Norms¶

Norms module.

class ffp.norms.Norms[source]¶

Bases: numpy.ndarray, ffp.io.Chunk

Embedding Norms.

Norms subclass numpy.ndarray, all typical numpy operations are available.

The ith norm is expected to correspond to the l2 norm of the ith row in the storage before normalizing it. Therefore, Norms should have at most the same length as a given Storage and are expected to match the length of the Vocabulary.

static chunk_identifier()[source]¶

Get the ChunkIdentifier for this Chunk.

Returns: chunk_identifier
Return type: ChunkIdentifier

static read_chunk(file: BinaryIO) → ffp.norms.Norms [source]¶

Read the Chunk and return it.

The file must be positioned before the contents of the Chunk but after its header.

Parameters: file (BinaryIO) – a finalfusion file containing the given Chunk
Returns: chunk – The chunk read from the file.
Return type: Chunk

write_chunk(file: BinaryIO)[source]¶

Write the Chunk to a file.

Parameters: file (BinaryIO) – Output file for the Chunk

ffp.norms.load_norms(file: Union[str, bytes, int, os.PathLike]) → ffp.norms.Norms [source]¶

Load an Norms chunk from the given file.

Parameters: file (str, bytes, int, PathLike) – Finalfusion file with a norms chunk.
Returns: storage – The Norms from the file.
Return type: Norms
Raises: ValueError – If the file did not contain an Norms chunk.