File size: 853 Bytes
8514b06 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 |
import torch
from torch import nn
from transformers import DistilBertModel, DistilBertTokenizer
class MultilabelClassifier(nn.Module):
"""Base model for multilabel classification supporting different backbones"""
def __init__(self, model_name, num_labels, dropout=0.1):
super(MultilabelClassifier, self).__init__()
self.backbone = DistilBertModel.from_pretrained(model_name)
self.dropout = nn.Dropout(dropout)
self.classifier = nn.Linear(768, num_labels)
self.sigmoid = nn.Sigmoid()
def forward(self, input_ids, attention_mask):
outputs = self.backbone(input_ids=input_ids, attention_mask=attention_mask)
pooled_output = outputs.last_hidden_state[:, 0]
x = self.dropout(pooled_output)
logits = self.classifier(x)
return self.sigmoid(logits)
|