Source code for gnes.encoder.text.char

from typing import List

import numpy as np

from ..base import BaseTextEncoder
from ...helper import batching, as_numpy_array


[docs]class CharEmbeddingEncoder(BaseTextEncoder): """A random character embedding model. Only useful for testing""" is_trained = True def __init__(self, dim: int = 128, *args, **kwargs): super().__init__(*args, **kwargs) self.dim = dim self.offset = 32 self.unknown_idx = 96 # in total 96 printable chars and 2 special chars = 98 self._char_embedding = np.random.random([97, dim])
[docs] @batching @as_numpy_array def encode(self, text: List[str], *args, **kwargs) -> List[np.ndarray]: # tokenize text sent_embed = [] for sent in text: ids = [ord(c) - 32 if 32 <= ord(c) <= 127 else self.unknown_idx for c in sent] sent_embed.append(np.mean(self._char_embedding[ids], axis=0)) return sent_embed