Class FixedPointEncoder

src/sympc/encoder/fp_encoder.py:23–141

Encoding/decoding a tensor to/from a fixed precision representation. This class was inspired from the Facebook Research - CrypTen project Attributes: _precision (int): the precision for the encoder _base (int): the base for the encoder _scale (int): the scale used f

class FixedPointEncoder:
    """Encoding/decoding a tensor to/from a fixed precision representation.

    This class was inspired from the Facebook Research - CrypTen project

    Attributes:
        _precision (int): the precision for the encoder
        _base (int): the base for the encoder
        _scale (int): the scale used for encoding/decoding
    """

    __slots__ = {"_precision", "_base", "_scale"}

    def __init__(self, base: int = 2, precision: int = 16):
        """Initialize FP Encoder.

        Args:
            base (int): The base for the encoder.
            precision (int): The precision for the encoder.
        """
        self._precision = precision
        self._base = base
        self._scale = base ** precision

    def encode(self, value: Union[torch.Tensor, float, int]) -> torch.LongTensor:
        """Encode a value using the FixedPoint Encoder.

        Args:
            value (Union[torch.Tensor, float, int]): value to encode

        Returns:
            torch.LongTensor: encoded value
        """
        if not isinstance(value, torch.Tensor):
            value = torch.tensor(data=[value])

        # Use the largest type
        long_value = (value * self._scale).long()

        return long_value

    def decode(self, value: Union[int, torch.Tensor]) -> torch.Tensor:
        """Decode a value using the FixedPoint Encoder.

        Args:
            value (Union[int, torch.Tensor]): Value to decode.

        Returns:
            torch.Tensor: Decoded tensor.

        Raises:
            ValueError: If value is a floating torch.Tensor.
        """
        if isinstance(value, torch.Tensor) and value.dtype.is_floating_point:
            raise ValueError(f"{value} should be converted to long format")

        if isinstance(value, int):
            value = torch.LongTensor([value])