Models

class TabularModel

TabularModel.build

@classmethod
def build(cls: type["TabularModel"],
          preproc: TabularPreproc,
          size: str | Size | TabularModelSize,
          block: str | None = None,
          dropout: float | None = 0.12) -> "TabularModel"

Tabular model to generate synthetic tabular relational data.

Arguments:

• preproc - A TabularPreproc object.
• size - The size configuration of the model. Could be either a TabularModelSize object, a Size object, or a string representation of the latter.
• block - The block type. The possible values depend on whether the data is single table or multi table. For a single table, either ‘free’ (default), ‘causal’, or ‘lstm’. For multi table data, either ‘free’ (default) or ‘lstm’.
• dropout - The dropout probability.

Returns:

A TabularModel instance.

TabularModel.generate

def generate(n_samples: int | None = None,
             ctx: pd.DataFrame | None = None,
             batch_size: int = 0,
             max_block_size: int = 0,
             temp: float = 1.0) -> RelationalData

Generate synthetic relational data.

Arguments:

• n_samples - Desired number of samples in the root table. Must be given if and only if ctx is nto provided.
• ctx - The first columns of the root table from where to start a conditional generation. If provided, n_samples should not be given.
• batch_size - Batch size used during generation. If 0, generate all data in a single batch.
• max_block_size - Maximum length for each generated sample. Active only for multi-table datasets. If 0, no limit is enforced.
• temp - Temperature parameter for sampling.

Returns:

A RelationalData object with the generated synthetic tabular data.

TabularModel.save

def save(path: Path | str) -> None

Save the model to a checkpoint at the given path.

TabularModel.load

@classmethod
def load(cls: type["TabularModel"], path: Path | str) -> "TabularModel"

Load the model from the checkpoint at the given path.

class TextModel

TextModel.build

@classmethod
def build(cls: type["TextModel"],
          preproc: TextPreproc,
          size: str | Size | TextModelSize,
          block_size: int,
          dropout: float | None = 0.12) -> "TextModel"

Text model to generate synthetic text columns of a table which is part of a relational structure.

Arguments:

• preproc - A TextPreproc object.
• size - The size configuration of the model. Could be either a Size object, a TextModelSize object or a string representation of such objects.
• block_size - Maximum text sequence length that the model can process.
• dropout - The dropout probability.

Returns:

A TextModel instance.

TextModel.build_from_pretrained

@classmethod
def build_from_pretrained(cls: type["TextModel"],
                          preproc: TextPreproc,
                          path: Path | str,
                          block_size: int | None = None) -> "TextModel"

Build a text model from a pretrained model.

Arguments:

• preproc - A TextPreproc object.
• path - The path to the checkpoint of the pre-trained model.
• block_size - Maximum text sequence length that the model can process during fine-tuning.

Returns:

A TextModel instance with the weights loaded from the pre-trained model.

TextModel.generate

def generate(data: RelationalData,
             batch_size: int = 0,
             max_text_len: int = 0,
             temp: float = 1.0) -> RelationalData

Generate text columns in the current table.

Arguments:

• data - A RelationalData object containing synthetic data.
• batch_size - Batch size used during generation. If 0, generate all data in a single batch.
• max_text_len - Maximum length for the generated text. If 0, the maximum possible value is used, namely the value of the TabularModel.max_block_size attribute.
• temp - Temperature parameter for sampling.

Returns:

A RelationalData object with the generated synthetic text data.

TextModel.save

def save(path: Path | str) -> None

Save the model to a checkpoint at the given path.

TextModel.load

@classmethod
def load(cls: type["TextModel"], path: Path | str) -> "TextModel"

Load the model from the checkpoint at the given path.

class Size

Enumeration class representing different model sizes. Supported sizes are: SMALL, MEDIUM and LARGE.

class TabularModelSize

Model size for TabularModel objects.

Arguments:

• n_layers - Number of internal layers.
• h - Number of heads.
• d - Size of the internal dimension.

TabularModelSize.from_size

@classmethod
def from_size(cls, size: Size | str) -> "TabularModelSize"

Create an instance based on a given Size or its string representation.

Arguments:

• size - A Size object.

class TextModelSize

Model size for TextModel objects.

Arguments:

• n_layers - Number of internal layers.
• h - Number of heads.
• d - Size of the internal dimension.

TextModelSize.from_size

@classmethod
def from_size(cls, size: Size | str) -> "TextModelSize"

Create an instance based on a given Size or its string representation.

Arguments:

• size - A Size or a str representing a Size.