File size: 793 Bytes
efa0ad4 c9fbd14 efa0ad4 c9fbd14 efa0ad4 63d6e05 efa0ad4 53184fe 20533c7 efa0ad4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 |
import torch
from torch import nn
from sentence_transformers import SentenceTransformer
from regressor import *
import numpy as np
import os
ENCODER = os.getenv("ENCODER")
class NextUsRegressor(nn.Module):
def __init__(self):
super(NextUsRegressor, self).__init__()
self.embedder = SentenceTransformer(ENCODER)
self.regressor = WRegressor()
return
def forward(self, txts):
# expects a list of strings
if type(txts) == str:
txts = [txts]
embedded = self.embedder.encode(np.array(txts))
embedded_tensor = torch.tensor(embedded, dtype=torch.float32)
regressed = self.regressor(embedded_tensor)
val = regressed.flatten().tolist()[0]
return round(val, 4)
|