



'''simple docstring'''





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 							lowerCamelCase	(					_snake_case	:    str  ,_snake_case	:    List[Any]  ,_snake_case	:    Tuple							):





    '''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









'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__          =  {
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE__          =  [
     "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
     "ClapModel",
     "ClapPreTrainedModel",
     "ClapTextModel",
     "ClapTextModelWithProjection",
     "ClapAudioModel",
     "ClapAudioModelWithProjection",
 ]
 SCREAMING_SNAKE_CASE__          =  ["ClapFeatureExtractor"]

if TYPE_CHECKING:
 from .configuration_clap import (
     CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
     ClapAudioConfig,
     ClapConfig,
     ClapTextConfig,
 )
 from .processing_clap import ClapProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_clap import ClapFeatureExtractor
  from .modeling_clap import (
      CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
      ClapAudioModel,
      ClapAudioModelWithProjection,
      ClapModel,
      ClapPreTrainedModel,
      ClapTextModel,
      ClapTextModelWithProjection,
  )


else:
 import sys

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




