langchain_community.utilities.tensorflow_datasets
.TensorflowDatasetsΒΆ
- class langchain_community.utilities.tensorflow_datasets.TensorflowDatasets[source]ΒΆ
Bases:
BaseModel
Access to the TensorFlow Datasets.
The Current implementation can work only with datasets that fit in a memory.
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data.Datasets. To get started see the Guide: https://www.tensorflow.org/datasets/overview and the list of datasets: https://www.tensorflow.org/datasets/catalog/
overview#all_datasets
- You have to provide the sample_to_document_function: a function that
a sample from the dataset-specific format to the Document.
- dataset_nameΒΆ
the name of the dataset to load
- split_nameΒΆ
the name of the split to load. Defaults to βtrainβ.
- load_max_docsΒΆ
a limit to the number of loaded documents. Defaults to 100.
- sample_to_document_functionΒΆ
a function that converts a dataset sample to a Document
Example
from langchain_community.utilities import TensorflowDatasets def mlqaen_example_to_document(example: dict) -> Document: return Document( page_content=decode_to_str(example["context"]), metadata={ "id": decode_to_str(example["id"]), "title": decode_to_str(example["title"]), "question": decode_to_str(example["question"]), "answer": decode_to_str(example["answers"]["text"][0]), }, ) tsds_client = TensorflowDatasets( dataset_name="mlqa/en", split_name="train", load_max_docs=MAX_DOCS, sample_to_document_function=mlqaen_example_to_document, )
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- param dataset_name: str = ''ΒΆ
- param load_max_docs: int = 100ΒΆ
- param sample_to_document_function: Optional[Callable[[Dict], langchain_core.documents.base.Document]] = NoneΒΆ
- param split_name: str = 'train'ΒΆ
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model ΒΆ
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = βallowβ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model ΒΆ
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include β fields to include in new model
exclude β fields to exclude from new model, as with values this takes precedence over include
update β values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep β set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny ΒΆ
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- classmethod from_orm(obj: Any) Model ΒΆ
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode ΒΆ
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- lazy_load() Iterator[Document] [source]ΒΆ
Download a selected dataset lazily.
Returns: an iterator of Documents.
- classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ΒΆ
- classmethod parse_obj(obj: Any) Model ΒΆ
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ΒΆ
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny ΒΆ
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode ΒΆ
- classmethod update_forward_refs(**localns: Any) None ΒΆ
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- classmethod validate(value: Any) Model ΒΆ