderModel

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_vision_text_dual_encoder import TFVisionTextDualEncoderModel


else:
     import sys

     _UpperCamelCase						:  Optional[int]							       =				_LazyModule(__name__, globals()["__file__"], _import_structure)





